TY - JOUR A1 - Kotak, Bhavya A1 - Kotak, Yash A1 - Brade, Katja A1 - Kubjatko, Tibor A1 - Schweiger, Hans-Georg T1 - Battery Crush Test Procedures in Standards and Regulation: Need for Augmentation and Harmonisation JF - Batteries N2 - Battery safety is a prominent concern for the deployment of electric vehicles (EVs). The battery powering an EV contains highly energetic active materials and flammable organic electrolytes. Usually, an EV battery catches fire due to its thermal runaway, either immediately at the time of the accident or can take a while to gain enough heat to ignite the battery chemicals. There are numerous battery abuse testing standards and regulations available globally. Therefore, battery manufacturers are always in dilemma to choose the safest one. Henceforth, to find the optimal outcome of these two major issues, six standards (SAE J2464:2009, GB/T 31485-2015:2015, FreedomCAR:2006, ISO 12405-3:2014, IEC 62660-2:2010, and SAND2017-6295:2017) and two regulations (UN/ECE-R100.02:2013 and GTR 20:2018), that are followed by more than fifty countries in the world, are investigated in terms of their abuse battery testing conditions (crush test). This research proves that there is a need for (a) augmenting these standards and regulations as they do not consider real-life vehicle crash scenarios, and (b) one harmonised framework should be developed, which can be adopted worldwide. These outcomes will solve the battery manufacturers dilemma and will also increase the safety of EV consumers. UR - https://doi.org/10.3390/batteries7030063 KW - lithium-ion battery KW - electric vehicle battery KW - battery standard KW - battery regulation KW - battery testing standard KW - battery testing regulation KW - abuse testing KW - harmonising battery standard KW - crush test procedure KW - battery incidents KW - battery standard and regulation augmentation Y1 - 2021 UR - https://doi.org/10.3390/batteries7030063 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-11083 SN - 2313-0105 VL - 7 IS - 3 PB - MDPI CY - Basel ER - TY - JOUR A1 - Sánchez Morales, Eduardo A1 - Dauth, Julian A1 - Huber, Bertold A1 - García Higuera, Andrés A1 - Botsch, Michael T1 - High precision outdoor and indoor reference state estimation for testing autonomous vehicles JF - Sensors N2 - A current trend in automotive research is autonomous driving. For the proper testing and validation of automated driving functions a reference vehicle state is required. Global Navigation Satellite Systems (GNSS) are useful in the automation of the vehicles because of their practicality and accuracy. However, there are situations where the satellite signal is absent or unusable. This research work presents a methodology that addresses those situations, thus largely reducing the dependency of Inertial Navigation Systems (INSs) on the SatNav. The proposed methodology includes (1) a standstill recognition based on machine learning, (2) a detailed mathematical description of the horizontation of inertial measurements, (3) sensor fusion by means of statistical filtering, (4) an outlier detection for correction data, (5) a drift detector, and (6) a novel LiDAR-based Positioning Method (LbPM) for indoor navigation. The robustness and accuracy of the methodology are validated with a state-of-the-art INS with Real-Time Kinematic (RTK) correction data. The results obtained show a great improvement in the accuracy of vehicle state estimation under adverse driving conditions, such as when the correction data is corrupted, when there are extended periods with no correction data and in the case of drifting. The proposed LbPM method achieves an accuracy closely resembling that of a system with RTK. UR - https://doi.org/10.3390/s21041131 KW - machine learning KW - autonomous vehicles KW - Inertial Navigation System KW - Satellite Navigation KW - Real-Time Kinematic KW - indoor navigation KW - reference state Y1 - 2021 UR - https://doi.org/10.3390/s21041131 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-10932 SN - 1424-8220 N1 - "This paper is an extended version of our paper published in : Sánchez Morales, E.; Botsch, M.; Huber, B.; García Higuera, A. High precision indoor positioning by means of LiDAR. In Proceedings of the 2019 DGON Inertial Sensors and Systems (ISS), Braunschweig, Germany, 10–11 September 2019." VL - 21 IS - 4 PB - MDPI CY - Basel ER - TY - JOUR A1 - Komsiyska, Lidiya A1 - Buchberger, Tobias A1 - Diehl, Simon A1 - Ehrensberger, Moritz A1 - Hanzl, Christian A1 - Hartmann, Christoph A1 - Hölzle, Markus A1 - Kleiner, Jan A1 - Lewerenz, Meinert A1 - Liebhart, Bernhard A1 - Schmid, Michael A1 - Schneider, Dominik A1 - Speer, Sascha A1 - Stöttner, Julia A1 - Terbrack, Christoph A1 - Hinterberger, Michael A1 - Endisch, Christian T1 - Critical review of intelligent battery systems BT - challenges, implementation, and potential for electric vehicles JF - Energies N2 - This review provides an overview of new strategies to address the current challenges of automotive battery systems: Intelligent Battery Systems. They have the potential to make battery systems more performant and future-proof for coming generations of electric vehicles. The essential features of Intelligent Battery Systems are the accurate and robust determination of cell individual states and the ability to control the current of each cell by reconfiguration. They enable high-level functions like fault diagnostics, multi-objective balancing strategies, multilevel inverters, and hybrid energy storage systems. State of the art and recent advances in these topics are compiled and critically discussed in this article. A comprising, critical discussion of the implementation aspects of Intelligent Battery Systems complements the review. We touch on sensing, battery topologies and management, switching elements, communication architecture, and impact on the single-cell. This review contributes to transferring the best technologies from research to product development. UR - https://doi.org/10.3390/en14185989 KW - smart battery KW - intelligent battery system KW - advanced monitoring KW - reconfigurable battery KW - battery management system KW - electric vehicle Y1 - 2021 UR - https://doi.org/10.3390/en14185989 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-10132 SN - 1996-1073 VL - 14 IS - 18 PB - MDPI CY - Basel ER - TY - JOUR A1 - Ahlberg Tidblad, Annika A1 - Edström, Kristina A1 - Hernández, Guiomar A1 - de Meatza, Iratxe A1 - Landa-Medrano, Imanol A1 - Jacas Biendicho, Jordi A1 - Trilla, Lluís A1 - Buysse, Maarten A1 - Ierides, Marcos A1 - Perez Horno, Beatriz A1 - Kotak, Yash A1 - Schweiger, Hans-Georg A1 - Koch, Daniel A1 - Kotak, Bhavya T1 - Future Material Developments for Electric Vehicle Battery Cells Answering Growing Demands from an End-User Perspective JF - Energies N2 - Nowadays, batteries for electric vehicles are expected to have a high energy density, allow fast charging and maintain long cycle life, while providing affordable traction, and complying with stringent safety and environmental standards. Extensive research on novel materials at cell level is hence needed for the continuous improvement of the batteries coupled towards achieving these requirements. This article firstly delves into future developments in electric vehicles from a technology perspective, and the perspective of changing end-user demands. After these end-user needs are defined, their translation into future battery requirements is described. A detailed review of expected material developments follows, to address these dynamic and changing needs. Developments on anodes, cathodes, electrolyte and cell level will be discussed. Finally, a special section will discuss the safety aspects with these increasing end-user demands and how to overcome these issues. UR - https://doi.org/10.3390/en14144223 KW - electric vehicle KW - battery material KW - anode KW - cathode KW - electrolyte KW - battery safety KW - end-user demands Y1 - 2021 UR - https://doi.org/10.3390/en14144223 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-10149 SN - 1996-1073 VL - 14 IS - 14 PB - MDPI CY - Basel ER - TY - JOUR A1 - Geisbauer, Christian A1 - Wöhrl, Katharina A1 - Mittmann, Christoph A1 - Schweiger, Hans-Georg T1 - Review of Safety Aspects of Calendar Aged Lithium Ion Batteries JF - Journal of the Electrochemical Society N2 - Nowadays, lithium ion batteries have found their place in a various field of portable applications. With the upcoming of electrically propelled vehicles, it is mandatory to guarantee a safe and predictable behavior during the whole lifetime and not only after manufacturing during performance tests. To gain a general overview of the abuse behavior, research on the topic of abusive tests on calendar-aged cells is being investigated, split up depending on the electrode composition and lined up against each other. It can be shown, that almost all abuse experiments have been performed with external heating tests in the past, still leaving research gaps that need to be filled. UR - https://doi.org/10.1149/1945-7111/ab89bf Y1 - 2020 UR - https://doi.org/10.1149/1945-7111/ab89bf UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-10183 SN - 1945-7111 VL - 167 IS - 9 PB - IOP Publishing CY - Bristol ER - TY - JOUR A1 - Shirur, Naveen A1 - Birkner, Christian A1 - Henze, Roman A1 - Deserno, Thomas Martin T1 - Tactile Occupant Detection Sensor for Automotive Airbag JF - Energies N2 - Automotive airbags protect occupants from crash forces during severe vehicle collisions. They absorb energy and restrain the occupants by providing a soft cushion effect known as the restraint effect. Modern airbags offer partial restraint effect control by controlling the bag’s vent holes and providing multi-stage deployment. Full restraint effect control is still a challenge because the closed-loop restraint control system needs airbag–occupant contact and interaction feedback. In this work, we have developed novel single and matrix capacitive tactile sensors to measure the occupant’s contact data. They can be integrated with the airbag surface and folded to follow the dynamic airbag shape during the deployment. The sensors are tested under a low-velocity pendulum impact and benchmarked with high-speed test videos. The results reveal that the single sensor can successfully measure occupant–airbag contact time and estimate the area, while the contact position is additionally identified from the matrix sensor. UR - https://doi.org/10.3390/en14175288 KW - automotive airbag KW - capacitive tactile sensor KW - occupant detection KW - passive safety KW - vehicle crash Y1 - 2021 UR - https://doi.org/10.3390/en14175288 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-9210 SN - 1996-1073 VL - 14 IS - 17 PB - MDPI CY - Basel ER - TY - JOUR A1 - Liu, E A1 - Conti, Fosca A1 - Bhogaraju, Sri Krishna A1 - Signorini, Raffaella A1 - Pedron, Danilo A1 - Wunderle, Bernhard A1 - Elger, Gordon T1 - Thermomechanical stress in GaN-LEDs soldered onto Cu substrates studied using finite element method and Raman spectroscopy JF - Journal of Raman Spectroscopy N2 - Local thermomechanical stress can cause failures in semiconductor packages during long-time operation under harsh environmental conditions. This study helps to explain the packaging-induced stress in blue GaN-LEDs soldered onto copper substrates using AuSn alloy as lead-free interconnect material. Based on the finite element method, a virtual prototype is developed to simulate the thermomechanical behavior and stress in the LED and in the complete LED/AuSn/Cu assembly considering plastic and viscoplastic strain. The investigations were performed by varying the temperature between −50°C and 180°C. To validate the model, the simulation results are compared to experimental data collected with Raman spectroscopy. Studies of the urn:x-wiley:03770486:media:jrs5947:jrs5947-math-0003 phonon mode of GaN semiconductor are elaborated to understand the induced thermomechanical stress. The model enables evaluation of the stress in the interfaces of the assembly, which otherwise cannot be accessed by measurements. It serves to predict how assemblies would perform, before committing resources to build a physical prototype. UR - https://doi.org/10.1002/jrs.5947 KW - finite element method KW - gallium