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 - 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 - TY - CHAP A1 - Ziegmann, Johannes A1 - Schmid, Michael A1 - Endisch, Christian T1 - Sensitivity Analysis for Driver Energy Prediction with Environmental Features and Naturalistic Data T2 - 2018 IEEE International Conference on Intelligent Engineering Systems (INES) UR - https://doi.org/10.1109/INES.2018.8523987 KW - Driver Energy Prediction KW - Environmental Feature Selection KW - Sensitivity Analysis KW - Feature Transformation KW - Filter and Wrapper Methods Y1 - 2018 UR - https://doi.org/10.1109/INES.2018.8523987 SN - 978-1-5386-1122-7 SP - 000199 EP - 000206 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Herrmann, Patrick A1 - Gerngroß, Martin A1 - Endisch, Christian T1 - Numerical Optimization in Planning of Flexible Needle Winding Trajectories T2 - 2018 IEEE International Conference on Intelligent Engineering Systems (INES) UR - https://doi.org/10.1109/INES.2018.8523924 KW - Windings KW - Wires KW - Trajectory KW - Optimization KW - Splines (mathematics) KW - Needles KW - Stators Y1 - 2018 UR - https://doi.org/10.1109/INES.2018.8523924 SN - 978-1-5386-1122-7 SP - 000255 EP - 000260 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Altmannshofer, Simon A1 - Endisch, Christian A1 - Trieu, Khanh Duy T1 - On-line identification and identifiability analysis of electrical and mechanical parameters of induction machines T2 - 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM) UR - https://doi.org/10.1109/AIM.2017.8014079 KW - Rotors KW - Estimation KW - Induction machines KW - Stators KW - Eigenvalues and eigenfunctions KW - Mathematical model KW - Inductance Y1 - 2017 UR - https://doi.org/10.1109/AIM.2017.8014079 SN - 978-1-5090-6000-9 SN - 2159-6255 SP - 577 EP - 583 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Müller, Tino A1 - Endisch, Christian T1 - An estimation based iterative learning control approach for cross-coupled vehicle test systems T2 - 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM) UR - https://doi.org/10.1109/AIM.2017.8014210 KW - Convergence KW - Testing KW - Control systems KW - Estimation KW - Iterative learning control KW - Load modeling KW - Adaptation models Y1 - 2017 UR - https://doi.org/10.1109/AIM.2017.8014210 SN - 978-1-5090-6000-9 SN - 978-1-5090-5998-0 SN - 2159-6255 SP - 1375 EP - 1381 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Ziegmann, Johannes A1 - Shi, Jieqing A1 - Schnörer, Tobias A1 - Endisch, Christian T1 - Analysis of individual driver velocity prediction using data-driven driver models with environmental features T2 - 2017 IEEE Intelligent Vehicles Symposium UR - https://doi.org/10.1109/IVS.2017.7995770 KW - vehicles KW - predictive models KW - training KW - prediction algorithms KW - kernel KW - navigation KW - biological system modeling Y1 - 2017 UR - https://doi.org/10.1109/IVS.2017.7995770 SN - 978-1-5090-4804-5 SP - 517 EP - 522 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Vögele, Ulrich A1 - Ziegmann, Johannes A1 - Endisch, Christian T1 - Driver adaptive predictive velocity control T2 - 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC.2017.8317668 KW - Predictive Velocity Control KW - Longitudinal Vehicle Control KW - Driver Adpative KW - Multi-Criteria Optimization Y1 - 2017 UR - https://doi.org/10.1109/ITSC.2017.8317668 SN - 978-1-5386-1526-3 SN - 2153-0017 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Herrmann, Patrick A1 - Gerngroß, Martin A1 - Endisch, Christian A1 - Stenzel, Peer A1 - Uhlmann, Philipp T1 - Automated contacting technology for needle winding applications with distributed windings T2 - 2017 7th International Electric Drives Production Conference (EDPC) Proceedings UR - https://doi.org/10.1109/EDPC.2017.8328169 KW - Contacting Technology KW - Joining Technology KW - Automation KW - Resistance Welding KW - Distributed Winding KW - Needle Winding Y1 - 2017 UR - https://doi.org/10.1109/EDPC.2017.8328169 SN - 978-1-5386-1069-5 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Herrmann, Patrick A1 - Gerngroß, Martin A1 - Endisch, Christian T1 - NURBS based trajectory generation for an industrial five axis needle winding robot T2 - Conference Proceedings of 2018 4th International Conference on Control, Automation and Robotics (ICCAR) UR - https://doi.org/10.1109/ICCAR.2018.8384640 KW - needle winding KW - trajectory planning KW - constant feed rate KW - NURBS KW - smooth path planning Y1 - 2018 UR - https://doi.org/10.1109/ICCAR.2018.8384640 SN - 978-1-5386-6338-7 SP - 31 EP - 36 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Leitner, Lukas A1 - Endisch, Christian T1 - Robust stochastic process models and parameter estimation for industrial end-of-line-testing T2 - Proceedings: 2018 IEEE International Conference on Industrial Technology (ICIT) UR - https://doi.org/10.1109/ICIT.2018.8352406 KW - Testing KW - Robustness KW - Production KW - Stochastic processes KW - Feature extraction KW - Training KW - Current measurement Y1 - 2018 UR - https://doi.org/10.1109/ICIT.2018.8352406 SN - 978-1-5090-5949-2 SP - 1520 EP - 1525 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Liebhart, Bernhard A1 - Diehl, Simon A1 - Schneider, Dominik A1 - Endisch, Christian A1 - Kennel, Ralph T1 - Enhancing the Cell Impedance Estimation of a Lithium-Ion Battery System with Embedded Power Path Switches T2 - APEC 2021: Thirty-Sixth Annual IEEE Applied Power Electronics Conference and Exposition UR - https://doi.org/10.1109/APEC42165.2021.9487173 KW - Reconfigurable Battery System KW - Impedance Spectroscopy KW - Power MOSFET KW - Pseudorandom Binary Sequence Y1 - 2021 UR - https://doi.org/10.1109/APEC42165.2021.9487173 SN - 978-1-7281-8949-9 SN - 2470-6647 SP - 967 EP - 974 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Kleiner, Jan A1 - Heider, Alexander A1 - Komsiyska, Lidiya A1 - Elger, Gordon A1 - Endisch, Christian T1 - Experimental Study on the Thermal Interactions in Novel Intelligent Lithium-Ion Modules for Electric Vehicles T2 - Proceedings of the Twentieth InterSociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems: ITherm 2021 UR - https://doi.org/10.1109/ITherm51669.2021.9503299 KW - Intelligent battery KW - Lithium-ion KW - Reconfiguration KW - Cooling KW - Thermal management KW - Parallel connection Y1 - 2021 UR - https://doi.org/10.1109/ITherm51669.2021.9503299 SN - 978-1-7281-8539-2 SN - 2694-2135 SP - 556 EP - 562 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Liebhart, Bernhard A1 - Diehl, Simon A1 - Schmid, Michael A1 - Endisch, Christian A1 - Kennel, Ralph T1 - Improved Impedance Measurements for Electric Vehicles with Reconfigurable Battery Systems T2 - Proceedings of the Energy Conversion Congress and Exposition – Asia, 2021 (ECCE Asia 2021) UR - https://doi.org/10.1109/ECCE-Asia49820.2021.9479060 KW - Reconfigurable Battery System KW - Impedance Spectroscopy KW - Power MOSFET KW - Artificial Neural Network Y1 - 2021 UR - https://doi.org/10.1109/ECCE-Asia49820.2021.9479060 SN - 978-1-7281-6344-4 SN - 2150-6086 SP - 1736 EP - 1742 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Herrmann, Patrick A1 - Gerngroß, Martin A1 - Endisch, Christian T1 - Benefits of numerical optimization and CAD/CAM in needle winding processes T2 - Proceedings, 2019 IEEE International Conference on Mechatronics (ICM) UR - https://doi.org/10.1109/ICMECH.2019.8722940 KW - needle winding technology KW - trajectory planning KW - automated trajectory generation KW - CAD/CAM KW - numerical optimization Y1 - 2019 UR - https://doi.org/10.1109/ICMECH.2019.8722940 SN - 978-1-5386-6959-4 SP - 301 EP - 307 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Okon, Michael A1 - Endisch, Christian T1 - On air-gap approximations for slotted electrical machine models assuming radial magnetic fields T2 - Proceedings, 2019 IEEE International Conference on Industrial Technology (ICIT) UR - https://doi.org/10.1109/ICIT.2019.8755196 KW - electrical machine modeling KW - radial air-gap magnetic field KW - magnetically effective air-gap KW - slotting effects Y1 - 2019 UR - https://doi.org/10.1109/ICIT.2019.8755196 SN - 978-1-5386-6376-9 SP - 292 EP - 297 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Gerngroß, Martin A1 - Herrmann, Patrick A1 - Endisch, Christian T1 - Nonlinear modelling of dynamic wire tension for needle winding processes of distributed windings T2 - Proceedings, 2019 IEEE International Conference on Industrial Technology (ICIT) UR - https://doi.org/10.1109/ICIT.2019.8755052 Y1 - 2019 UR - https://doi.org/10.1109/ICIT.2019.8755052 SN - 978-1-5386-6376-9 SP - 151 EP - 156 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Kohler, Markus A1 - Gerngroß, Martin A1 - Endisch, Christian T1 - A Test Bench Concept and Method for Image-Based Modeling of Geometric Wire Bending Behavior in Needle Winding Processes T2 - 2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) UR - https://doi.org/10.1109/ISIE51582.2022.9831494 KW - wire forming KW - manufacturing KW - computer vision KW - machine vision KW - image processing KW - curve fitting KW - splines Y1 - 2022 UR - https://doi.org/10.1109/ISIE51582.2022.9831494 SN - 978-1-6654-8240-0 SN - 2163-5145 SP - 1113 EP - 1120 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Nachtsheim, Martin A1 - Korkmaz, Luetfue A1 - Schmoelz, Martin A1 - Endisch, Christian T1 - Observability Analysis for Parameter Identification of Induction Machines in Automotive Environment T2 - 2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) UR - https://doi.org/10.1109/ISIE51582.2022.9831658 KW - observability KW - induction machine KW - parameter identification KW - extended Kalman Filter Y1 - 2022 UR - https://doi.org/10.1109/ISIE51582.2022.9831658 SN - 978-1-6654-8240-0 SN - 2163-5145 SP - 206 EP - 213 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Stöttner, Julia A1 - Rauscher, Andreas A1 - Endisch, Christian T1 - Pareto optimization of multilevel inverter structures regarding the DC magnitude, switching frequency and switching angles JF - International Journal of Electrical Power & Energy Systems UR - https://doi.org/10.1016/j.ijepes.2022.108259 KW - Cascaded H-bridge (CHB) KW - Electric vehicle (EV) KW - Multilevel inverter (MLI) KW - Pareto optimization (PO) Y1 - 2022 UR - https://doi.org/10.1016/j.ijepes.2022.108259 SN - 0142-0615 VL - 2022 IS - 142, Part A PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Terbrack, Christoph