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 - 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 - CHAP A1 - Kleiner, Jan A1 - Heider, Alexander A1 - Hanzl, Christian A1 - Komsiyska, Lidiya A1 - Elger, Gordon A1 - Endisch, Christian T1 - Thermal behavior of an intelligent li-ion cell under vehicle conditions T2 - Proceedings: IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society UR - https://doi.org/10.1109/IECON43393.2020.9254336 KW - Li-ion KW - electro-thermal model KW - intelligent battery KW - reconfigurable system KW - smart cell Y1 - 2020 UR - https://doi.org/10.1109/IECON43393.2020.9254336 SN - 978-1-7281-5414-5 SN - 2577-1647 SP - 2081 EP - 2086 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Schmid, Michael A1 - Gebauer, Emanuel A1 - Hanzl, Christian A1 - Endisch, Christian T1 - Active model-based fault diagnosis in reconfigurable battery systems JF - IEEE Transactions on Power Electronics UR - https://doi.org/10.1109/TPEL.2020.3012964 KW - active fault isolation KW - active hypothesis testing KW - constrained parameter estimation KW - fault tolerance KW - fuzzy clustering KW - reconfigurable battery system (RBS) Y1 - 2020 UR - https://doi.org/10.1109/TPEL.2020.3012964 SN - 1941-0107 SN - 0885-8993 VL - 36 IS - 3 SP - 2584 EP - 2597 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Hanzl, Christian A1 - Hartmann, Christoph A1 - Hölzle, Markus A1 - Liebhart, Bernhard A1 - Schmid, Michael A1 - Endisch, Christian T1 - Current commutation in a switched lithium-ion cell used in cascaded half-bridge multilevel inverters JF - IET Power Electronics N2 - In order to improve the efficiency of battery electric vehicles, the utilization of reconfigurable batteries and multilevel inverters based on low-voltage Si MOSFETs gains growing attention. Focusing on the half-bridge as basic switching unit, this paper examines voltage and current waveforms during switching. It is shown that the current commutation speed depends on various factors such as sign and amplitude of the current as well as the particular switching scenario. For instance, turning off a positive cell current takes 0.21 𝜇s while turning it on takes 0.9 𝜇s. In addition, it is revealed that depending on the switching scenario and current direction, the lithium-ion cell supports or opposes the remagnetization of the parasitic inductances and therefore the switching losses of the MOSFETs. Switching a positive load current of 125 A from active to bypass converts 276 𝜇J into heat while switching from bypass to active converts merely 32.5 𝜇J into heat. UR - https://doi.org/10.1049/pel2.12088 Y1 - 2021 UR - https://doi.org/10.1049/pel2.12088 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13364 SN - 1755-4543 VL - 14 IS - 6 SP - 1073 EP - 1088 PB - Wiley CY - Hoboken ER - TY - CHAP A1 - Mayer, Sebastian A1 - Arnet, Christian A1 - Gankin, Dennis A1 - Endisch, Christian T1 - Standardized framework for evaluating centralized and decentralized control systems in modular assembly systems T2 - 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) UR - https://doi.org/10.1109/SMC.2019.8914314 KW - virtual commissioning KW - cyber-physical production system KW - digital manufacturing KW - scheduling KW - production control KW - multi-agent system KW - modular assembly system Y1 - 2019 UR - https://doi.org/10.1109/SMC.2019.8914314 SN - 978-1-7281-4569-3 SP - 113 EP - 119 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Mayer, Sebastian A1 - Gankin, Dennis A1 - Arnet, Christian A1 - Endisch, Christian T1 - Adaptive production control with negotiating agents in modular assembly systems T2 - 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) UR - https://doi.org/10.1109/SMC.2019.8914498 KW - multi-agent system KW - negotiation-based coordination KW - intelligent manufacturing KW - production scheduling KW - production control KW - modular assembly system Y1 - 2019 UR - https://doi.org/10.1109/SMC.2019.8914498 SN - 978-1-7281-4569-3 SP - 120 EP - 127 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Gerngroß, Martin A1 - Herrmann, Patrick A1 - Westermaier, Christian A1 - Endisch, Christian T1 - Highly flexible needle winding kinematics for traction stators based on a standard industrial robot T2 - 2017 7th International Electric Drives Production Conference (EDPC) UR - https://doi.org/10.1109/EDPC.2017.8328147 KW - Needle Winding KW - Industrial Robot KW - Distributed Windings KW - Automation KW - Stator Production Y1 - 2017 UR - https://doi.org/10.1109/EDPC.2017.8328147 SN - 978-1-5386-1069-5 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Gerngroß, Martin A1 - Herrmann, Patrick A1 - Endisch, Christian A1 - Westermaier, Christian T1 - Optimization of the End Winding Patterns in Needle Wound Traction Stators T2 - Proceedings, 2019 IEEE International Conference on Mechatronics (ICM) UR - https://doi.org/10.1109/ICMECH.2019.8722897 KW - needle winding KW - end winding patterns KW - optimization method KW - virtual tool chain Y1 - 2019 UR - https://doi.org/10.1109/ICMECH.2019.8722897 SN - 978-1-5386-6959-4 SP - 314 EP - 320 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Stöttner, Julia A1 - Hanzl, Christian A1 - Endisch, Christian T1 - Experimental investigation of parasitic side effects in MOSFET-based multilevel inverter for electric vehicle applications JF - Electric Power Systems Research UR - https://doi.org/10.1016/j.epsr.2023.109197 Y1 - 2023 UR - https://doi.org/10.1016/j.epsr.2023.109197 SN - 1873-2046 SN - 0378-7796 VL - 2023 IS - 218 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Williams Ngaleu, Guy A1 - Theiler, Michael A1 - Straßer, Xenia A1 - Hanzl, Christian A1 - Komsiyska, Lidiya A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Influence of Switching on the Aging of High Power Lithium-Ion Cells JF - Batteries N2 - For intelligent battery systems that are able to control the current flow for each individual cell, the multilevel inverter is an interesting approach to replace the bidirectional AC/DC-converter and improve flexibility of charging system and signal quality in both directions. Therefore, the cells are modulated by switching varying the duty cycle, the current and the frequency up to the kHz-range. This is only beneficial if the switching does not lead to a significant additional aging. The scientific gap to assess and understand the impact of switching is investigated in this paper by testing 22 high-power 18650 lithium-ion cells (Samsung 25R). The cells are tested at 50 Hz and 10 kHz switching frequency during charge, discharge and charge/discharge at 50% duty cycle. The tests are compared to eight reference tests with continuous current flow performed at the average and the maximum current for charge and discharge, respectively. The results are obtained by evaluating the remaining capacity, resistance, electrochemical impedance spectroscopy and dV/dQ analysis. Before reaching rollover, the investigated cells lose homogeneity and cathode capacity but no significant difference for the aging parameters are found. After rollover, the cell-to-cell variation is greater than the aging induced by the different cycling parameters. UR - https://doi.org/10.3390/batteries8040033 KW - 18650 KW - NCA KW - graphite KW - switching KW - multilevel inverter KW - frequency KW - cycle life Y1 - 2022 UR - https://doi.org/10.3390/batteries8040033 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-22861 SN - 2313-0105 VL - 8 IS - 4 PB - MDPI CY - Basel ER - TY - CHAP A1 - Hanzl, Christian A1 - Stöttner, Julia A1 - Hölzle, Markus A1 - Endisch, Christian T1 - Experimental Investigation and Analytical Modeling of Half-Bridge Switching Losses in Reconfigurable Lithium-Ion Cells T2 - ICPE 2023 - ECCE Asia: 11th International Conference on Power Electronics - ECCE Asia UR - https://doi.org/10.23919/ICPE2023-ECCEAsia54778.2023.10213901 KW - half-bridge KW - lithium-ion cell KW - MOSFET switching losses KW - multilevel inverter Y1 - 2023 UR - https://doi.org/10.23919/ICPE2023-ECCEAsia54778.2023.10213901 SN - 978-89-5708-350-5 SP - 1058 EP - 1065 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Kohler, Markus A1 - Herrera, Christian A1 - Gerngroß, Martin A1 - Kennel, Ralph A1 - Endisch, Christian T1 - Empirical Investigation and Feed-Forward Control of Wire Tension in Needle Winding Processes T2 - 2024 IEEE 33rd International Symposium on Industrial Electronics (ISIE), Proceedings UR - https://doi.org/10.1109/ISIE54533.2024.10595747 Y1 - 2024 UR - https://doi.org/10.1109/ISIE54533.2024.10595747 SN - 979-8-3503-9408-5 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Straßer, Xenia A1 - Williams Ngaleu, Guy A1 - Hanzl, Christian A1 - Azzam, Mohamed A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Influence of Switching on the Aging of High Energy Lithium-Ion Cells JF - Batteries N2 - An AC-battery or multilevel inverter used to increase safety and flexibility is realizable by switching the cells and modules on and off in a