nitride (GaN) KW - LED KW - semiconductor KW - thermomechanical stress Y1 - 2020 UR - https://doi.org/10.1002/jrs.5947 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-9438 SN - 1097-4555 VL - 51 IS - 10 SP - 2083 EP - 2094 PB - Wiley CY - Chichester ER - TY - JOUR A1 - Böhm, Klaus A1 - Kubjatko, Tibor A1 - Paula, Daniel A1 - Schweiger, Hans-Georg T1 - New developments on EDR (Event Data Recorder) for automated vehicles JF - Open Engineering N2 - With the upcoming new legislative rules in the EU on Event Data Recorder beginning 2022 the question is whether the discussed data base is sufficient for the needs of clarifying accidents involving automated vehicles. Based on the reconstruction of real accidents including vehicles with ADAS combined with specially designed crash tests a broader data base than US EDR regulation (NHTSA 49 CFR Part 563.7) is proposed. The working group AHEAD, to which the authors contribute, has already elaborated a data model that fits the needs of automated driving. The structure of this data model is shown. Moreover, the special benefits of storing internal video or photo feeds form the vehicle camera systems combined with object data is illustrated. When using a sophisticate 3D measurement method of the accident scene the videos or photos can also serve as a control instance for the stored vehicle data. The AHEAD Data Model enhanced with the storage of the video and photo feeds should be considered in the planned roadmap of the Informal Working Group (IWG) on EDR/ DSSAD (Data Storage System for Automated Driving) reporting to UNECE WP29. Also, a data access over the air using technology already applied in China for electric vehicles called Real Time Monitoring would allow a quantum leap in forensic accident reconstruction. UR - https://doi.org/10.1515/eng-2020-0007 KW - Event Data Recorder (EDR) KW - automated vehicles KW - video and photo feeds KW - Real Time Monitoring (RTM) KW - AHEAD (Aggregated Homologation proposal for Event data recorder for Automated Driving) Y1 - 2020 UR - https://doi.org/10.1515/eng-2020-0007 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-9263 SN - 2391-5439 VL - 10 IS - 1 SP - 140 EP - 146 PB - De Gruyter CY - Berlin ER - TY - JOUR A1 - Steger, Fabian A1 - Nitsche, Alexander A1 - Arbesmeier, Alexander A1 - Brade, Katja A1 - Schweiger, Hans-Georg A1 - Belski, Iouri T1 - Teaching Battery Basics in Laboratories: Hands-On Versus Simulated Experiments JF - IEEE Transactions on Education N2 - Contribution: Prior studies comparing the effectiveness of different laboratory learning modes do not allow one to draw a universally valid conclusion, as other influences are mixed with the learning modes. In order to contribute to the existing body of work and to add another piece to the puzzle, this article demonstrates an improved methodology to evaluate the effectiveness of computer-simulated laboratories in comparison to hands-on exercises using a battery basics practical course as a case study. Background: Computer-simulated experiments are becoming increasingly popular for conducting laboratory exercises in higher education and vocational training institutions. To ensure the consistent quality of laboratory learning, an accurate comparison between the results of simulated experiments and practical hands-on experiments is required. Intended Outcomes: In this article, the achievement of the following learning objectives were compared between the two laboratory modes: 1) comprehension of the most important parameters of battery cells and 2) knowledge on how these parameters can be determined using adequate experimental procedures. Application Design: To avoid interference of factors other than laboratory mode on the learning, laboratory instructions and experimental interfaces ensured identical execution of the experiments in the compared modes. Using a counterbalanced methodology, the two laboratory modes alternated by the session, while the experimental procedures remained constant regardless of the respective modes. Findings: Tests taken by the participants after conducting the laboratory experiments revealed that hands-on laboratories resulted in statistically significantly better student performance than simulated laboratories. This difference was even more pronounced for the participants that finished a vocational education and training program before the university studies. UR - https://doi.org/10.1109/TE.2020.2970554 KW - battery KW - electrical engineering KW - energy storages KW - hands-on KW - knowledge gain KW - laboratory learning KW - simulation KW - student experience Y1 - 2020 UR - https://doi.org/10.1109/TE.2020.2970554 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-9517 SN - 1557-9638 VL - 63 IS - 3 SP - 198 EP - 208 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Geisbauer, Christian A1 - Wöhrl, Katharina A1 - Koch, Daniel A1 - Wilhelm, Gudrun A1 - Schneider, Gerhard A1 - Schweiger, Hans-Georg T1 - Comparative Study on the Calendar Aging Behavior of Six Different Lithium-Ion Cell Chemistries in Terms of Parameter Variation JF - Energies N2 - The degradation of lithium-ion cells is an important aspect, not only for quality management, but also for the customer of the application like, e.g., scooters or electric vehicles. During the lifetime of the system, the overall health on the battery plays a key role in its depreciation. Therefore, it is necessary to monitor the health of the battery during operation, i.e., cycle life, but also during stationary conditions, i.e., calendar aging. In this work, the degradation due to calendar aging is analyzed for six different cell chemistries in terms of capacity degradation and impedance increase and their performance are being compared. In a new proposed metric, the relative deviations between various cells with the exact identical aging history are being analyzed for their degradation effects and their differences, which stands out in comparison to similar research. The capacity loss was found to be most drastic at 60 °C and at higher storage voltages, even for titanate-oxide cells. LiNiMnCoO2 (NMC), LiNiCoAlO2 (NCA) and Li2TiO3 (LTO) cells at 60 °C showed the most drastic capacity decrease. NMC and NCA cells at 60 °C and highest storage voltage did not show any open circuit voltage, as their current interrupt mechanism triggered. The effect of aging shows no uniform impact on the changes in the capacity variance when comparing different aging conditions, with respect to the evaluated standard deviation for all cells. The focus of this work was on the calendar aging effect and may be supplemented in a second study for cyclic aging. UR - https://doi.org/10.3390/en14113358 KW - electromobility KW - batteries KW - lithium-ion KW - calendar aging KW - electric vehicle KW - capacity degradation KW - storage KW - parameter distribution Y1 - 2021 UR - https://doi.org/10.3390/en14113358 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-10091 SN - 1996-1073 VL - 14 IS - 11 PB - MDPI CY - Basel ER - TY - JOUR A1 - Kotak, Yash A1 - Marchante Fernández, Carlos A1 - Canals Casals, Lluc A1 - Kotak, Bhavya A1 - Koch, Daniel A1 - Geisbauer, Christian A1 - Trilla, Lluís A1 - Gómez-Nuñez, Alberto A1 - Schweiger, Hans-Georg T1 - End of Electric Vehicle Batteries BT - Reuse vs. Recycle JF - Energies N2 - It is a fact that electric vehicles (EVs) are beneficial for climate protection. However, the current challenge is to decide on whether to reuse an EV battery or to recycle it after its first use. This paper theoretically investigates these areas i.e., recycle and reuse. It was found that there are several commercially used recycling processes and also some are under research to regain maximum possible materials and quantity. The concept of reusing (second life) of the battery is promising because, at the end of the first life, batteries from EVs can be used in several applications such as storing energy generated from renewable sources to support the government grid. However, the cost and life-cycle analysis (LCA) demonstrated that there are several aspects involved in battery reuse applications. Henceforth, one LCA generalised method cannot provide an optimal approach for all cases. It is important to have a detailed study on each of the battery reusing applications. Until then, it is safe to say that reusing the battery is a good option as it would give some time to recycling companies to develop cost and energy-efficient methods. UR - https://doi.org/10.3390/en14082217 KW - battery recycling KW - battery reuse KW - battery second life KW - circular economy KW - lithium-ion cells KW - electric vehicles KW - battery components recycling KW - sustainability in mobility KW - battery safety KW - battery cost analysis Y1 - 2021 UR - https://doi.org/10.3390/en14082217 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-10115 SN - 1996-1073 VL - 14 IS - 8 PB - MDPI CY - Basel ER - TY - JOUR A1 - Wöhrl, Katharina A1 - Geisbauer, Christian A1 - Nebl, Christoph A1 - Lott, Susanne A1 - Schweiger, Hans-Georg T1 - Crashed Electric Vehicle Handling and Recommendations - State of the Art in Germany JF - Energies N2 - In the near future, electric powered vehicles will represent a major part of the road traffic. Accordingly, there will be a natural increase of accidents involving electric vehicles. There are not many cases of such accidents yet and therefore the experience and correct handling are still partially open points for the involved parties, such as the rescue services for example. The aim of this work is to provide a complete overview of the accident handling sequence in Germany, starting with the damaged vehicle on site and moving on to the risks and challenges for the stakeholders, such as transport and recycling companies. Arising from the developed overview, a handling recommendation for yet undiscussed points is given. Especially, different extinguishing and deactivation methods are compared and discussed. Due to a lack of a common live-feed from battery data on site, other criteria have to be taken into account to assess the state of the battery. The wrecked vehicle—including the high voltage system—needs to be in a definite safe state at the handover to a towing service. Depending on the case, different options for securing the vehicle will be considered in this work. UR - https://doi.org/10.3390/en14041040 KW - electric vehicle KW - battery KW - high voltage KW - accident KW - recommendation KW - energy storage KW - thermal runaway KW - fire extinguishing KW - rescue service KW - handling Y1 - 2021 UR - https://doi.org/10.3390/en14041040 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-10123 SN - 1996-1073 VL - 14 IS - 4 PB - MDPI CY - Basel ER - TY - CHAP A1 - Ritz, Fabian A1 - Ratke, Daniel A1 - Phan, Thomy A1 - Belzner, Lenz A1 - Linnhoff-Popien, Claudia T1 - A sustainable ecosystem through emergent cooperation in multi-agent reinforcement learning T2 - Proceedings of the Artificial Life Conference 2021 UR - https://doi.org/10.1162/isal_a_00399 Y1 - 2021 UR - https://doi.org/10.1162/isal_a_00399 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-12975 VL - 2021 PB - MIT Press CY - Cambridge ER - TY - JOUR A1 - Kleiner, Jan A1 - Stuckenberger, Magdalena A1 - Komsiyska, Lidiya A1 - Endisch, Christian T1 - Advanced monitoring and prediction of the thermal state of intelligent battery cells in electric vehicles by physics-based and data-driven modeling JF - Batteries N2 - Novel intelligent battery systems are gaining importance with functional hardware on the cell level. Cell-level hardware allows for advanced battery state monitoring and thermal management, but also leads to additional thermal interactions. In this work, an electro-thermal framework for the modeling of these novel intelligent battery cells is provided. Thereby, a lumped thermal model, as well as a novel neural network, are implemented in the framework as thermal submodels. For the first time, a direct comparison of a physics-based and a data-driven thermal battery model is performed in the same framework. The models are compared in terms of temperature estimation with regard to accuracy. Both models are very well suited to represent the thermal behavior in novel intelligent battery cells. In terms of accuracy and computation time, however, the data-driven neural network approach with a Nonlinear AutoregRessive network with eXogeneous input (NARX) shows slight advantages. Finally, novel applications of temperature prediction in battery electric vehicles are presented and the applicability of the models is illustrated. Thereby, the conventional prediction of the state of power is extended by simultaneous temperature prediction. Additionally, temperature forecasting is used for pre-conditioning by advanced cooling system regulation to enable energy efficiency and fast charging. UR - https://doi.org/10.3390/batteries7020031 KW - lithium-ion battery KW - electro-thermal model KW - smart cell KW - intelligent battery KW - neural network KW - temperature prediction Y1 - 2021 UR - https://doi.org/10.3390/batteries7020031 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13068 SN - 2313-0105 VL - 7 IS - 2 PB - MDPI CY - Basel ER - TY - JOUR A1 - Theiler, Michael A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Float Current Analysis for Fast Calendar Aging Assessment of 18650 Li(NiCoAl)O2/Graphite Cells JF - Batteries N2 - Float currents are steady-state self-discharge currents after a transient phase—caused by anode overhang, polarization, etc.