A1 - Stöttner, Julia A1 - Endisch, Christian T1 - Design and Validation of the Parallel Enhanced Commutation Integrated Nested Multilevel Inverter Topology JF - IEEE Transactions on Power Electronics UR - https://doi.org/10.1109/TPEL.2022.3183859 KW - drivetrain KW - enhanced commutation integrated nested (ECIN) KW - electric vehicles KW - modular multilevel converter (MMLC) KW - parallel enhanced commutation integrated nested (PECIN) KW - power electronics Y1 - 2022 UR - https://doi.org/10.1109/TPEL.2022.3183859 SN - 1941-0107 VL - 37 IS - 12 SP - 15163 EP - 15174 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Rauscher, Andreas A1 - Hufnagel, Manuel A1 - Endisch, Christian T1 - Pareto optimization of wavelet filter design for partial discharge detection in electrical machines JF - Measurement N2 - A reliable detection of partial discharges (PDs) in the insulation system of electrical machines is essential to prevent premature breakdowns. Wavelet filters (WFs) are often recommended for denoising this PD measurement data. However, filtering performance strongly depends on numerous settings, which impedes an optimum filter choice. We propose an approach to systematically select the best filter for denoising PD signals. First, representative PD pulses are determined from measurement data by an averaging and a singular value decomposition method. Next, realistic benchmark signals are generated for filter assessment. Further, all possible WF combinations from a set of different mother wavelet selection methods, decomposition trees, and thresholding approaches are evaluated. On the basis of two contradicting objectives, namely mean square error of noise intervals and pulse amplitude distortion, Pareto optimization is applied to choose optimal WF settings. The corresponding filters dominate several common WF proposals from previous literature. UR - https://doi.org/10.1016/j.measurement.2022.112163 KW - Pareto optimization KW - Wavelet filter KW - Denoising KW - Ultra high frequency KW - Partial discharge KW - Electrical machine Y1 - 2022 UR - https://doi.org/10.1016/j.measurement.2022.112163 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-30673 SN - 1873-412X SN - 0263-2241 VL - 2022 IS - 205 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kleiner, Jan A1 - Lambauer, Florian A1 - Singh, Randeep A1 - Komsiyska, Lidiya A1 - Hinterberger, Michael A1 - Endisch, Christian T1 - Experimental study of cell integrated heat pipe cooling with a lithium-ion cell emulator JF - Journal of Energy Storage UR - https://doi.org/10.1016/j.est.2022.105808 Y1 - 2022 UR - https://doi.org/10.1016/j.est.2022.105808 SN - 2352-1538 SN - 2352-152X VL - 2022 IS - 56, Part A PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Schmid, Michael A1 - Liebhart, Bernhard A1 - Kleiner, Jan A1 - Endisch, Christian A1 - Kennel, Ralph T1 - Online Detection of Soft Internal Short Circuits in Lithium-Ion Battery Packs by Data-Driven Cell Voltage Monitoring T2 - Proceedings of the Energy Conversion Congress & Exposition - Asia, 2021 (ECCE-Asia 2021) UR - https://doi.org/10.1109/ECCE-Asia49820.2021.9479175 KW - Internal Short Circuit KW - Fault Diagnosis KW - Lithium-Ion Battery KW - Battery Safety KW - Electric Vehicle Y1 - 2021 UR - https://doi.org/10.1109/ECCE-Asia49820.2021.9479175 SN - 978-1-7281-6344-4 SN - 2150-6086 SP - 1711 EP - 1718 PB - IEEE CY - Piscataway (NJ) ER - TY - JOUR A1 - Morales Torricos, Pablo A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Apparent Aging during Accelerated Cycling Aging Test of Cylindrical Silicon Containing Li-Ion Cells JF - Batteries N2 - Accelerated cyclic aging tests are very important for research and industry to quickly characterize lithium-ion cells. However, the accentuation of stress factors and the elimination of rest periods lead to an apparent capacity fade, that can be subsequently recovered during a resting phase. This effect is attributed to the inhomogeneous lithium distribution in the anode and is observable with differential voltage analysis (DVA). We tested cylindrical 18,650 cells with Li(NixCoyAlz)O2-graphite/silicon chemistry during two cycling and resting phases. The capacity, the pulse resistance, the DVA, and the capacity difference analysis are evaluated for cells cycled at different average SOC and current rates. An apparent capacity loss of up to 12% was reported after 200 FCE for cells cycled under the presence of pressure gradients, while only 1% were at low-pressure gradients. The subsequent recovery was up to 80% of the apparent capacity loss in some cases. The impact of silicon cannot be estimated as it shows no features in the dV/dQ curves. We observe a recovery of apparent resistance increase, which is not reported for cells with pure graphite anodes. Finally, we demonstrate the strong impact of apparent aging for the lifetime prediction based on standard accelerated cyclic aging tests. UR - https://doi.org/10.3390/batteries9040230 KW - aging KW - lifetime prognosis KW - cycle life KW - NCA KW - silicon KW - mechanical stress KW - homogeneity of lithium distribution KW - capacity recovery Y1 - 2023 UR - https://doi.org/10.3390/batteries9040230 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-35477 