defined way and thus can replace the bidirectional converter. Assessing possible additional aging due to switching, the results of a previous study for a high-power optimized cell showed no influence on the current rates or the switching. In this paper, a highly energy-optimized LG 18650-cell is investigated to discuss the influence of switching during the charge and discharge process, respectively, as well as combining both processes together with clear performance differences when applying higher charge and discharge currents. Moreover, the influence of switching is discussed for the two frequencies (50 Hz and 10 kHz) and different duty cycles. The aging is analyzed by capacity loss and resistance increase, by dV/dQ analysis, and by electrochemical impedance spectroscopy. We found no clear negative influence of switching but a positive effect if the cells are switched during charge. The best performance is found for switching during charge as well as during discharge. The cell aging during switching is clearly determined by the average and not the maximum current applied. This work shows no negative effects of multilevel inverter applications on the tested cells. UR - https://doi.org/10.3390/batteries9020139 KW - 18650 KW - NMC811 KW - Graphite KW - switching KW - multilevel inverter KW - frequency KW - cycle life Y1 - 2023 UR - https://doi.org/10.3390/batteries9020139 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-41074 SN - 2313-0105 VL - 9 IS - 2 PB - MDPI CY - Basel ER - TY - CHAP A1 - Hanzl, Christian A1 - Endisch, Christian T1 - Closed-Form Modeling of MOSFET Switching Losses Including Variable Gate-Drain Capacitance and Zero-Voltage Switching T2 - Proceedings of the 2025 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific) UR - https://doi.org/10.1109/ITECAsia-Pacific63742.2025.11345027 Y1 - 2026 UR - https://doi.org/10.1109/ITECAsia-Pacific63742.2025.11345027 SN - 979-8-3315-5984-7 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Stöttner, Julia A1 - Hanzl, Christian A1 - Endisch, Christian T1 - Extensive investigation of symmetrical and asymmetrical cascaded multilevel inverters for electric vehicle applications JF - Electric Power Systems Research UR - https://doi.org/10.1016/j.epsr.2022.108009 KW - Asymmetrical multilevel inverter (MLI) KW - Symmetrical multilevel inverter (MLI) KW - Level Redundancy KW - Voltage pattern KW - Total harmonic distortion (THD) Y1 - 2022 UR - https://doi.org/10.1016/j.epsr.2022.108009 SN - 1873-2046 SN - 0378-7796 VL - 2022 IS - 209 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schwertner, Stefan A1 - Buchberger, Tobias A1 - Diehl, Simon A1 - Ferg, Rebekka A1 - Hanzl, Christian A1 - Hartmann, Christoph A1 - Hölzle, Markus A1 - Kleiner, Jan A1 - Komsiyska, Lidiya A1 - Lewerenz, Meinert A1 - Liebhart, Bernhard A1 - Schmid, Michael A1 - Schneider, Dominik A1 - Scholz, Florian A1 - Speer, Sascha A1 - Stöttner, Julia A1 - Terbrack, Christoph A1 - Hinterberger, Michael A1 - Endisch, Christian T1 - Design and Implementation of an Intelligent Reconfigurable High-Voltage Battery System for Next-Generation Electric Vehicles JF - Batteries N2 - Battery system engineers face the challenge of balancing competing requirements regarding performance, maintainability, sustainability, safety, and cost—especially in the automotive industry. IBS potentially offer a solution with fewer trade-offs. They feature a battery management system with advanced sensing and data analysis capabilities that facilitate improved battery monitoring and operation. Reconfigurable energy storage units enable sophisticated operating strategies, including complete cell state control, full energy content utilization, and a measured response to faults. This article presents the design, development, and operation of a full-scale intelligent battery system prototype comprising 324 automotive lithium-ion cells with a nominal voltage of 400V. The system exhibits a modular single cell architecture and an advanced centralized battery management system. We detail the system architecture, hardware and software component design, and system integration. Initial tests demonstrate the battery’s operability, extended functionality, and enhanced safety. Our analysis shows that the additional losses introduced by reconfigurability are more than offset by the benefits of full energy utilization—even for new cells, with increasing advantage as aging progresses. The results underscore the potential of intelligent battery