—is accomplished. The float current is measured in this study with a standard test bench for five 18650 cells (Samsung 25R) at potentiostatic conditions while the temperature is changed in 5 K steps from 5 °C to 60 °C. The entire test is performed in about 100 days resulting in 12 measurement points per cell potential for an Arrhenius representation. The float current follows the Arrhenius law with an activation energy of about 60 kJ/mol. The capacity loss measured at reference condition shows a high correlation to the results of float currents analysis. In contrast to classical calendar aging tests, the performed float current analysis enables determining the aging rate with high precision down to at least 10 °C. Returning from higher temperatures to 30 °C reference temperature shows reducing float currents at 30 °C for increasing temperature steps that may originate from an hysteresis effect that has to be investigated in future publications. UR - https://doi.org/10.3390/batteries7020022 KW - 18650 KW - NCA KW - graphite KW - float current KW - self-discharge KW - calendar aging KW - Arrhenius Y1 - 2021 UR - https://doi.org/10.3390/batteries7020022 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13081 SN - 2313-0105 VL - 7 IS - 2 PB - MDPI CY - Basel ER - TY - JOUR A1 - Mayer, Sebastian A1 - Classen, Tobias A1 - Endisch, Christian T1 - Modular production control using deep reinforcement learning: proximal policy optimization JF - Journal of Intelligent Manufacturing N2 - EU regulations on CO2 limits and the trend of individualization are pushing the automotive industry towards greater flexibility and robustness in production. One approach to address these challenges is modular production, where workstations are decoupled by automated guided vehicles, requiring new control concepts. Modular production control aims at throughput-optimal coordination of products, workstations, and vehicles. For this np-hard problem, conventional control approaches lack in computing efficiency, do not find optimal solutions, or are not generalizable. In contrast, Deep Reinforcement Learning offers powerful and generalizable algorithms, able to deal with varying environments and high complexity. One of these algorithms is Proximal Policy Optimization, which is used in this article to address modular production control. Experiments in several modular production control settings demonstrate stable, reliable, optimal, and generalizable learning behavior. The agent successfully adapts its strategies with respect to the given problem configuration. We explain how to get to this learning behavior, especially focusing on the agent’s action, state, and reward design. UR - https://doi.org/10.1007/s10845-021-01778-z KW - modular production KW - production control KW - production scheduling KW - deep reinforcement learning KW - proximal policy optimization KW - automotive industry Y1 - 2021 UR - https://doi.org/10.1007/s10845-021-01778-z UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13092 SN - 1572-8145 VL - 32 IS - 8 SP - 2335 EP - 2351 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Sequeira, Gerald Joy A1 - Patel, Akshay A1 - Afraj, Shahabaz A1 - Lugner, Robert A1 - Brandmeier, Thomas T1 - FEM-based methodology for crash severity estimation in frontal crash scenarios JF - IOP Conference Series: Materials Science and Engineering N2 - With the technological development of forward-looking sensors, researchers are exploring their use not only for advanced driver assistance systems but also to gain important pre-crash information. Based on this pre-crash information, if the occupant motion inside the vehicle structure can be predicted for the oncoming crash scenario, then an optimal restraint strategy can be planned before the crash. This paper introduces a two-step FEM simulation based methodology for predicting the occupant severity in head-on crash scenarios. In the first step, we simulate the vehicle level model with different impact positions and relative approach angles. The results of these simulations, linear velocities in the longitudinal and lateral direction and angular velocities (roll, pitch, and yaw) during in-crash phase are the loading conditions for next simulation step (occupant level). This step simulates the motion of the driver in different crash scenarios. In this paper, we investigate the head, neck, and chest injury risks from vehicle-to-vehicle crash both traveling at 50 kilometers per hour. Prediction of the head injury criterion, identifying the cases where additional deployment of side-airbags and discussion of injury criteria with contour plots are the main outcome of this paper. UR - https://doi.org/10.1088/1757-899X/831/1/012019 Y1 - 2020 UR - https://doi.org/10.1088/1757-899X/831/1/012019 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13159 SN - 1757-899X SN - 1757-8981 VL - 2020 IS - 831 PB - IOP CY - Bristol ER - TY - JOUR A1 - Schmid, Maximilian A1 - Bhogaraju, Sri Krishna A1 - Liu, E A1 - Elger, Gordon T1 - Comparison of Nondestructive Testing Methods for Solder, Sinter, and Adhesive Interconnects in Power and Opto-Electronics JF - Applied Sciences N2 - Reliability is one of the major requirements for power and opto-electronic devices across all segments. High operation temperature and/or high thermomechanical stress cause defects and degradation of materials and interconnects, which may lead to malfunctions with costly or even life-threatening consequences. To avoid or at least reduce failures, nondestructive testing (NDT) methods are common within development and production of power and opto-electronics. Currently, the dominating NDT methods are X-ray, scanning acoustic microscopy (SAM), and transient thermal analysis (TTA). However, they have different strengths and weaknesses with respect to materials and mechanical designs. This paper compares these NDT methods for different interconnect technologies, i.e., reflow soldering, adhesive, and sintered interconnection. While X-ray provided adequate results for soldered interfaces, inspection of adhesives and sintered interconnects was not possible. With SAM, evaluation of adhesives and sintered interconnects was also feasible, but quality depended strongly on the sample under test. TTA enabled sufficiently detailed results for all the interconnect applications. Automated TTA equipment, as the in-house developed tester used within this investigation, enabled measurement times compatible with SAM and X-ray. In the investigations, all methods revealed their pros and cons, and their selection has to depend on the sample under tests and the required analysis depth and data details. In the paper, guidelines are formulated for an appropriate decision on the NDT method depending on sample and requirements. UR - https://doi.org/10.3390/app10238516 KW - reliability KW - nondestructive testing KW - power electronics KW - X-ray KW - scanning acoustic microscopy KW - transient thermal analysis KW - TTA KW - sintering KW - LED KW - MOSFET Y1 - 2020 UR - https://doi.org/10.3390/app10238516 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-12518 SN - 2076-3417 VL - 10 IS - 23 PB - MDPI CY - Basel ER - TY - INPR A1 - Antônio Rufino Júnior, Carlos A1 - Riva Sanseverino, Eleonora A1 - Gallo, Pierluigi A1 - Amaral, Murilo Machado A1 - Koch, Daniel A1 - Kotak, Yash A1 - Diel, Sergej A1 - Walter, Gero A1 - Schweiger, Hans-Georg A1 - Zanin, Hudson T1 - A Comprehensive Review of EV Lithium-Ion Battery Degradation N2 - Lithium-ion batteries with improved energy densities have made understanding the Solid Electrolyte Interphase (SEI) generation mechanisms that cause mechanical, thermal, and chemical failures more complicated. SEI processes reduce battery capacity and power. Thus, a review of this area's understanding is important. It is essential to know how batteries degrade in EVs to estimate battery lifespan as it goes, predict, and minimize losses, and determine the ideal time for a replacement. Lithium-ion batteries used in EVs mainly suffer two types of degradation: calendar degradation and cycling degradation. Despite the existence of several existing works in the literature, several aspects of battery degradation remain unclear or have not been analyzed in detail. This work presents a systematic review of existing works in the literature. The results of the present investigation provide insight into the complex relationships among various factors affecting battery degradation mechanisms. Specifically, this systematic review examined the effects of time, side reactions, temperature fluctuations, high charge/discharge rates, depth of discharge, mechanical stress, thermal stress, and the voltage relationship on battery performance and longevity. The results revealed that these factors interact in complex ways to influence the degradation mechanisms of batteries. For example, high charge currents and deep discharges were found to accelerate degradation, while low temperatures and moderate discharge depths were shown to be beneficial for battery longevity. Additionally, the results showed that the relationship between cell voltage and State-of-Charge (SOC) plays a critical role in determining the rate of degradation. Overall, these findings have important implications for the design and operation of battery systems, as they highlight the need to carefully manage a range of factors to maximize battery performance and longevity. The result is an analysis of the main articles published in this field in recent years. This work aims to present new knowledge about fault detection, diagnosis, and management of lithium-ion batteries based on battery degradation concepts. The new knowledge is presented and discussed in a structured and comprehensive way. UR - https://doi.org/10.20944/preprints202306.0228.v2 Y1 - 2023 UR - https://doi.org/10.20944/preprints202306.0228.v2 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58428 PB - Preprints CY - Basel ER - TY - INPR A1 - Song, Rui A1 - Liu, Dai A1 - Chen, Dave Zhenyu A1 - Festag, Andreas A1 - Trinitis, Carsten A1 - Schulz, Martin A1 - Knoll, Alois T1 - Federated Learning via Decentralized Dataset Distillation in Resource Constrained Edge Environments N2 - In federated learning, all networked clients contribute to the model training cooperatively. However, with model sizes increasing, even sharing the trained partial models often leads to severe communication bottlenecks in underlying networks, especially when communicated iteratively. In this paper, we introduce a federated learning framework FedD3 requiring only one-shot communication by integrating dataset distillation instances. Instead of sharing model updates in other federated learning approaches, FedD3 allows the connected clients to distill the local datasets independently, and then aggregates those decentralized distilled datasets (e.g. a few unrecognizable images) from networks for model training. Our experimental results show that FedD3 significantly outperforms other federated learning frameworks in terms of needed communication