SN - 2313-0105 VL - 9 IS - 4 PB - MDPI CY - Basel ER - TY - JOUR A1 - Lechermann, Lorenz A1 - Kleiner, Jan A1 - Komsiyska, Lidiya A1 - Hinterberger, Michael A1 - Endisch, Christian T1 - A comparative study of data-driven electro-thermal models for reconfigurable lithium-ion batteries in real-time applications JF - Journal of Energy Storage UR - https://doi.org/10.1016/j.est.2023.107188 Y1 - 2023 UR - https://doi.org/10.1016/j.est.2023.107188 SN - 2352-1538 SN - 2352-152X VL - 2023 IS - 65 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Terbrack, Christoph A1 - Speer, Sascha A1 - Endisch, Christian T1 - Control and Implementation of the Parallel Enhanced Commutation Integrated Nested Multilevel Inverter Topology JF - Electronics N2 - Due to their high efficiency and advanced battery management capability, cascaded multilevel inverters are an exciting option for battery electric powertrains. A promising, new and highly efficient cascaded multilevel inverter is the Parallel Enhanced Commutation Integrated Nested Multilevel Inverter. The inverter, with four semiconductor switches per submodule, can reconfigure individual battery cells in series and parallel and generate positive and negative phase voltages in regular four-quadrant operation. Therefore, emerging degrees of freedom in battery management and inverter operation must be managed and mapped into a specific Switching State for every switch. As controlling the high number of switches is safety-relevant, this publication profoundly explains the inverter’s functionality. We introduce a Switching Function that accepts easy-to-understand functional states as input, simplifying research on higher-level control algorithms and advanced single-cell battery-management capabilities. As the Switching Function guarantees safe operation and the correct contribution of every cell to the overall functionality of the inverter, it enables researchers to confidently use and thereby accelerate research on the promising new topology. The method we describe is fast, simple, deterministic and designed to convert setpoint specifications into an executable Switching Pattern. We prove that our Switching Function is operable on an FPGA with a twenty-kilohertz setpoint update operating a 17-level inverter. UR - https://doi.org/10.3390/electronics12143130 KW - cascaded KW - drivetrain KW - electric vehicles KW - MLI KW - PECIN KW - power electronics KW - reconfigurable battery system KW - Switching Function Y1 - 2023 UR - https://doi.org/10.3390/electronics12143130 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-37990 SN - 2079-9292 VL - 12 IS - 14 PB - MDPI CY - Basel ER - TY - CHAP A1 - Nachtsheim, Martin A1 - Grund, Karina A1 - Endisch, Christian A1 - Kennel, Ralph T1 - Online Identification of Induction Machine Parameter Deviations for Aging Detection - A Comparative Study Using Recursive Least Squares Algorithm and Extended Kalman Filter T2 - 2023 IEEE Transportation Electrification Conference & Expo (ITEC) UR - https://doi.org/10.1109/ITEC55900.2023.10186964 KW - Induction Machine KW - Online Parameter Identification KW - Extended Kalman Filter KW - Recursive Least Squares Algorithm KW - Aging Detection Y1 - 2023 UR - https://doi.org/10.1109/ITEC55900.2023.10186964 SN - 979-8-3503-9742-0 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Azzam, Mohamed A1 - Ehrensberger, Moritz A1 - Scheuer, Reinhard A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Long-Term Self-Discharge Measurements and Modelling for Various Cell Types and Cell Potentials JF - Energies N2 - Self-discharge of lithium-ion cells leads to voltage decay over time. In this work, the self-discharge was measured at 30 °C for three cell types at various voltage levels for about 150 days in a constant voltage mode determining the current at a high precision (float current). All cells exhibit a transient part leading to a steady-state, which is no longer influenced by reversible effects. To study the effect of the check-ups on the steady-state float current, the cells, interrupted and not interrupted by check-ups, were compared. The results indicate that both the transient processes and steady-state currents are highly reproducible. In the first period of the float current, the polarization dominates the measured current, followed by the anode overhang effect dominating the process for a period of 5–30 days. After the decline of both processes, a mostly constant steady-state in the order of µA is observed. The check-up interruption generally shows no apparent effect on the reached steady-state and results only in an extended settling time. A model to simulate the transient process and steady-state of float currents was developed. The model shows a high accuracy in reproducing the results and identifying the time needed to reach the steady-state. UR - https://doi.org/10.3390/en16093889 KW - 18650 KW - NCA KW - NMC KW - LFP KW - graphite KW - float current analysis KW - potentiostatic hold KW - self-discharge rate KW - modelling KW - filtering KW - anode overhang Y1 - 2023 UR - https://doi.org/10.3390/en16093889 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-36693 SN - 1996-1073 VL - 16 IS - 9 PB - MDPI CY - Basel ER - TY - CHAP A1 - Terbrack, Christoph A1 - Stöttner, Julia A1 - Endisch, Christian T1 - Operation of an externally excited synchronous machine with a hybrid multilevel inverter T2 - 2020 22nd European Conference on Power Electronics and Applications (EPE'20 ECCE Europe) UR - https://doi.org/10.23919/EPE20ECCEEurope43536.2020.9215895 KW - AC machine KW - Batteries KW - Converter circuit KW - Electrical drive KW - Electrical machine KW - High voltage power converters KW - Multilevel converters KW - Power converters for EV KW - Synchronous motor Y1 - 2020 UR - https://doi.org/10.23919/EPE20ECCEEurope43536.2020.9215895 SN - 978-9-0758-1536-8 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Liebhart, Bernhard A1 - Diehl, Simon A1 - Endisch, Christian T1 - Sensitivity analysis of battery cell aging estimators based on impedance spectroscopy regarding temperature compensation T2 - IEEE CCTA 2020, 4th IEEE Conference on Control Technology and Applications UR - https://doi.org/10.1109/CCTA41146.2020.9206395 KW - sensitivity analysis KW - impedance spectroscopy KW - temperature compensation KW - battery management systems KW - multiple lithium-ion cells KW - battery cell aging estimators KW - on board electric vehicles Y1 - 2020 UR - https://doi.org/10.1109/CCTA41146.2020.9206395 SN - 978-1-7281-7140-1 SP - 699 EP - 705 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Müller, Tino A1 - Vögele, Ulrich A1 - Endisch, Christian T1 - Disturbance compensation for iterative control of suspension durability test rigs T2 - 2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM) UR - https://doi.org/10.1109/AIM.2016.7577011 KW - testing KW - predictive models KW - vehicles KW - axles KW - inverse problems KW - actuators KW - optimal control Y1 - 2016 UR - https://doi.org/10.1109/AIM.2016.7577011 SN - 978-1-5090-2065-2 SP - 1675 EP - 1681 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Müller, Tino A1 - Ziegmann, Johannes A1 - Krüner, Simon A1 - Endisch, Christian T1 - Optimization of inverse model identification for multi-axial test rig control JF - MATEC Web of Conferences N2 - Laboratory testing of multi-axial fatigue situations improves repeatability and allows a time condensing of tests which can be carried out until component failure, compared to field testing. To achieve realistic and convincing durability results, precise load data reconstruction is necessary. Cross-talk and a high number of degrees of freedom negatively affect the control accuracy. Therefore a multiple input/multiple output (MIMO) model of the system, capturing all inherent cross-couplings is identified. In a first step the model order is estimated based on the physical fundamentals of a one channel hydraulic-servo system. Subsequently, the structure of the MIMO model is optimized using correlation of the outputs, to increase control stability and reduce complexity of the parameter optimization. The identification process is successfully applied to the iterative control of a multi-axial suspension rig. The results show accurate control, with increased stability compared to control without structure optimization. UR - https://doi.org/10.1051/matecconf/20164201002 Y1 - 2016 UR - https://doi.org/10.1051/matecconf/20164201002 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-16314 SN - 2261-236X VL - 2016 IS - 42 PB - EDP Sciences CY - Les Ulis ER - TY - CHAP A1 - Altmannshofer, Simon A1 - Endisch, Christian A1 - Martin, Jan A1 - Gerngroß, Martin A1 - Limbacher, Reimund T1 - Robust estimation of vehicle longitudinal dynamics parameters T2 - 2016 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/IVS.2016.7535443 KW - vehicles KW - brakes KW - estimation KW - resistance KW - robustness KW - vehicle dynamics KW - friction Y1 - 2016 UR - https://doi.org/10.1109/IVS.2016.7535443 SN - 978-1-5090-1821-5 SP - 566 EP - 571 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Altmannshofer, Simon A1 - Endisch, Christian T1 - Robust Vehicle Mass and Driving Resistance Estimation T2 - 2016 American Control Conference (ACC) UR - https://doi.org/10.1109/ACC.2016.7526754 KW - parameter estimation KW - vehicle dynamics Y1 - 2016 UR - https://doi.org/10.1109/ACC.2016.7526754 SN - 978-1-4673-8682-1 SN - 2378-5861 SP - 6869 EP - 6874 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Vögele, Ulrich A1 - Endisch, Christian T1 - Potential analysis of predictive optimal velocity control for electric and conventional vehicles T2 - 2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES) UR - https://doi.org/10.1109/ICVES.2015.7396917 KW - Dynamic Programming KW - Deterministic Discrete Systems KW - Electric Mobility KW - Vehicle Fuel Consumption Reduction KW - Ford-Bellman KW - Dijkstra KW - Shortest-Path KW - Directed Acyclic Graphs Y1 - 2015 UR - https://doi.org/10.1109/ICVES.2015.7396917 SN - 978-1-4673-9114-6 SP - 196 EP - 201 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Martin, Jan A1 - Vögele, Ulrich A1 - Endisch, Christian T1 - Effects of errors in position- and navigation data on predictive vehicle operational strategy optimization T2 - 2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES) UR - https://doi.org/10.1109/ICVES.2015.7396916 KW - car technologies KW - predictive operational strategy