systems and motivate further research and development toward economic assessment and industrial adoption. UR - https://doi.org/10.3390/batteries11110424 Y1 - 2025 UR - https://doi.org/10.3390/batteries11110424 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64086 SN - 2313-0105 VL - 11 IS - 11 PB - MDPI CY - Basel ER - TY - JOUR A1 - Kleiner, Jan A1 - Komsiyska, Lidiya A1 - Elger, Gordon A1 - Endisch, Christian T1 - Thermal modelling of a prismatic lithium-ion cell in a battery electric vehicle environment BT - influences of the experimental validation setup JF - Energies N2 - In electric vehicles with lithium-ion battery systems, the temperature of the battery cells has a great impact on performance, safety, and lifetime. Therefore, developing thermal models of lithium-ion batteries to predict and investigate the temperature development and its impact is crucial. Commonly, models are validated with experimental data to ensure correct model behaviour. However, influences of experimental setups or comprehensive validation concepts are often not considered, especially for the use case of prismatic cells in a battery electric vehicle. In this work, a 3D electro–thermal model is developed and experimentally validated to predict the cell’s temperature behaviour for a single prismatic cell under battery electric vehicle (BEV) boundary conditions. One focus is on the development of a single cell’s experimental setup and the investigation of the commonly neglected influences of an experimental setup on the cell’s thermal behaviour. Furthermore, a detailed validation is performed for the laboratory BEV scenario for spatially resolved temperatures and heat generation. For validation, static and dynamic loads are considered as well as the detected experimental influences. The validated model is used to predict the temperature within the cell in the BEV application for constant current and Worldwide harmonized Light vehicles Test Procedure (WLTP) load profile. UR - https://doi.org/10.3390/en13010062 KW - Lithium-Ionen-Batterie KW - Elektrofahrzeug Y1 - 2019 UR - https://doi.org/10.3390/en13010062 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-7532 SN - 1996-1073 VL - 13 IS - 1 PB - MDPI CY - Basel ER - TY - JOUR A1 - Eriksson, Lars A1 - Thomasson, Andreas A1 - Ekberg, Kristoffer A1 - Reig, Alberto A1 - Eifert, Mark A1 - Donatantonio, Fabrizio A1 - D'Amato, Antonio A1 - Arsie, Ivan A1 - Pianese, Cesare A1 - Otta, Pavel A1 - Held, Manne A1 - Vögele, Ulrich A1 - Endisch, Christian T1 - Look-ahead controls of heavy duty trucks on open roads — six benchmark solutions JF - Control Engineering Practice UR - https://doi.org/10.1016/j.conengprac.2018.10.014 KW - Engine model KW - Driveline model KW - Vehicle model KW - Control design KW - Optimal control Y1 - 2018 UR - https://doi.org/10.1016/j.conengprac.2018.10.014 SN - 1873-6939 VL - 2019 IS - 83 SP - 45 EP - 66 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Liebhart, Bernhard A1 - Satzke, Martin A1 - Komsiyska, Lidiya A1 - Endisch, Christian T1 - Application of nonlinear impedance spectroscopy for the diagnosis of lithium-ion battery cells under various operating conditions JF - Journal of Power Sources UR - https://doi.org/10.1016/j.jpowsour.2020.228673 KW - Nonlinear impedance spectroscopy KW - Mechanical pressure KW - Frequency response functions KW - Volterra kernels Y1 - 2020 UR - https://doi.org/10.1016/j.jpowsour.2020.228673 SN - 1873-2755 VL - 2020 IS - 480 PB - Elsevier CY - New York ER - TY - JOUR A1 - Liebhart, Bernhard A1 - Komsiyska, Lidiya A1 - Endisch, Christian T1 - Passive impedance spectroscopy for monitoring lithium-ion battery cells during vehicle operation JF - Journal of Power Sources UR - https://doi.org/10.1016/j.jpowsour.2019.227297 KW - (Nonparametric) system identification KW - (Passive) impedance spectroscopy KW - Data-driven battery parameter estimation KW - Single-cell BMS Y1 - 2019 UR - https://doi.org/10.1016/j.jpowsour.2019.227297 SN - 1873-2755 VL - 2020 IS - 449 PB - Elsevier CY - New York ER - TY - JOUR A1 - Schneider, Dominik A1 - Vögele, Ulrich A1 - Endisch, Christian T1 - Model-based sensor data fusion of quasi-redundant voltage and current measurements in a lithium-ion battery module JF - Journal of Power Sources UR - https://doi.org/10.1016/j.jpowsour.2019.227156 KW - Battery model KW - Current sensor KW - Dual kalman filter KW - Sensor data fusion KW - State estimation KW - Weighted least squares Y1 - 2019 UR - https://doi.org/10.1016/j.jpowsour.2019.227156 SN - 1873-2755 VL - 2019 IS - 440 PB - Elsevier CY - New York 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 - 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 - 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 - Rauscher, Andreas A1 - Stenzel, Peer A1 - Endisch, Christian T1 - Investigation of Factors Influencing the End-of-Line Partial Discharge Testing of Electrical Machines T2 - 2025 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD) UR - https://doi.org/10.1109/WEMDCD61816.2025.11014117 Y1 - 2025 UR - https://doi.org/10.1109/WEMDCD61816.2025.11014117 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Schreiber, Markus A1 - Lin, Yilei A1 - Sommer, Alessandro A1 - Wassiliadis, Nikolaos A1 - Morales Torricos, Pablo A1 - Rogge, Marcel A1 - Lewerenz, Meinert A1 - Grosu, Cristina A1 - Endisch, Christian A1 - Jossen, Andreas A1 - Lienkamp, Markus T1 - Apparent vs. true battery aging: Impact of various load characteristics on accelerated aging tests JF - Journal of Energy Storage N2 - Vehicle applications involve highly dynamic and variable operating conditions. These result from changing driving profiles and diverse driving behaviors. To accelerate battery aging tests, experiments are often based on constant load cycles. While efficient, this approach distorts the natural degradation behavior of the cells. This study compares cell aging under real-world and laboratory load conditions. For this purpose, we compare realistic driving profiles measured in a test vehicle in the field with synthetic constant power cycles. Average discharge power and charging sequences are kept identical for comparability. Results show that constant power cycles cause stronger cell aging than dynamic loads. Differential voltage analysis indicates more lithium inventory loss and active material loss at the negative electrode under static loads. Static loading also leads to strong inhomogeneity in the negative electrode and altered charge transfer and diffusion kinetics, as shown by impedance data. After 15 months of rest, the cells recovered up to 52 of lost capacity and 66 of the resistance increase. Impedance assessment and differential voltage analysis confirm the recovery and rehomogenization of the negative electrode. These findings show that conventional accelerated tests are strongly influenced by relaxation and load dynamics. As a result, their applicability to specific use cases, such as automotive applications, is strongly limited . Therefore, andraditional test strategies require reconsideration and redesign. UR - https://doi.org/10.1016/j.est.2025.116924 Y1 - 2025 UR - https://doi.org/10.1016/j.est.2025.116924 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59653 SN - 2352-1538 VL - 2025 IS - 127 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Azzam, Mohamed A1 - Aydin, Atakhan A1 - Endisch, Christian A1 - Sauer, Dirk Uwe A1 - Lewerenz, Meinert T1 - Float Current Analysis for Lithium-Ion Battery Aging: Insights into SEI Growth and Cathode Lithiation with EIS and ICP OES JF - Journal of The Electrochemical Society N2 - This study investigates calendar-aging mechanisms in lithium-ion batteries, focusing on cathode lithiation due to decomposition of conductive salt and SEI growth, by correlating quantified float currents, capacity loss rates, and pulse resistances with changes in electrochemical impedance spectroscopy (EIS) spectra. Seven SamSung 25 R cells are aged at different float voltages with periodic EIS measurements at 30 °C. Using a pre-characterization cell, the internal processes via EIS are allocated across various states of charge and temperatures and GITT measurements are performed to derive scaling factors. GITT, float currents and capacity loss rate measurements at 30 °C enables the separation of SEI growth ISEI growth and cathode lithiation current ICL based on float current behavior across a temperature range of 5 °C to 50 °C. The distribution of relaxation times (DRT) method is employed to deconvolute overlapping electrochemical processes. EIS and DRT analyses showed significant changes in cathode charge transfer resistance and diffusion, confirming that cathode lithiation correlates substantially to elevated internal resistance at high cell voltages. The theory of ISEI growth and ICL is further supported using inductively coupled plasma atomic emission spectroscopy by quantifying elemental inventory changes and linking phosphorus release and lithium consumption