volumes, while it provides the additional benefit to be able to balance the trade-off between accuracy and communication cost, depending on usage scenario or target dataset. For instance, for training an AlexNet model on CIFAR-10 with 10 clients under non-independent and identically distributed (Non-IID) setting, FedD3 can either increase the accuracy by over 71% with a similar communication volume, or save 98% of communication volume, while reaching the same accuracy, compared to other one-shot federated learning approaches. UR - https://doi.org/10.48550/arXiv.2208.11311 Y1 - 2022 UR - https://doi.org/10.48550/arXiv.2208.11311 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60054 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Novicki Neto, Leonardo A1 - Reway, Fabio A1 - Poledna, Yuri A1 - Funk Drechsler, Maikol A1 - Parente Ribeiro, Eduardo A1 - Huber, Werner A1 - Icking, Christian T1 - TWICE Dataset: Digital Twin of Test Scenarios in a Controlled Environment N2 - Ensuring the safe and reliable operation of autonomous vehicles under adverse weather remains a significant challenge. To address this, we have developed a comprehensive dataset composed of sensor data acquired in a real test track and reproduced in the laboratory for the same test scenarios. The provided dataset includes camera, radar, LiDAR, inertial measurement unit (IMU), and GPS data recorded under adverse weather conditions (rainy, night-time, and snowy conditions). We recorded test scenarios using objects of interest such as car, cyclist, truck and pedestrian -- some of which are inspired by EURONCAP (European New Car Assessment Programme). The sensor data generated in the laboratory is acquired by the execution of simulation-based tests in hardware-in-the-loop environment with the digital twin of each real test scenario. The dataset contains more than 2 hours of recording, which totals more than 280GB of data. Therefore, it is a valuable resource for researchers in the field of autonomous vehicles to test and improve their algorithms in adverse weather conditions, as well as explore the simulation-to-reality gap. UR - https://doi.org/10.48550/arXiv.2310.03895 Y1 - 2023 UR - https://doi.org/10.48550/arXiv.2310.03895 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59887 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Fidelis, Eduardo A1 - Reway, Fabio A1 - Ribeiro, Herick Y. S. A1 - Campos, Pietro A1 - Huber, Werner A1 - Icking, Christian A1 - Faria, Lester A1 - Schön, Torsten T1 - Generation of Realistic Synthetic Raw Radar Data for Automated Driving Applications using Generative Adversarial Networks N2 - The main approaches for simulating FMCW radar are based on ray tracing, which is usually computationally intensive and do not account for background noise. This work proposes a faster method for FMCW radar simulation capable of generating synthetic raw radar data using generative adversarial networks (GAN). The code and pre-trained weights are open-source and available on GitHub. This method generates 16 simultaneous chirps, which allows the generated data to be used for the further development of algorithms for processing radar data (filtering and clustering). This can increase the potential for data augmentation, e.g., by generating data in non-existent or safety-critical scenarios that are not reproducible in real life. In this work, the GAN was trained with radar measurements of a motorcycle and used to generate synthetic raw radar data of a motorcycle traveling in a straight line. For generating this data, the distance of the motorcycle and Gaussian noise are used as input to the neural network. The synthetic generated radar chirps were evaluated using the Frechet Inception Distance (FID). Then, the Range-Azimuth (RA) map is calculated twice: first, based on synthetic data using this GAN and, second, based on real data. Based on these RA maps, an algorithm with adaptive threshold and edge detection is used for object detection. The results have shown that the data is realistic in terms of coherent radar reflections of the motorcycle and background noise based on the comparison of chirps, the RA maps and the object detection results. Thus, the proposed method in this work has shown to minimize the simulation-to-reality gap for the generation of radar data. UR - https://doi.org/10.48550/arXiv.2308.02632 Y1 - 2023 UR - https://doi.org/10.48550/arXiv.2308.02632 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59872 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Han, Longfei A1 - Kefferpütz, Klaus A1 - Beyerer, Jürgen T1 - Decentralized Fusion of 3D Extended Object Tracking based on a B-Spline Shape Model N2 - Extended Object Tracking (EOT) exploits the high resolution of modern sensors for detailed environmental perception. Combined with decentralized fusion, it contributes to a more scalable and robust perception system. This paper investigates the decentralized fusion of 3D EOT using a B-spline curve based model. The spline curve is used to represent the side-view profile, which is then extruded with a width to form a 3D shape. We use covariance intersection (CI) for the decentralized fusion and discuss the challenge of applying it to EOT. We further evaluate the tracking result of the decentralized fusion with simulated and real datasets of traffic scenarios. We show that the CI-based fusion can significantly improve the tracking performance for sensors with unfavorable perspective. UR - https://doi.org/10.48550/arXiv.2504.18708 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2504.18708 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59648 PB - arXiv CY - Ithaca ER - TY - JOUR A1 - Morales Torricos, Pablo A1 - Berg, Sascha A1 - Figgemeier, Egbert A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - The important role of lithiation-induced pressure change on apparent aging of lithium-ion batteries during accelerated cyclic aging tests JF - Journal of Energy Storage N2 - In assessing the lifespan of lithium-ion batteries in laboratory conditions, the measured capacity declines during accelerated cyclic aging tests but increases when the cells are left idle. This recoverable capacity loss, known in literature as apparent aging, results from an inhomogeneous lithium distribution in the anode appearing in dV/dQ and capacity difference analysis. This study explores the origin of the apparent aging by correlating lithium distribution in the anode and recoverable capacity loss, with the lithiation induced pressure change and generated electrolyte motion during cycling. To this end, we compressed five commercial pouch lithium-ion cells (NMC/Gr) with holder stiffnesses ranging from 0.9 to 15.4 MPa/mm and offset pressure from 289 to 681 kPa and subjected them to continuous cyclic aging tests. While offset pressure had no significant impact, we observed, that holder stiffnesses over 3.3 MPa/mm induces an apparent capacity loss, which is recoverable by 35 % during a resting phase. The root cause is the so-called electrolyte motion induced salt inhomogeneity (EMSI), driven by continuous high current cycling and electrolyte motion, which is intensified by higher holder stiffness but not by offset pressure. These insights are crucial for improving the accuracy of accelerated aging tests and enhancing battery lifespan predictions. UR - https://doi.org/10.1016/j.est.2025.117323 Y1 - 2025 UR - https://doi.org/10.1016/j.est.2025.117323 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60173 SN - 2352-1538 VL - 2025 IS - 131, Part A PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Fadl, Islam A1 - Schön, Torsten A1 - Behret, Valentino A1 - Brandmeier, Thomas A1 - Palme, Frank A1 - Helmer, Thomas ED - Bashford-Rogers, Thomas ED - Meneveaux, Daniel ED - Ammi, Mehdi ED - Ziat, Mounia ED - Jänicke, Stefan ED - Purchase, Helen ED - Radeva, Petia ED - Furnari, Antonino ED - Bouatouch, Kadi ED - Sousa, A. Augusto T1 - Environment Setup and Model Benchmark of the MuFoRa Dataset T2 - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - (Volume 3) N2 - Adverse meteorological conditions, particularly fog and rain, present significant challenges to computer vision algorithms and autonomous systems. This work presents MuFoRa a novel, controllable, and measured multimodal dataset recorded at CARISSMA’s indoor test facility, specifically designed to assess perceptual difficulties in foggy and rainy environments. The dataset bridges research gap in the public benchmarking datasets, where quantifiable weather parameters are lacking. The proposed dataset comprises synchronized data from two sensor modalities: RGB stereo cameras and LiDAR sensors, captured under varying intensities of fog and rain. The dataset incorporates synchronized meteorological annotations, such as visibility through fog and precipitation levels of rain, and the study contributes a detailed explanation of the diverse weather effects observed during data collection in the methods section. The dataset’s utility is demonstrated through a baseline evaluation example, asse ssing the performance degradation of state-of-the-art YOLO11 and DETR 2D object detection algorithms under controlled and quantifiable adverse weather conditions. The public release of the dataset (https://doi.org/10.5281/zenodo.14175611) facilitates various benchmarking and quantitative assessments of advanced multimodal computer vision and deep learning models under the challenging conditions of fog and rain. UR - https://doi.org/10.5220/0013307900003912 Y1 - 2025 UR - https://doi.org/10.5220/0013307900003912 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58070 SN - 978-989-758-728-3 SP - 729 EP - 737 PB - SciTePress CY - Setúbal ER - TY - INPR A1 - Song, Rui A1 - Liang, Chenwei A1 - Xia, Yan A1 - Zimmer, Walter A1 - Cao, Hu A1 - Caesar, Holger A1 - Festag, Andreas A1 - Knoll, Alois T1 - CoDa-4DGS: Dynamic Gaussian Splatting with Context and Deformation Awareness for Autonomous Driving N2 - Dynamic scene rendering opens new avenues in autonomous driving by enabling closed-loop simulations with photorealistic data, which is crucial for validating end-to-end algorithms. However, the complex and highly dynamic nature of traffic environments presents significant challenges in accurately rendering these scenes. In this paper, we introduce a novel 4D Gaussian Splatting (4DGS) approach, which incorporates context and temporal deformation awareness to improve dynamic scene rendering. Specifically, we employ a 2D semantic segmentation foundation model to self-supervise the 4D semantic features of Gaussians, ensuring meaningful contextual embedding. Simultaneously, we track the temporal deformation of each Gaussian across adjacent frames. By aggregating and encoding both semantic and temporal deformation features, each Gaussian is equipped with cues for potential deformation compensation within 3D space, facilitating a more precise representation of dynamic scenes. Experimental results show that our method improves 4DGS's ability to capture fine details in dynamic scene rendering for autonomous driving and outperforms other self-supervised methods in 4D reconstruction and novel view synthesis. Furthermore, CoDa-4DGS deforms semantic features with each Gaussian, enabling broader applications. UR - https://doi.org/10.48550/arXiv.2503.06744 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2503.06744 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58313 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Kalyanasundaram, Abinav A1 - Chandra Sekaran, Karthikeyan A1 - Stäuber, Philipp A1 - Lange, Michael A1 - Utschick, Wolfgang A1 - Botsch, Michael T1 - Uncertainty-Aware Hybrid Machine Learning in Virtual Sensors for Vehicle Sideslip Angle Estimation N2 - Precise vehicle state estimation is crucial for safe and reliable autonomous driving. The number of measurable states and their precision offered by the onboard vehicle sensor system are often constrained by cost. For instance, measuring critical quantities such as the Vehicle Sideslip Angle (VSA) poses significant commercial challenges using current optical sensors. This paper addresses these limitations by focusing on the development of high-performance virtual sensors to enhance vehicle state estimation for active safety. The