KW - look-ahead data KW - optimization Y1 - 2015 UR - https://doi.org/10.1109/ICVES.2015.7396916 SN - 978-1-4673-9114-6 SP - 190 EP - 195 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Járdán, Rafael K. A1 - Varga, Zoltán A1 - Stumpf, Péter A1 - Nagy, Istvan A1 - Endisch, Christian A1 - Sipos, Péter A1 - Simon, Miklós T1 - Development of a Dedicated Laboratory System for Measurement of Iron Losses in High Speed PMSM T2 - 2015 IEEE International Conference on Industrial Technology (ICIT) UR - https://doi.org/10.1109/ICIT.2015.7125181 KW - Permanent magnet machine KW - Loss measurement KW - High speed drives Y1 - 2015 UR - https://doi.org/10.1109/ICIT.2015.7125181 SN - 978-1-4799-7800-7 SP - 708 EP - 713 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Stenzel, Peer A1 - Dollinger, P. A1 - Richnow, Jan A1 - Bader, T. A1 - Franke, Jörg A1 - Endisch, Christian T1 - Experimental investigations of the needle winding technology regarding the influence of the wire guide geometry on the tensile wire force T2 - 2015 IEEE International Conference on Industrial Technology (ICIT) UR - https://doi.org/10.1109/ICIT.2015.7125487 Y1 - 2015 UR - https://doi.org/10.1109/ICIT.2015.7125487 SN - 978-1-4799-7800-7 SP - 2642 EP - 2649 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Nachtsheim, Martin A1 - Betz, Michael A1 - Endisch, Christian T1 - Explicit analytical approach for electromagnetic modeling of arbitrary pole pair induction machines T2 - 2022 12th International Conference on Power, Energy and Electrical Engineering (CPEEE) UR - https://doi.org/10.1109/CPEEE54404.2022.9738660 KW - induction machine KW - induction motor KW - analytical model KW - magnetic saturation KW - iron losses Y1 - 2022 UR - https://doi.org/10.1109/CPEEE54404.2022.9738660 SN - 978-1-6654-2049-5 SP - 41 EP - 48 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Schneider, Dominik A1 - Liebhart, Bernhard A1 - Endisch, Christian A1 - Kennel, Ralph T1 - Enhanced state and parameter estimation within reconfigurable battery systems for electric vehicles T2 - 2022 12th International Conference on Power, Energy and Electrical Engineering (CPEEE) UR - https://doi.org/10.1109/CPEEE54404.2022.9738700 KW - state estimation KW - battery management system KW - reconfigurable battery systems KW - power electronics Y1 - 2022 UR - https://doi.org/10.1109/CPEEE54404.2022.9738700 SN - 978-1-6654-2049-5 SP - 71 EP - 77 PB - IEEE CY - Piscataway, NJ ER - TY - JOUR A1 - Theiler, Michael A1 - Schneider, Dominik A1 - Endisch, Christian T1 - Experimental Investigation of State and Parameter Estimation within Reconfigurable Battery Systems JF - Batteries N2 - The battery system is one of the most-important, but also -critical components in the electric power-train. The battery’s system states and parameters are commonly tracked by the battery monitoring system. However, in reality, the accuracy of the state and parameter estimation may suffer from insufficient excitation of the system. Since the current states and parameters serve as the basis for many battery management system functions, this might lead to incorrect operation and severe damage. Reconfigurable battery systems allow enhancing the system’s excitation by applying a switching operation. In this contribution, the state and parameter estimation of a reconfigurable battery module were simulated and tested experimentally. Thereby, a low-exciting and a high-exciting drive cycle were compared. Furthermore, the switching patterns were applied to enhance the excitation and, hence, improve the estimation of an extended Kalman filter. The cells were switched via a pulse-width modulation signal, and the influence of frequency and duty cycle variation on the estimation accuracy were investigated. Compared to the low-excitation input, a significant improvement in the estimation of up to 46% for the state of charge and 78% for the internal resistance were achieved. Hereby, low frequencies and duty cycles proved to be particularly advantageous. Switching, however, has only a limited influence on an already highly excited system and may lead to additional aging due to higher heat generation. UR - https://doi.org/10.3390/batteries9030145 KW - battery model KW - Kalman filter KW - joint estimation KW - reconfigurable battery systems KW - state estimation KW - parameter estimation Y1 - 2023 UR - https://doi.org/10.3390/batteries9030145 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-31110 SN - 2313-0105 VL - 9 IS - 3 PB - MDPI CY - Basel ER - TY - JOUR A1 - Nachtsheim, Martin A1 - Ernst, Johannes A1 - Endisch, Christian A1 - Kennel, Ralph T1 - Performance of Recursive Least Squares Algorithm Configurations for Online Parameter Identification of Induction Machines in an Automotive Environment JF - IEEE Transactions on Transportation Electrification UR - https://doi.org/10.1109/TTE.2023.3244619 KW - parameter estimation KW - induction machine KW - power system identification KW - road vehicle electric propulsion KW - fault diagnosis Y1 - 2023 UR - https://doi.org/10.1109/TTE.2023.3244619 SN - 2332-7782 VL - 9 IS - 3 SP - 4236 EP - 4254 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Rauscher, Andreas A1 - Kalamkar, Siddhanth A1 - Endisch, Christian