to degradation mechanisms. UR - https://doi.org/10.1149/1945-7111/adef85 Y1 - 2025 UR - https://doi.org/10.1149/1945-7111/adef85 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60922 SN - 1945-7111 VL - 172 IS - 7 PB - IOP Publishing CY - Bristol ER - TY - CHAP A1 - Gankin, Dennis A1 - Mayer, Sebastian A1 - Zinn, Jonas A1 - Vogel-Heuser, Birgit A1 - Endisch, Christian T1 - Modular Production Control with Multi-Agent Deep Q-Learning T2 - Proceedings: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) UR - https://doi.org/10.1109/ETFA45728.2021.9613177 Y1 - 2021 UR - https://doi.org/10.1109/ETFA45728.2021.9613177 SN - 978-1-7281-2989-1 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Schmid, Michael A1 - Kneidinger, Hans-Georg A1 - Endisch, Christian T1 - Data-driven fault diagnosis in battery systems through cross-cell monitoring JF - IEEE Sensors Journal UR - https://doi.org/10.1109/JSEN.2020.3017812 KW - Battery systems KW - data-driven fault diagnosis KW - fault isolation KW - recursive principal component analysis KW - signal processing Y1 - 2020 UR - https://doi.org/10.1109/JSEN.2020.3017812 SN - 1558-1748 SN - 1530-437X SN - 2379-9153 VL - 21 IS - 2 SP - 1829 EP - 1837 PB - IEEE CY - New York ER - TY - JOUR A1 - Kleiner, Jan A1 - Singh, Randeep A1 - Schmid, Michael A1 - Komsiyska, Lidiya A1 - Elger, Gordon A1 - Endisch, Christian T1 - Influence of heat pipe assisted terminal cooling on the thermal behavior of a large prismatic lithium-ion cell during fast charging in electric vehicles JF - Applied Thermal Engineering UR - https://doi.org/10.1016/j.applthermaleng.2020.116328 KW - Lithium-ion battery KW - Battery modeling KW - Electro-thermal model KW - Fast charging KW - Terminal cooling KW - Heat pipe Y1 - 2020 UR - https://doi.org/10.1016/j.applthermaleng.2020.116328 SN - 1359-4311 VL - 2021 IS - 188 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schmid, Michael A1 - Gebauer, Emanuel A1 - Endisch, Christian T1 - Structural analysis in reconfigurable battery systems for active fault diagnosis JF - IEEE Transactions on Power Electronics UR - https://doi.org/10.1109/TPEL.2021.3049573 KW - Active fault diagnosis KW - electrothermal battery model KW - minimal sensor set KW - reconfigurable battery KW - structural analysis Y1 - 2021 UR - https://doi.org/10.1109/TPEL.2021.3049573 SN - 1941-0107 VL - 36 IS - 8 SP - 8672 EP - 8684 PB - IEEE CY - New York ER - TY - CHAP A1 - Altmannshofer, Simon A1 - Endisch, Christian ED - Schröder, Dierk ED - Buss, Martin T1 - Robuste Parameterschätzung für reale Anwendungen T2 - Intelligente Verfahren: Identifikation und Regelung nichtlinearer Systeme UR - https://doi.org/10.1007/978-3-662-55327-5_12 Y1 - 2017 UR - https://doi.org/10.1007/978-3-662-55327-5_12 SN - 978-3-662-55327-5 SN - 978-3-662-55326-8 SP - 399 EP - 472 PB - Springer Vieweg CY - Berlin ET - 2., erweiterte Auflage ER - TY - JOUR A1 - Wiederer, Julian A1 - Leitner, Lukas A1 - Endisch, Christian A1 - Reiss, Hans T1 - Fast Crank-Angle Based 0D Simulation of Combustion Engine Cold Tests including Manufacturing Faults and Production Spread JF - SAE International Journal of Passenger Cars - Mechanical Systems UR - https://doi.org/10.4271/2016-01-1374 Y1 - 2016 UR - https://doi.org/10.4271/2016-01-1374 SN - 1946-4002 SN - 1946-3995 VL - 9 IS - 1 SP - 321 EP - 335 PB - SAE International CY - Warrendale ER - TY - JOUR A1 - Járdán, Rafael K. A1 - Stumpf, Péter A1 - Varga, Zoltán A1 - Endisch, Christian A1 - Sipos, Péter A1 - Simon, Miklós T1 - Laboratory system for measurement of iron losses in high speed drives JF - International Journal of Hydrogen Energy UR - https://doi.org/10.1016/j.ijhydene.2016.01.061 KW - Electrical machines and drives KW - Permanent magnet machine KW - Loss measurement KW - High speed drives Y1 - 2016 UR - https://doi.org/10.1016/j.ijhydene.2016.01.061 SN - 0360-3199 N1 - Special Issue on 3rd European Conference on Renewable Energy Systems (ECRES′2015), 7–10 October 2015, Kemer, Antalya, Turkey VL - 41 IS - 29 SP - 12650 EP - 12658 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Stolze, Peter A1 - Karamanakos, Petros A1 - Kennel, Ralph A1 - Manias, Stefanos A1 - Endisch, Christian T1 - Effective variable switching point predictive current control for ac low-voltage drives JF - International Journal of Control UR - https://doi.org/10.1080/00207179.2014.942699 KW - model predictive control (MPC) KW - optimal control KW - variable switching point KW - three-level inverter KW - ac low-voltage