proposed Uncertainty-Aware Hybrid Learning (UAHL) architecture integrates a machine learning model with vehicle motion models to estimate VSA directly from onboard sensor data. A key aspect of the UAHL architecture is its focus on uncertainty quantification for individual model estimates and hybrid fusion. These mechanisms enable the dynamic weighting of uncertainty-aware predictions from machine learning and vehicle motion models to produce accurate and reliable hybrid VSA estimates. This work also presents a novel dataset named Real-world Vehicle State Estimation Dataset (ReV-StED), comprising synchronized measurements from advanced vehicle dynamic sensors. The experimental results demonstrate the superior performance of the proposed method for VSA estimation, highlighting UAHL as a promising architecture for advancing virtual sensors and enhancing active safety in autonomous vehicles. UR - https://doi.org/10.48550/arXiv.2504.06105 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2504.06105 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59578 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Han, Longfei A1 - Xu, Qiuyu A1 - Kefferpütz, Klaus A1 - Elger, Gordon A1 - Beyerer, Jürgen T1 - Applying Extended Object Tracking for Self-Localization of Roadside Radar Sensors N2 - Intelligent Transportation Systems (ITS) can benefit from roadside 4D mmWave radar sensors for large-scale traffic monitoring due to their weatherproof functionality, long sensing range and low manufacturing cost. However, the localization method using external measurement devices has limitations in urban environments. Furthermore, if the sensor mount exhibits changes due to environmental influences, they cannot be corrected when the measurement is performed only during the installation. In this paper, we propose self-localization of roadside radar data using Extended Object Tracking (EOT). The method analyses both the tracked trajectories of the vehicles observed by the sensor and the aerial laser scan of city streets, assigns labels of driving behaviors such as "straight ahead", "left turn", "right turn" to trajectory sections and road segments, and performs Semantic Iterative Closest Points (SICP) algorithm to register the point cloud. The method exploits the result from a down stream task -- object tracking -- for localization. We demonstrate high accuracy in the sub-meter range along with very low orientation error. The method also shows good data efficiency. The evaluation is done in both simulation and real-world tests. UR - https://doi.org/10.48550/arXiv.2407.03084 Y1 - 2024 UR - https://doi.org/10.48550/arXiv.2407.03084 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58361 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Han, Longfei A1 - Kefferpütz, Klaus A1 - Beyerer, Jürgen T1 - 3D Extended Object Tracking based on Extruded B-Spline Side View Profiles N2 - Object tracking is an essential task for autonomous systems. With the advancement of 3D sensors, these systems can better perceive their surroundings using effective 3D Extended Object Tracking (EOT) methods. Based on the observation that common road users are symmetrical on the right and left sides in the traveling direction, we focus on the side view profile of the object. In order to leverage of the development in 2D EOT and balance the number of parameters of a shape model in the tracking algorithms, we propose a method for 3D extended object tracking (EOT) by describing the side view profile of the object with B-spline curves and forming an extrusion to obtain a 3D extent. The use of B-spline curves exploits their flexible representation power by allowing the control points to move freely. The algorithm is developed into an Extended Kalman Filter (EKF). For a through evaluation of this method, we use simulated traffic scenario of different vehicle models and realworld open dataset containing both radar and lidar data. UR - https://doi.org/10.48550/arXiv.2503.10730 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2503.10730 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58331 PB - arXiv CY - Ithaca ER - TY - JOUR A1 - Yu, Qing A1 - Kiran, Iqra A1 - Ehrensberger, Moritz A1 - Streck, Luiza A1 - Roth, Thomas A1 - Jossen, Andreas A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Assigning Calendar Aging during Open Circuit and Float Current Analysis to Anode and Cathode Aging Using Three-Electrode Cells JF - Journal of the Electrochemical Society N2 - Analyzing calendar aging by float current analysis, instead of solely repeating capacity tests, gains more insights into aging. However, the underlying mechanisms of the recharge current required to keep the voltage constant are not yet fully understood. Therefore, this study performs float current and additional open circuit voltage (OCV) tests on 3-electrode cells for four different voltages at 30 °C. By monitoring the potentials of the anode and the cathode over time individually, the aging rate on both electrodes and the present capacity can be calculated based on adjusting the electrode-specific OCV curves according to the voltage slippery theory. The electrode-specific aging and the capacity prediction show high agreement among both methods and the capacity tests at the end of the experiment. As a result, the capacity loss appears linear-like and is associated with the loss of active lithium mainly due to SEI formation on the anode. Additionally, a significant cathode voltage decay is observed especially for higher cell voltage. According to the literature, this is associated with cathode lithiation where the conductive salt is decomposed by inserting active lithium into the cathode masking SEI losses. Finally, OCV and float current analysis return comparable results and support present 2-electrode evaluation approaches. UR - https://doi.org/10.1149/1945-7111/ade295 Y1 - 2025 UR - https://doi.org/10.1149/1945-7111/ade295 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60504 SN - 1945-7111 VL - 172 IS - 6 PB - IOP Publishing CY - Bristol ER - TY - CHAP A1 - Karpenahalli Ramakrishna, Chidvilas A1 - Mohan, Adithya A1 - Zeinaly, Zahra A1 - Belzner, Lenz ED - Rocha, Ana Paula ED - Steels, Luc ED - van den Herik, Jaap T1 - The Evolution of Criticality in Deep Reinforcement Learning T2 - Proceedings of the 17th International Conference on Agents and Artificial Intelligence (ICAART 2025) - Volume 3 N2 - In Reinforcement Learning (RL), certain states demand special attention due to their significant influence on outcomes; these are identified as critical states. The concept of criticality is essential for the development of effective and robust policies and to improve overall trust in RL agents in real-world applications like autonomous driving. The current paper takes a deep dive into criticality and studies the evolution of criticality throughout training. The experiments are conducted on a new, simple yet intuitive continuous cliff maze environment and the Highway-env autonomous driving environment. Here, a novel finding is reported that criticality is not only learnt by the agent but can also be unlearned. We hypothesize that diversity in experiences is necessary for effective criticality quantification which is majorly driven by the chosen exploration strategy. This close relationship between exploration and criticality is studied utilizing two different strategies namely the ex ponential ε-decay and the adaptive ε-decay. The study supports the idea that effective exploration plays a crucial role in accurately identifying and understanding critical states. UR - https://doi.org/10.5220/0013114200003890 Y1 - 2025 UR - https://doi.org/10.5220/0013114200003890 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-57992 SN - 978-989-758-737-5 SP - 217 EP - 224 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Wildgrube, Fabian A1 - Ehrett, Pete A1 - Trojahn, Paul A1 - Membarth, Richard A1 - Beckmann, Bradford A1 - Baumeister, Dominik A1 - Chajdas, Matthäus T1 - GPUs All Grown-Up: Fully Device-Driven SpMV Using GPU Work Graphs T2 - ISCA ´25: Proceedings of the 52nd Annual International Symposium on Computer Architecture N2 - Sparse matrix-vector multiplication (SpMV) is a key operation across high-performance computing, graph analytics, and many more applications. In these applications, the matrix characteristics, notably non-zero elements per row, can vary widely and impact which algorithm performs best. Thus, Graphics Processing Unit (GPU) SpMV algorithms often rely on costly preprocessing to determine what per-row algorithm to select to achieve high performance. In this work we combine SpMV preprocessing and the subsequent per-row processing on the GPU by leveraging the novel “Work Graphs” GPU programming model—initially designed for graphics applications—for dynamic on-device self-scheduling. Work Graphs allow for fine-grain dataflow execution of individual workgroups using emerging hardware and firmware support. As soon as preprocessing has generated sufficient work, workgroups of individual processing kernels are self-scheduled and executed, interleaved with those of other kernels. This improves cache locality and eliminates host interaction altogether. Across a suite of 59 sparse matrices, the best of various novel Work Graphs SpMV implementations outperforms state-of-the-art rocSPARSE “LRB” for a single SpMV by up to 7.19 × (mean: 3.35 ×, SD: 1.89). Furthermore, it achieves much more stable performance across various sparsity patterns than the rocSPARSE CSR-General algorithm, and even beats the advanced rocSPARSE CSR-Adaptive algorithm for up to 92 consecutive SpMV calculations. In addition, compared to rocSPARSE LRB, it reduces code complexity by 75%. Its memory footprint for supporting data structures is a fixed ∼ 25 MiB independent of matrix size, compared to rocSPARSE LRB’s data structures that scale with matrix size to hundreds of megabytes. Overall, this work showcases the performance potential of emerging dynamic on-device scheduling techniques for GPU compute applications. UR - https://doi.org/10.1145/3695053.3731060 Y1 - 2025 UR - https://doi.org/10.1145/3695053.3731060 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58868 SN - 979-8-4007-1261-6 SP - 1777 EP - 1791 PB - ACM CY - New York ER - TY - INPR A1 - Paula, Daniel A1 - Bauder, Maximilian A1 - Pfeilschifter, Claus A1 - Petermeier, Franziska A1 - Kubjatko, Tibor A1 - Böhm, Klaus A1 - Riener, Andreas A1 - Schweiger, Hans-Georg T1 - Impact of Partially Automated Driving Functions on Forensic Accident Reconstruction: A Simulator Study on Driver Reaction Behavior in the Event of a Malfunctioning System Behavior N2 - Partially automated driving functions (SAE Level 2) can control a vehicle's longitudinal and lateral movements. However, taking over the driving task involves automation risks that the driver must manage. In severe accidents, the driver's ability to avoid a collision must be assessed, considering their expected reaction behavior. The primary goal of this study is to generate essential data on driver reaction behavior in case of malfunctions in partially automated driving functions for use in legal affairs. A simulator study with two scenarios involving 32 subjects was conducted for this purpose. The first scenario investigated driver reactions to system limitations during cornering. The second scenario examined driver responses to phantom braking caused by the AEBS. As a result, the first scenario shows that none of the subjects could control the situation safely. Due to partial automation, we could also identify a new part of the reaction time, the hands-on time, which leads to increased steering reaction times of 1.18 to 1.74 seconds. In the second scenario, we found that 25 of the 32 subjects could not override the phantom braking by pressing the accelerator pedal, although 16 subjects were informed about the system analog to the actual vehicle manuals. Overall, the study suggests that the current legal perspective on vehicle control and the expected driver reaction behavior for accident avoidance should be reconsidered. UR - https://doi.org/10.20944/preprints202311.0947.v1 Y1 - 2023 UR - https://doi.org/10.20944/preprints202311.0947.v1 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-42173 PB - Preprints CY - Basel ER - TY - CHAP A1 - Devillers, Hugo A1 - Kurtenacker, Matthias A1 - Membarth, Richard A1 - Lemme, Stefan A1 - Kenzel, Michael A1 - Yazici, Ömercan A1 - Slusallek, Philipp ED - Knoll, Aaron ED - Peters, Christoph T1 - No More Shading Languages: Compiling C++ to Vulkan Shaders T2 - High-Performance Graphics - Symposium Papers N2 - Graphics APIs have traditionally relied on shading languages, however, these languages have a number of fundamental defects and limitations. By contrast, GPU compute platforms offer powerful, feature-rich languages suitable for heterogeneous compute. We propose reframing shading languages as embedded domain-specific languages, layered on top of a more general language like C++, doing away with traditional limitations on pointers, functions, and recursion, to the benefit of programmability. This represents a significant compilation challenge because the limitations of shaders are reflected in their lower-level representations. We present the Vcc compiler, which allows conventional C and C++ code to run as Vulkan shaders. Our compiler is complemented by a simple shading library and exposes GPU particulars as intrinsics and annotations. We evaluate the performance of our compiler using a selection of benchmarks, including a real-time path tracer, achieving competitive performance compared to their native CUDA counterparts. UR - https://doi.org/10.2312/hpg.20251167 Y1 - 2025 UR - https://doi.org/10.2312/hpg.20251167 UR - https://diglib.eg.org/handle/10.2312/hpg20251167 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60151 SN - 978-3-03868-291-2 PB - The Eurographics Association CY - Goslar ER - TY - INPR A1 - Endt, Sebastian A1 - Engel, Maria A1 - Naldi, Emanuele A1 - Assereto, Rodolfo A1 - Molendowska, Malwina A1 - Mueller, Lars A1 - Verdun, Claudio Mayrink A1 - Pirkl, Carolin A1 - Palombo, Marco A1 - Jones, Derek K. A1 - Menzel, Marion Irene T1 - In-vivo myelin water quantification using diffusion-relaxation correlation MRI: a comparison of 1D and 2D methods T2 - Research Square N2 - Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion-recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. While 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion. UR - https://doi.org/10.21203/rs.3.rs-3069146/v1 Y1 - 2023 UR - https://doi.org/10.21203/rs.3.rs-3069146/v1 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-46448 SN - 2693-5015 PB - Research Square CY - Durham ER - TY - JOUR A1 - Endt, Sebastian A1 - Engel, Maria A1 - Naldi, Emanuele A1 - Assereto, Rodolfo A1 - Molendowska, Malwina A1 - Mueller, Lars A1 - Verdun, Claudio Mayrink A1 - Pirkl, Carolin A1 - Palombo, Marco A1 - Jones, Derek K. A1 - Menzel, Marion Irene T1 - In Vivo Myelin Water Quantification Using Diffusion–Relaxation Correlation MRI: A Comparison of 1D and 2D Methods JF - Applied Magnetic Resonance N2 - Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion–relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion. UR - https://doi.org/10.1007/s00723-023-01584-1 KW - MWF mapping KW - Microstructure KW - Relaxometry KW - Diffusometry KW - Multi-component KW - Multidimensional KW - Multi-exponential KW - Multiparametric KW - Correlation imaging Y1 - 2023 UR - https://doi.org/10.1007/s00723-023-01584-1 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-40317 SN - 0937-9347 SN - 1613-7507 VL - 54 IS - 11-12 SP - 1571 EP - 1588 PB - Springer CY - Wien ER - TY - CHAP A1 - Agrawal, Shiva A1 - Bhanderi, Savankumar A1 - Amanagi, Sumit A1 - Doycheva, Kristina A1 - Elger, Gordon ED - Vinel, Alexey ED - Ploeg, Jeroen ED - Berns, Karsten ED - Gusikhin, Oleg T1 - Instance Segmentation and Detection of Children to Safeguard Vulnerable Traffic User by Infrastructure T2 - Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems N2 - Cameras mounted on intelligent roadside infrastructure units and vehicles can detect humans on the road using state-of-the-art perception algorithms, but these algorithms are presently not trained to distinguish between human and adult. However, this is a crucial requirement from a safety perspective because a child may not follow all the traffic rules, particularly while crossing the road. Moreover, a child may stop or may start playing on the road. In such situations, the separation of a child from an adult is necessary. The work in this paper targets to solve this problem by applying a transfer-learning-based neural network approach to classify child and adult separately in camera images. The described work is comprised of image data collection, data annotation, transfer learning-based model development, and evaluation. For the work, Mask-RCNN (region-based convolutional neural network) with different backbone architectures and two different baselines are investigated and the perception precision of the architectures after transfer-learning is compared. The results reveal that the best performing trained model is able to detect and classify children and adults separately in different road scenarios with segmentation mask AP (average precision) of 85% and bounding box AP of 92%. UR - https://doi.org/10.5220/0011825400003479 KW - Child and Adult Detection KW - Classification KW - Intelligent Roadside Infrastructure KW - Image Segmentation KW - Mask-RCNN KW - Traffic Flow Optimization KW - Transfer Learning Y1 - 2023 UR - https://doi.org/10.5220/0011825400003479 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-41785 SN - 978-989-758-652-1 SN - 2184-495X SP - 206 EP - 214 PB - SciTePress CY - Setúbal ER - TY - JOUR A1 - Agrawal, Shiva A1 - Bhanderi, Savankumar A1 - Elger, Gordon T1 - Infra-3DRC-FusionNet: Deep Fusion of Roadside Mounted RGB Mono Camera and Three-Dimensional Automotive Radar for Traffic User Detection JF - Sensors N2 - Mono RGB cameras and automotive radar sensors provide a complementary information set that makes them excellent candidates for sensor data fusion to obtain robust traffic user detection. This has been widely used in the vehicle domain and recently introduced in roadside-mounted smart infrastructure-based road user detection. However, the performance of the most commonly used late fusion methods often degrades when the camera fails to detect road users in adverse environmental conditions. The solution is to fuse the data using deep neural networks at the early stage of the fusion pipeline to use the complete data provided by both sensors. Research has been carried out in this area, but is limited to vehicle-based sensor setups. Hence, this work proposes a novel deep neural network to jointly fuse RGB mono-camera images and 3D automotive radar point cloud data to obtain enhanced traffic user detection for the roadside-mounted smart infrastructure setup. Projected radar points are first used to generate anchors in image regions with a high likelihood of road users, including areas not visible to the camera. These anchors guide the prediction of 2D bounding boxes, object categories, and confidence scores. Valid detections are then used to segment radar points by instance, and the results are post-processed to produce final road user detections in the ground plane. The trained model is evaluated for different light and weather conditions using ground truth data from a lidar sensor. It provides a precision of 92%, recall of 78%, and F1-score of 85%. The proposed deep fusion methodology has 33%, 6%, and 21% absolute improvement in precision, recall, and F1-score, respectively, compared to object-level spatial fusion output. UR - https://doi.org/10.3390/s25113422 Y1 - 2025 UR - https://doi.org/10.3390/s25113422 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59421 SN - 1424-8220 VL - 25 IS - 11 PB - MDPI CY - Basel ER - TY - JOUR A1 - Flores Fernández, Alberto A1 - Sánchez Morales, Eduardo A1 - Botsch, Michael A1 - Facchi, Christian A1 - García Higuera, Andrés T1 - Generation of Correction Data for Autonomous Driving by Means of Machine Learning and On-Board Diagnostics JF - Sensors N2 - A highly accurate reference vehicle state is a requisite for the evaluation and validation of Autonomous Driving (AD) and Advanced Driver Assistance Systems (ADASs). This highly accurate vehicle state is usually obtained by means of Inertial Navigation Systems (INSs) that obtain position, velocity, and Course Over Ground (COG) correction data from Satellite Navigation (SatNav). However, SatNav is not always available, as is the case of roofed places, such as parking structures, tunnels, or urban canyons. This leads to a degradation over time of the estimated vehicle state. In the present paper, a methodology is proposed that consists on the use of a Machine Learning (ML)-method (Transformer Neural Network—TNN) with the objective of generating highly accurate velocity correction data from On-Board Diagnostics (OBD) data. The TNN obtains OBD data as input and measurements from state-of-the-art reference sensors as a learning target. The results show that the TNN is able to infer the velocity over ground with a Mean Absolute Error (MAE) of 0.167 kmh (0.046 ms) when a database of 3,428,099 OBD measurements is considered. The accuracy decreases to 0.863 kmh (0.24 ms) when only 5000 OBD measurements are used. Given that the obtained accuracy closely resembles that of state-of-the-art reference sensors, it allows INSs to be provided with accurate velocity correction data. An inference time of less than 40 ms for the generation of new correction data is achieved, which suggests the possibility of online implementation. This supports a highly accurate estimation of the vehicle state for the evaluation and validation of AD and ADAS, even in SatNav-deprived environments. UR - https://doi.org/10.3390/s23010159 KW - On-Board Diagnostics KW - Machine Learning KW - Transformer Neural Network KW - Autonomous Driving KW - ADAS KW - Inertial Navigation Systems Y1 - 2022 UR - https://doi.org/10.3390/s23010159 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-30464 SN - 1424-8220 VL - 23 IS - 1 PB - MDPI CY - Basel ER - TY - JOUR A1 - Da Rosa Zanatta, Mateus A1 - Carvalho Lustosa da Costa, Joao Paulo A1 - Antreich, Felix A1 - Haardt, Martin A1 - Elger, Gordon A1 - Lopes de Mendonça, Fábio Lúcio A1 - de Sousa Junior, Rafael Timóteo T1 - Tensor-based framework with model order selection and high accuracy factor decomposition for time-delay estimation in dynamic multipath scenarios JF - IEEE Access N2 - Global Navigation Satellite Systems (GNSS) are crucial for applications that demand very accurate positioning. Tensor-based time-delay estimation methods, such as CPD-GEVD, DoA/KRF, and SECSI, combined with the GPS3 L1C signal, are capable of, significantly, mitigating the positioning degradation caused by multipath components. However, even though these schemes require an estimated model order, they assume that the number of multipath components is constant. In GNSS applications, the number of multipath components is time-varying in dynamic scenarios. Thus, in this paper, we propose a tensor-based framework with model order selection and high accuracy factor decomposition for time-delay estimation in dynamic multipath scenarios. Our proposed approach exploits the estimates of the model order for each slice by grouping the data tensor slices into sub-tensors to provide high accuracy factor decomposition. We further enhance the proposed approach by incorporating the tensor-based Multiple Denoising (MuDe). UR - https://doi.org/10.1109/ACCESS.2020.3024597 KW - Global navigation satellite systems (GNSS) KW - global positioning system (GPS) KW - GPS3 KW - time-delay estimation (TDE) KW - multipath components KW - model order selection (MOS) Y1 - 2020 UR - https://doi.org/10.1109/ACCESS.2020.3024597 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-9528 SN - 2169-3536 VL - 8 SP - 174931 EP - 174942 PB - IEEE CY - New York ER - TY - JOUR A1 - Delooz, Quentin A1 - Willecke, Alexander A1 - Garlichs, Keno A1 - Hagau, Andreas-Christian A1 - Wolf, Lars A1 - Vinel, Alexey A1 - Festag, Andreas T1 - Analysis and Evaluation of Information Redundancy Mitigation for V2X Collective Perception JF - IEEE Access N2 - Sensor data sharing enables vehicles to exchange locally perceived sensor data among each other and with the roadside infrastructure to increase their environmental awareness. It is