T1 - Impact of High Voltage Waveform on Partial Discharge Inception in Electrical Machines T2 - 2024 IEEE 33rd International Symposium on Industrial Electronics (ISIE), Proceedings UR - https://doi.org/10.1109/ISIE54533.2024.10595712 Y1 - 2024 UR - https://doi.org/10.1109/ISIE54533.2024.10595712 SN - 979-8-3503-9408-5 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Azzam, Mohamed A1 - Ehrensberger, Moritz A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Accelerating float current measurement with temperature ramps revealing entropy insights JF - Journal of Energy Storage UR - https://doi.org/10.1016/j.est.2024.114142 Y1 - 2024 UR - https://doi.org/10.1016/j.est.2024.114142 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-52253 SN - 2352-1538 VL - 2024 IS - 102, Part B PB - Elsevier CY - Science ER - TY - JOUR A1 - Rauscher, Andreas A1 - Kaiser, Johannes A1 - Devaraju, Manoj A1 - Endisch, Christian T1 - Deep learning and data augmentation for partial discharge detection in electrical machines JF - Engineering Applications of Artificial Intelligence N2 - Fault testing in the production line of automotive traction machines is essential to ensure the desired lifetime. Since repetitive partial discharges (PDs) caused by anomalies in the insulation system lead to premature breakdowns of electrical machines, a reliable PD detection is of great importance. This paper proposes deep learning (DL) methods to improve the discrimination of PD from background noise in comparison with the state-of-the-art amplitude based PD detection in the production line. First, a systematic data extraction and labeling procedure is introduced to obtain correctly labeled datasets from arbitrary PD measurements. In addition, datasets are enhanced with low signal-to-noise ratio PD pulses by applying a special data augmentation approach. 13 different convolutional, recurrent and fully connected neural networks are compared for various time-frequency representations of the input signals. Hyperparameters for input transform, network topology and solver are optimized for all 13 combinations to ensure a fair case study. As a result, the two-dimensional convolutional neural network with continuous wavelet transform achieves the best accuracy of around 99.76% on a test dataset of PD signals originating from previously not utilized test objects. All DL models considered in this comparison outperform the state-of-the-art threshold-based PD classification. Even for PD events with an amplitude close to the noise level, the detection rate is still around 95% for the best network. Furthermore, without applying the proposed data augmentation procedure, the DL models investigated are not able to distinguish small PD pulses from noise. UR - https://doi.org/10.1016/j.engappai.2024.108074 Y1 - 2024 UR - https://doi.org/10.1016/j.engappai.2024.108074 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-45384 SN - 1873-6769 SN - 0952-1976 VL - 133 IS - Part A PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Theiler, Michael A1 - Baumann, Alexander A1 - Endisch, Christian T1 - Influence of inhomogeneous state of charge distributions on thermal runaway propagation in lithium-ion batteries JF - Journal of Energy Storage N2 - It is well known that lithium-ion batteries pose a certain safety risk. The thermal runaway of a cell and the subsequent thermal propagation through the battery are considered particularly dangerous. Effective solutions for their mitigation are therefore of great interest. Previous studies have shown the significant influence of a cell’s state of charge (SOC) on its behavior during thermal runaway. This relation may be exploitable in a battery pack to improve its safety. This study aims to assess the leverage of active SOC reduction in the imminent threat of thermal runaway. Implementing such a technique could become feasible with the emergence of reconfigurable battery systems. Four experiments were conducted, each with a module of three fresh 63 Ah high energy pouch cells in a spring-loaded bracing. The experiments studied different stationary SOC configurations, uniform (100% and 60%) and non-uniform (100%–60%–100% and 100%–20%–100%). The results indicate that thermal propagation is substantially delay (87 s) by discharging a cell in its path. The SOC reduction primarily decreases the maximum temperature of the respective cell. Further effects are a calmer thermal runaway and prolonged propagation time within the cell as well as to the next cell. In comparison, the SOC reduction has little impact on the cell’s own triggering time, as the triggering time is mainly determined by the thermal energy transferred from the preceding cell and hence by its SOC. Furthermore, the analysis of the experimental data (temperature, voltage, pressure, video) gives insights into the propagation of thermal runaway through the individual layers of a cell. With reference to the position of a cell relative to the origin of the thermal propagation, a decrease of its mass loss and an increase of its internal propagation time is observed. This effect is attributed to the decreasing module pressure due to progressive loss of material. The assessment shows that active SOC reduction