drives Y1 - 2014 UR - https://doi.org/10.1080/00207179.2014.942699 SN - 0020-7179 SN - 1366-5820 VL - 88 IS - 7 SP - 1366 EP - 1378 PB - Taylor & Francis CY - London ER - TY - CHAP A1 - Okon, Michael A1 - Opferkuch, Johannes A1 - Endisch, Christian T1 - Modular gear transmission model for analyzing production tolerances in electric drivetrains T2 - Proceedings, 2020 IEEE International Conference on Industrial Technology UR - https://doi.org/10.1109/ICIT45562.2020.9067240 KW - electric drivetrain modeling KW - multidomain simulation KW - modular gear transmission model KW - gear mesh dynamics Y1 - 2020 UR - https://doi.org/10.1109/ICIT45562.2020.9067240 SN - 978-1-7281-5754-2 SP - 709 EP - 716 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Gerngroß, Martin A1 - Kohler, Markus A1 - Endisch, Christian A1 - Kennel, Ralph T1 - Model-based control of nonlinear wire tension in dynamic needle winding processes T2 - Proceedings, 2020 IEEE International Conference on Industrial Technology UR - https://doi.org/10.1109/ICIT45562.2020.9067168 Y1 - 2020 UR - https://doi.org/10.1109/ICIT45562.2020.9067168 SN - 978-1-7281-5754-2 SP - 381 EP - 388 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Kleiner, Jan A1 - Komsiyska, Lidiya A1 - Elger, Gordon A1 - Endisch, Christian T1 - Modelling of 3D temperature behavior of prismatic lithium-ion cell with focus on experimental validation under battery electric vehicle conditions T2 - 2019 25th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC) UR - https://doi.org/10.1109/THERMINIC.2019.8923604 Y1 - 2019 UR - https://doi.org/10.1109/THERMINIC.2019.8923604 SN - 978-1-7281-2078-2 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Schneider, Dominik A1 - Endisch, Christian T1 - Robustness and reliability of model-based sensor data fusion in a lithium-ion battery system T2 - IEEE CCTA 2020, 4th IEEE Conference on Control Technology and Applications UR - https://doi.org/10.1109/CCTA41146.2020.9206336 KW - Batteries KW - Robustness KW - Parameter estimation KW - Current measurement KW - Noise measurement KW - Data models KW - Kalman filters Y1 - 2020 UR - https://doi.org/10.1109/CCTA41146.2020.9206336 SN - 978-1-7281-7140-1 SP - 685 EP - 691 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Schneider, Dominik A1 - Liebhart, Bernhard A1 - Endisch, Christian T1 - Adaptive Variance Estimation of Sensor Noise within a Sensor Data Fusion Framework T2 - 2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC 2021) Proceedings UR - https://doi.org/10.1109/I2MTC50364.2021.9459790 Y1 - 2021 UR - https://doi.org/10.1109/I2MTC50364.2021.9459790 SN - 978-1-7281-9539-1 SN - 2642-2077 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Theiler, Michael A1 - Schneider, Dominik A1 - Endisch, Christian T1 - Kalman Filter Tuning Using Multi-Objective Genetic Algorithm for State and Parameter Estimation of Lithium-Ion Cells JF - Batteries N2 - To ensure a reliable and safe operation of battery systems in various applications, the system’s internal states must be observed with high accuracy. Hereby, the Kalman filter is a frequently used and well-known tool to estimate the states and model parameters of a lithium-ion cell. A strong requirement is the selection of a suitable model and a reasonable initialization, otherwise the algorithm’s estimation might be insufficient. Especially the process noise parametrization poses a difficult task, since it is an abstract parameter and often optimized by an arbitrary trial-and-error principle. In this work, a traceable procedure based on the genetic algorithm is introduced to determine the process noise offline considering the estimation error and filter consistency. Hereby, the parameters found are independent of the researcher’s experience. Results are validated with a simulative and experimental study, using an NCA/graphite lithium-ion cell. After the transient phase, the estimation error of the state-of-charge is lower than 0.6% and for internal resistance smaller than 4mΩ while the corresponding estimated covariances fit the error well. UR - https://doi.org/10.3390/batteries8090104 KW - battery model KW - Kalman filter KW - joint estimation KW - Kalman filter tuning KW - genetic algorithm KW - multi-objective optimization Y1 - 2022 UR - https://doi.org/10.3390/batteries8090104 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-29528 SN - 2313-0105 VL - 8 IS - 9 PB - MDPI CY - Basel ER - TY - CHAP A1 - Nachtsheim, Martin A1 - Hartmann, Thomas A1 - Endisch, Christian T1 - Physically Inspired Neural Network for Modeling Induction Machine Nonlinear Magnetic Saturation T2 - ITEC+2022: 2022 IEEE/AIAA Transportation Electrification Conference and Electric Aircraft Technologies Symposium (ITEC+EATS) UR - https://doi.org/10.1109/ITEC53557.2022.9813908 KW - Data-driven modelling KW - neural network KW - system identification KW - magnetic saturation KW - induction machine Y1 - 2022 UR - https://doi.org/10.1109/ITEC53557.2022.9813908 SN - 978-1-6654-0560-7 SP - 874 EP - 881 PB - IEEE CY - Piscataway (NJ) ER - TY - CHAP A1 - Kohler, Markus A1 - Fendt, David A1 - Endisch, Christian T1 - Modeling Geometric Wire Bending Behavior in Needle Winding Processes Using Circular Arcs with Tangential Linear Functions T2 - ITEC+2022: 2022 IEEE/AIAA Transportation Electrification Conference and Electric Aircraft Technologies Symposium (ITEC+EATS) UR - https://doi.org/10.1109/ITEC53557.2022.9814041 KW - wire forming KW - manufacturing KW - production systems KW - digital twin KW - machine learning Y1 - 2022 UR - https://doi.org/10.1109/ITEC53557.2022.9814041 SN - 978-1-6654-0560-7 SP - 894 EP - 901 PB - IEEE CY - Piscataway (NJ) ER - TY - CHAP A1 - Mayer, Sebastian A1 - Höhme, Nikolas A1 - Gankin, Dennis A1 - Endisch, Christian T1 - Adaptive Production Control in a Modular Assembly System – Towards an Agent-based Approach T2 - Proceedings, 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) UR - https://doi.org/10.1109/INDIN41052.2019.8972152 KW - intelligent manufacturing KW - scheduling KW - production control KW - multi-agent system KW - modular assembly system KW - automated guided vehicles Y1 - 2020 UR - https://doi.org/10.1109/INDIN41052.2019.8972152 SN - 978-1-7281-2927-3 SP - 45 EP - 52 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Mayer, Sebastian A1 - Endisch, Christian T1 - Adaptive production control in a modular assembly system based on partial look-ahead scheduling T2 - Proceedings, 2019 IEEE International Conference on Mechatronics (ICM) UR - https://doi.org/10.1109/ICMECH.2019.8722904 KW - scheduling KW - production control KW - production planning KW - modular assembly system KW - automated guided vehicles KW - cyber-physical systems KW - intelligent manufacturing KW - genetic algorithm Y1 - 2019 UR - https://doi.org/10.1109/ICMECH.2019.8722904 SN - 978-1-5386-6959-4 SP - 293 EP - 300 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Herrmann, Patrick A1 - Stenzel, Peer A1 - Vögele, Ulrich A1 - Endisch, Christian T1 - Optimization Algorithms for Maximizing the Slot Filling Factor of Technically Feasible Slot Geometries and Winding Layouts T2 - 2016 6th International Electric Drives Production Conference (E|DPC): Proceedings UR - https://doi.org/10.1109/EDPC.2016.7851327 KW - Slot Filling Factor KW - Optimization Algorithm KW - Slot Geometry KW - Filling Factor Optimization KW - Needle Winding Y1 - 2016 UR - https://doi.org/10.1109/EDPC.2016.7851327 SN - 978-1-5090-2909-9 SN - 978-1-5090-2908-2 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Müller, Tino A1 - Endisch, Christian T1 - Compensation techniques for iterative rig control in multi-axial durability testing T2 - 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA) UR - https://doi.org/10.1109/ETFA.2016.7733517 KW - Testing KW - Inverse problems KW - Load modeling KW - Autoregressive processes KW - Adaptation models KW - Convergence KW - Computational modeling Y1 - 2016 UR - https://doi.org/10.1109/ETFA.2016.7733517 SN - 978-1-5090-1314-2 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Leitner, Lukas A1 - Lagrange, Antoine A1 - Endisch, Christian T1 - End-of-line fault detection for combustion engines using one-class classification T2 - 2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM) UR - https://doi.org/10.1109/AIM.2016.7576768 KW - Training KW - Support vector machines KW - Tuning KW - Engines KW - Kernel KW - Production KW - Testing Y1 - 2016 UR - https://doi.org/10.1109/AIM.2016.7576768 SN - 978-1-5090-2065-2 SP - 207 EP - 213 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Leitner, Lukas A1 - Endisch, Christian T1 - Skewed and Heavy-Tailed Hidden Random Walk Models with Applications in Automated Production Testing T2 - 2018 IEEE 22nd International Conference on Intelligent Engineering Systems (INES) UR - https://doi.org/10.1109/INES.2018.8523927 Y1 - 2018 UR - https://doi.org/10.1109/INES.2018.8523927 SN - 978-1-5386-1122-7 SP - 000281 EP - 000286 PB - IEEE CY - Piscataway ER -