commonly regarded as a next-generation vehicular communication service beyond the exchange of highly aggregated messages in the first generation. The approach is being considered in the European standardization process, where it relies on the exchange of locally detected objects representing anything safety-relevant, such as other vehicles or pedestrians, in periodically broadcasted messages to vehicles in direct communication range. Objects filtering methods for inclusion in a message are necessary to avoid overloading a channel and provoking unnecessary data processing. Initial studies provided in a pre-standardization report about sensor data sharing elaborated a first set of rules to filter objects based on their characteristics, such as their dynamics or type. However, these rules still lack the consideration of information received by other stations to operate. Specifically, to address the problem of information redundancy, several rules have been proposed, but their performance has not been evaluated yet comprehensively. In the present work, the rules are further analyzed, assessed, and compared. Functional and operational requirements are investigated. A performance evaluation is realized by discrete-event simulations in a scenario for a representative city with realistic vehicle densities and mobility patterns. A score and other redundancy-level metrics are elaborated to ease the evaluation and comparison of the filtering rules. Finally, improvements and future works to the filtering methods are proposed. UR - https://doi.org/10.1109/ACCESS.2022.3170029 KW - Collective perception KW - information redundancy mitigation KW - road safety KW - sensor data sharing KW - V2X communications Y1 - 2022 UR - https://doi.org/10.1109/ACCESS.2022.3170029 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-28662 SN - 2169-3536 VL - 10 SP - 47076 EP - 47093 PB - IEEE CY - New York ER - TY - JOUR A1 - Funk Drechsler, Maikol A1 - Sharma, Varun A1 - Reway, Fabio A1 - Schütz, Christoph A1 - Huber, Werner T1 - Dynamic Vehicle-in-the-Loop: A Novel Method for Testing Automated Driving Functions JF - SAE International Journal of Connected and Automated Vehicles N2 - In automated driving functions (ADF) testing, novel methods have been developed to allow the combination of hardware and simulation to ensure safety in usage even at an early stage of development. This article proposes an architecture to integrate an entire test vehicle—denominated Dynamic Vehicle-in-the-Loop (DynViL)—in a virtual environment. This approach enables the interaction of a real vehicle with virtual traffic participants. The vehicle is physically tested on an empty track, but connected to the CARLA simulator, in which virtual driving scenarios are created. The simulated environment is transmitted to the vehicle driving function which controls the real vehicle in reaction to the virtual objects perceived in simulation. Furthermore, the performance of the DynViL in different test scenarios is evaluated. The results show that the reproducibility of the tests with the DynViL is satisfactory. Furthermore, the results indicate that the deviation between simulation and DynViL variates according to the vehicle speed and the complexity of the scenario. Based on the performance of the DynViL in comparison to simulation, the DynViL can be implemented as a complementary test method to be added to the transition between hardware in the loop (HiL) and proving ground. In this test method, erratic or unexpected behavior generated by the driving function and controllers can be detected in the real vehicle dynamics in a risk-free manner. UR - https://doi.org/10.4271/12-05-04-0029 KW - automated driving KW - safety KW - test KW - track KW - vehicle dynamics KW - virtual KW - driving functions KW - automated emergency braking Y1 - 2022 UR - https://doi.org/10.4271/12-05-04-0029 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-24952 SN - 2574-0741 SN - 2574-075X VL - 5 IS - 4 PB - SAE International CY - Warrendale ER - TY - JOUR A1 - Mohan, Nihesh A1 - Ahuir-Torres, Juan Ignacio A1 - Kotadia, Hiren R. A1 - Elger, Gordon T1 - Laser sintering of Cu particle-free inks for high-performance printed electronics JF - npj Flexible Electronics N2 - This study investigates laser sintering of Cu particle-free ink (Cu formate tetrahydrate—amino-2-propanol complex) as an alternative to conventional sintering in an oven (under inert/reducing atmosphere). Utilizing benefits of high-speed localized heating using laser, substrate damage can be prevented for low-melting substrates such as Polyethylene Terephthalate (PET). Firstly, a suitable sintering process window is achieved based on energy density for two different flexible polymeric susbtrates: Polyimide and PET using different laser parameters (laser power, scan rate and spot diameter). Subsequently, characterization of laser sintered traces are also made using different laser optic profiles (Gaussian and top hat). Different methodologies for fabrication of metallized Cu layer were also demonstrated. A very low bulk resistivity of 3.24 µΩcm (1.87 times of bulk Cu) was achieved on trace thickness of 0.85 ± 0.15 µm exhibiting good adherence to polymeric substrates. A promising fabrication process of low-cost and reliable flexible printed electronic devices is demonstrated. UR - https://doi.org/10.1038/s41528-025-00389-5 Y1 - 2025 UR - https://doi.org/10.1038/s41528-025-00389-5 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58266 SN - 2397-4621 VL - 9 IS - 1 PB - Springer CY - London ER - TY - JOUR A1 - Stöttner, Julia A1 - Hanzl, Christian A1 - Terbrack, Christoph A1 - Endisch, Christian T1 - Holistic evaluation and optimization of multilevel inverter designs for electric vehicle applications JF - Energy Reports N2 - To advance the development of multilevel inverters (MLIs) for electric vehicle applications, this study introduces novel asymmetric MLI (AMLI) configurations featuring buffer modules to enhance efficiency. A comprehensive comparative analysis of 125 distinct inverter systems is conducted, integrating five different microtopologies and 25 representative symmetrical MLI (SMLI) and AMLI systems. Unlike previous studies, this work employs a successive design process with a graph-based approach to systematically minimize conduction losses. Furthermore, experimental loss measurements ensure practical relevance. By applying Pareto optimization with cost, energy losses, and total harmonic distortion as objective functions, the study identifies the most promising MLI systems among all considered ones. While the cascaded H-bridge MLI emerges as the most cost-effective solution, specific SMLI configurations with 12 or 18 battery cells per module and AMLI designs featuring buffer modules exhibit lower inverter losses. In both cases, the incorporation of microtopologies that enable parallel operation leads to a remarkable reduction in inverter losses by more than 30 % compared to the least efficient MLI systems. Finally, a comparative assessment against a conventional B6-bridge SiC inverter highlights the significant advantages of these optimized MLI configurations in terms of efficiency and system performance. UR - https://doi.org/10.1016/j.egyr.2025.03.001 Y1 - 2025 UR - https://doi.org/10.1016/j.egyr.2025.03.001 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58297 SN - 2352-4847 VL - 2025 IS - 13 SP - 3561 EP - 3573 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Bazzi, Alessandro A1 - Sepulcre, Miguel A1 - Delooz, Quentin A1 - Festag, Andreas A1 - Vogt, Jonas A1 - Wieker, Horst A1 - Berens, Friedbert A1 - Spaanderman, Paul T1 - Multi-Channel Operation for the Release 2 of ETSI Cooperative Intelligent Transport Systems JF - IEEE Communications Standards Magazine N2 - Vehicles and road infrastructure are starting to be equipped with vehicle-to-everything (V2X) communication solutions to increase road safety and provide new services to drivers and passengers. In Europe, the deployment is based on a set of Release 1 standards developed by ETSI to support basic use cases for cooperative intelligent transport systems (C-ITS). For them, the capacity of a single 10 MHz channel in the ITS band at 5.9 GHz is considered sufficient. At the same time, the ITS stakeholders are working toward several advanced use cases, which imply a significant increment of data traffic and the need for multiple channels. To address this issue, ETSI has recently standardized a new multi-channel operation (MCO) concept for flexible, efficient, and future-proof use of multiple channels. This new concept is defined in a set of new specifications that represent the foundation for the future releases of C-ITS standards. The present article provides a comprehensive review of the new set of specifications, describing the main entities that extend the C-ITS architecture at the different layers of the protocol stack. In addition, the article provides representative examples that describe how these MCO standards will be used in the future and discusses some of the main open issues arising. The review and analysis of this article facilitate the understanding and motivation of the new set of Release 2 ETSI specifications for MCO and the identification of new research opportunities. UR - https://doi.org/10.1109/MCOMSTD.0001.2200080 Y1 - 2024 UR - https://doi.org/10.1109/MCOMSTD.0001.2200080 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58154 SN - 2471-2833 VL - 8 IS - 1 SP - 28 EP - 35 PB - IEEE CY - New York ER - TY - JOUR A1 - Theissler, Andreas A1 - Pérez-Velázquez, Judith A1 - Kettelgerdes, Marcel A1 - Elger, Gordon T1 - Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry JF - Reliability Engineering & System Safety N2 - Recent developments in maintenance modelling fuelled by data-based approaches such as machine learning (ML), have enabled a broad range of applications. In the automotive industry, ensuring the functional safety over the product life cycle while limiting maintenance costs has become a major challenge. One crucial approach to achieve this, is predictive maintenance (PdM). Since modern vehicles come with an enormous amount of operating data, ML is an ideal candidate for PdM. While PdM and ML for automotive systems have both been covered in numerous review papers, there is no current survey on ML-based PdM for automotive systems. The number of publications in this field is increasing — underlining the need for such a survey. Consequently, we survey and categorize papers and analyse them from an application and ML perspective. Following that, we identify open challenges and discuss possible research directions. We conclude that (a) publicly available data would lead to a boost in research activities, (b) the majority of papers rely on supervised methods requiring labelled data, (c) combining multiple data sources can improve accuracies, (d) the use of deep learning methods will further increase but requires efficient and interpretable methods and the availability of large amounts of (labelled) data. UR - https://doi.org/10.1016/j.ress.2021.107864 KW - predictive maintenance KW - artificial intelligence KW - machine learning KW - deep learning KW - vehicle KW - automotive KW - reliability KW - lifetime prediction KW - condition monitoring Y1 - 2021 UR - https://doi.org/10.1016/j.ress.2021.107864 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-9673 SN - 0951-8320 VL - 2021 IS - 215 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Da Silva Junior, Amauri A1 - Birkner, Christian A1 - Jazar, Reza A1 - Marzbani, Hormoz T1 - Crash-Prone Fault Combination Identification for Over-Actuated Vehicles During Evasive Maneuvers JF - IEEE Access N2 - Throughout a vehicle’s lifecycle, systems may fail during operation, requiring effective fault management by the vehicle controller. Various system faults affect vehicle handling differently. Additionally, vehicle velocity and road friction directly impact handling and stability. Thus, it is essential to investigate relevant factors, such as actuator faults, vehicle velocity, road friction, and their combinations, before developing a fault-tolerant controller to mitigate potential critical situations. Our work thus focuses on identifying faults and fault combinations that might lead to