techniques have great leverage for mitigating or even stopping thermal propagation in a battery pack. UR - https://doi.org/10.1016/j.est.2024.112483 Y1 - 2024 UR - https://doi.org/10.1016/j.est.2024.112483 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-47952 VL - 2024 IS - 95 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Azzam, Mohamed A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Evaluating the Aging-Induced Voltage Slippery as Cause for Float Currents of Lithium-ion Cells JF - Batteries N2 - This paper provides a comprehensive exploration of float current analysis in lithium-ion batteries, a promising new testing method to assess calendar aging. Float currents are defined as the steady-state trickle charge current after a transient part. In the literature, a correlation to capacity loss was reported. Assuming the float current compensates for the voltage decay over time and is linked to calendar aging, effects from voltage slippery must be considered. The dU/dQ analysis suggests solely a loss of active lithium. Therefore, we investigate the solid electrolyte interphase (SEI) growth as the general aging mechanism to explain the origin of float currents. Our results show that the voltage slippery theory holds true within the low to middle test voltage ranges. However, the theory’s explanatory power begins to diminish at higher voltage ranges, suggesting the existence of additional, yet unidentified, factors influencing the float current. A shuttle reaction or lithiation of the cathode by electrolyte decomposition are the most promising alternative aging mechanisms at high voltages. The paper proposes a unique voltage slippery model to check for correlations between aging mechanisms, the float current test and the check-up test. For a better understanding, test strategies are proposed to verify/falsify the aging mechanisms beyond SEI. UR - https://doi.org/10.3390/batteries10010003 Y1 - 2023 UR - https://doi.org/10.3390/batteries10010003 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-43157 SN - 2313-0105 VL - 10 IS - 1 PB - MDPI CY - Basel ER - TY - CHAP A1 - Rauscher, Andreas A1 - Stenzel, Peer A1 - Endisch, Christian T1 - Optimization of Sensor Setup and Filter Frequency for End-of-Line Partial Discharge Testing of Electrical Machines T2 - 2024 IEEE International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC) UR - https://doi.org/10.1109/ESARS-ITEC60450.2024.10819886 Y1 - 2024 UR - https://doi.org/10.1109/ESARS-ITEC60450.2024.10819886 SN - 979-8-3503-7390-5 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Azzam, Mohamed A1 - Ehrensberger, Moritz A1 - Endisch, Christian A1 - Sauer, Dirk Uwe A1 - Lewerenz, Meinert T1 - Comparison of dU/dQ, Voltage Decay, and Float Currents via Temperature Ramps and Steps in Li‐ion Batteries JF - Batteries & Supercaps UR - https://doi.org/10.1002/batt.202400627 Y1 - 2024 UR - https://doi.org/10.1002/batt.202400627 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-53655 SN - 2566-6223 VL - 8 IS - 1 PB - Wiley CY - Weinheim ER - TY - JOUR A1 - Paarmann, Sabine A1 - Schreiber, Markus A1 - Chahbaz, Ahmed A1 - Hildenbrand, Felix A1 - Stahl, Gereon A1 - Rogge, Marcel A1 - Dechent, Philipp A1 - Queisser, Oliver A1 - Frankl, Sebastian Dominic A1 - Morales Torricos, Pablo A1 - Lu, Yao A1 - Nikolov, Nikolay I. A1 - Kateri, Maria A1 - Sauer, Dirk Uwe A1 - Danzer, Michael A. A1 - Wetzel, Thomas A1 - Endisch, Christian A1 - Lienkamp, Markus A1 - Jossen, Andreas A1 - Lewerenz, Meinert T1 - Short‐Term Tests, Long‐Term Predictions – Accelerating Ageing Characterisation of Lithium‐Ion Batteries JF - Batteries & Supercaps N2 - AbstractFor the battery industry, quick determination of the ageing behaviour of lithium‐ion batteries is important both for the evaluation of existing designs as well as for R&D on future technologies. However, the target battery lifetime is 8–10 years, which implies low ageing rates that lead to an unacceptably long ageing test duration under real operation conditions. Therefore, ageing characterisation tests need to be accelerated to obtain ageing patterns in a period ranging from a few weeks to a few months. Known strategies, such as increasing the severity of stress factors, for example, temperature, current, and taking measurements with particularly high precision, need care in application to achieve meaningful results. We observe that this challenge does not receive enough attention in typical ageing studies. Therefore, this review introduces the definition and challenge of accelerated ageing along existing methods to accelerate the characterisation of battery ageing and lifetime modelling. We systematically discuss approaches along the existing literature. In this context, several test conditions and feasible acceleration strategies are highlighted, and the underlying modelling and statistical perspective is provided. This makes the review valuable for all who set up ageing tests, interpret ageing data, or rely on ageing data to predict battery lifetime. UR - https://doi.org/10.1002/batt.202300594 Y1 - 2024 UR - https://doi.org/10.1002/batt.202300594 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-51546 SN - 2566-6223 VL - 7 IS - 11 PB - Wiley CY - Weinheim ER -