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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - Schneider, Dominik A1 - Liebhart, Bernhard A1 - Endisch, Christian T1 - Active state and parameter estimation as part of intelligent battery systems JF - Journal of Energy Storage UR - https://doi.org/10.1016/j.est.2021.102638 Y1 - 2021 UR - https://doi.org/10.1016/j.est.2021.102638 SN - 2352-1538 VL - 2021 IS - 39 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 -