crashes for over-actuated vehicles during evasive maneuvers and those impacting comfort parameters. We employ a state-of-the-art vehicle controller optimized for evasive lane changes for over-actuated vehicles. The driving scenario encompasses critical conditions defined in ISO 26262 with ASIL-D, including velocities up to 130 km/h and requiring steering away from obstacles. Failure Mode and Effects Analysis, Design of Experiments, and statistical tools are used to determine fault combinations most likely to lead to crashes during evasive maneuvers. Our results indicate that the vehicle controller successfully handled the maneuver in over 53% of investigated cases, reaching up to 75.1% on dry surfaces. Road friction emerges as the most critical parameter for collision avoidance and comfort. Brake faults exhibit a higher influence on vehicle handling than other actuator faults, while single motor faults do not significantly impact vehicle parameters. Regarding two-factor interactions, brake actuators dominate, followed by steering and motor. These findings provide valuable insights for developing fault-tolerant controllers for over-actuated vehicles, guiding decisions on addressing specific faults to enhance safety and comfort parameters. UR - https://doi.org/10.1109/ACCESS.2024.3374524 Y1 - 2024 UR - https://doi.org/10.1109/ACCESS.2024.3374524 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-46165 SN - 2169-3536 VL - 12 SP - 37256 EP - 37275 PB - IEEE CY - New York ER - TY - JOUR A1 - Song, Rui A1 - Zhou, Liguo A1 - Lyu, Lingjuan A1 - Festag, Andreas A1 - Knoll, Alois T1 - ResFed: Communication-Efficient Federated Learning With Deep Compressed Residuals JF - IEEE Internet of Things Journal N2 - Federated learning allows for cooperative training among distributed clients by sharing their locally learned model parameters, such as weights or gradients. However, as model size increases, the communication bandwidth required for deployment in wireless networks becomes a bottleneck. To address this, we propose a residual-based federated learning framework (ResFed) that transmits residuals instead of gradients or weights in networks. By predicting model updates at both clients and the server, residuals are calculated as the difference between updated and predicted models and contain more dense information than weights or gradients. We find that the residuals are less sensitive to an increasing compression ratio than other parameters, and hence use lossy compression techniques on residuals to improve communication efficiency for training in federated settings. With the same compression ratio, ResFed outperforms current methods (weight- or gradient-based federated learning) by over 1.4× on federated data sets, including MNIST, FashionMNIST, SVHN, CIFAR-10, CIFAR-100, and FEMNIST, in client-to-server communication, and can also be applied to reduce communication costs for server-to-client communication. UR - https://doi.org/10.1109/JIOT.2023.3324079 Y1 - 2023 UR - https://doi.org/10.1109/JIOT.2023.3324079 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-46371 SN - 2327-4662 VL - 11 IS - 6 SP - 9458 EP - 9472 PB - IEEE CY - New York ER - TY - JOUR A1 - Hegde, Anupama A1 - Song, Rui A1 - Festag, Andreas T1 - Radio Resource Allocation in 5G-NR V2X: A Multi-Agent Actor-Critic Based Approach JF - IEEE Access N2 - The efficiency of radio resource allocation and scheduling procedures in Cellular Vehicle-to-X (Cellular V2X) communication networks directly affects link quality in terms of latency and reliability. However, owing to the continuous movement of vehicles, it is impossible to have a centralized coordinating unit at all times to manage the allocation of radio resources. In the unmanaged mode of the fifth generation new radio (5G-NR) V2X, the sensing-based semi-persistent scheduling (SB-SPS) loses its effectiveness when V2X data messages become aperiodic with varying data sizes. This leads to misinformed resource allocation decisions among vehicles and frequent resource collisions. To improve resource selection, this study formulates the Cellular V2X communication network as a decentralized multi-agent networked markov decision process (MDP) where each vehicle agent executes an actor-critic-based radio resource scheduler. Developing further the actor-critic methodology for the radio resource allocation problem in Cellular V2X, two variants are derived: independent actor-critic (IAC) and shared experience actor-critic (SEAC). Results from simulation studies indicate that the actor-critic schedulers improve reliability, achieving a 15-20% higher probability of reception under high vehicular density scenarios with aperiodic traffic patterns. UR - https://doi.org/10.1109/ACCESS.2023.3305267 KW - Cellular V2X KW - radio resource allocation KW - deep reinforcement learning Y1 - 2023 UR - https://doi.org/10.1109/ACCESS.2023.3305267 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-39352 SN - 2169-3536 VL - 11 SP - 87225 EP - 87244 PB - IEEE CY - New York ER - TY - JOUR A1 - Agrawal, Shiva A1 - Bhanderi, Savankumar A1 - Elger, Gordon T1 - Semi-Automatic Annotation of 3D Radar and Camera for Smart Infrastructure-Based Perception JF - IEEE Access N2 - Environment perception using camera, radar, and/or lidar sensors has significantly improved in the last few years because of deep learning-based methods. However, a large group of these methods fall into the category of supervised learning, which requires a considerable amount of annotated data. Due to uncertainties in multi-sensor data, automating the data labeling process is extremely challenging; hence, it is performed manually to a large extent. Even though full automation of such a process is difficult, semiautomation can be a significant step to ease this process. However, the available work in this regard is still very limited; hence, in this paper, a novel semi-automatic annotation methodology is developed for labeling RGB camera images and 3D automotive radar point cloud data using a smart infrastructure-based sensor setup. This paper also describes a new method for 3D radar background subtraction to remove clutter and a new object category, GROUP, for radar-based object detection for closely located vulnerable road users. To validate the work, a dataset named INFRA-3DRC is created using this methodology, where 75% of the labels are automatically generated. In addition, a radar cluster classifier and an image classifier are developed, trained, and tested on this dataset, achieving accuracy of 98.26% and 94.86%, respectively. The dataset and Python scripts are available at https://fraunhoferivi.github.io/INFRA-3DRC-Dataset/. UR - https://doi.org/10.1109/ACCESS.2024.3373310 Y1 - 2024 UR - https://doi.org/10.1109/ACCESS.2024.3373310 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-46180 SN - 2169-3536 VL - 12 SP - 34325 EP - 34341 PB - IEEE CY - New York ER - TY - JOUR A1 - Bauder, Maximilian A1 - Kubjatko, Tibor A1 - Schweiger, Hans-Georg T1 - Cooperative Awareness Messages’ Generation Frequencies, Trigger Distributions, and Pseudonym Changes of First Commercially Deployed Vehicles in Real Operating Scenarios JF - IEEE Access N2 - Cooperative Intelligent Transport Systems have been deployed in mass-produced vehicles in Europe (Golf 8, ID.3, etc.) since 2019, promising major improvements in vehicle safety, efficiency, and comfort. Equipped with Vehicle-to-X communication, the vehicles directly send information about their driving status to the environment. The data are already used for many Vehicle-to-X communication use-cases specified by the Car-2-Car Communication Consortium to achieve the above-mentioned improvements. This study focuses on using Vehicle-2-X communication and its messages for accident analysis. For this purpose, we investigated the advantage in temporal resolution of the continuously sent Cooperative Awareness Message compared to the Event-Data-Recorder for accident reconstruction in the pre-crash. A high resolution of the temporal accident scene is essential for the doubtless clarification of accidents. Therefore, we analyzed the generation frequencies and the trigger conditions of the Cooperative Awareness Message of vehicles available on the European market while driving in real traffic and during different parking maneuvers. Also, the pseudonym change was analyzed. We found that the average generation frequency of the Cooperative Awareness Message is higher than the 2.00 Hz recording frequency of the event data recorder for all scenarios investigated. Especially on rural roads and highways, the temporal resolution is advantageous. Since many serious accidents occur on rural roads, the use of Cooperative Awareness Messages could significantly benefit the reconstruction of the accident scene. Thus, we recommend increasing efforts to use the Cooperative Awareness Message as digital data for accident analysis and encourage more scientists to deal with this topic. UR - https://doi.org/10.1109/ACCESS.2023.3292576 KW - Accident analysis KW - accident reconstruction KW - cooperative awareness message KW - cooperative intelligent transport systems KW - fundamental data KW - real operating investigation KW - vehicle-2-X communication Y1 - 2023 UR - https://doi.org/10.1109/ACCESS.2023.3292576 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-38543 SN - 2169-3536 VL - 11 SP - 69708 EP - 69719 PB - IEEE CY - New York ER - TY - JOUR A1 - Mohan, Nihesh A1 - Steinberger, Fabian A1 - Wächter, Sonja A1 - Erdogan, Hüseyin A1 - Elger, Gordon T1 - Additive Manufacturing for Automotive Radar Sensors Using Copper Inks and Pastes JF - Applied Sciences N2 - Radar sensors are critical for obstacle detection and navigation, especially for automated driving. Using the use-case “printing of heating coils on the inside of the front housing (primary radome)” needed for de-icing in winter, it is demonstrated that additive manufacturing (AM) can provide economic and functional benefits for manufacturing of the sensors. AM will allow significant cost reduction by eliminating parts and simplifying the manufacturing process. Different AM technologies for the coils were investigated, first, by applying the conductive traces by fused deposition modeling (FDM), and, second, by printing copper particle-free inks and pastes. The metal layers were electrically and mechanically characterized using a profilometer to measure the trace dimension and a four-point probe to measure the resistance. It was revealed that low-cost conductive filaments with low resistivity and current carrying capacity are commercially still not available. The best option sourced was a copper–polyester-based filament with 6000 µΩcm after printing. Therefore, low-cost particle-free copper inks and commercial copper flake paste were selected to print the heating coil. The Cu particle-free inks were amine-based Cu (II) formate complexes, where the Cu exists in an ionic form. Using contactless printing processes such as ink-jet printing or pneumatic dispensing, the traces could be deposited onto the low-melting temperature (225 °C) polymeric radome structure. After printing, the material needed to be sintered to form the conductive copper traces. To avoid damaging the polymer radome during sintering, two different processes were investigated: low-temperature (<150 °C) sintering in an oven for 30 min or fast laser sintering. The sintered Cu layers achieved the following specific electric resistivities when slowly sintered in the oven: paste 4 µΩcm and ink 8.8 µΩcm. Using laser sintering, the ink achieved 3.2 µΩcm because the locally high temperature provides better sintering. Also, the adhesion was significantly increased to (5 B). Therefore, laser sintering is the preferred technology. In addition, it allows fast processing directly after printing. Commercial equipment is available where printing and laser sintering is integrated. The potential of low-cost copper material and the integration in additive manufacturing of electronic systems using radar sensors as an example are demonstrated in this paper. UR - https://doi.org/10.3390/app15052676 Y1 - 2025 UR - https://doi.org/10.3390/app15052676 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58065 SN - 2076-3417 VL - 15 IS - 5 PB - MDPI CY - Basel ER -