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 - TY - JOUR A1 - Kiran, Iqra A1 - Azzam, Mohamed A1 - Endisch, Christian A1 - Butt, Nauman Zafar A1 - Lewerenz, Meinert T1 - Evaluation of Calendar Aging in Cells with Graphite: Silicon Anode Using Float Current Analysis Under the Influence of Voltage Hysteresis JF - Journal of The Electrochemical Society N2 - This study investigates the calendar aging of lithium-ion batteries with graphite-silicon anodes using float current analysis. While float current analysis is already a proven method for assessing aging in cells with graphite-based anodes, the presence of silicon introduces additional complexities due to its voltage hysteresis. We address this by comparing the results for the scaling factor separately for charge and discharge. The scaling factor is initially derived from charge and discharge GITT measurements on fresh cells, including an aging-induced shift among both electrode curves. This approach enables quantification of SEI growth ISEI growth, and cathode lithiation current ICL bridging measured results for float currents with capacity loss rate. As a result, the scaling factor during charge delivered the most meaningful results regarding fitted aging currents. By extending the estimation method based on the Arrhenius equation across temperatures from 5 °C to 50 °C, our model is validated against measured float currents, improving the predictive accuracy of long-term aging trends in silicon-containing anodes. Electrochemical impedance spectroscopy provided further insights into degradation mechanisms, revealing a strong correlation between cathode lithiation by salt decomposition and resistance increase at high voltages (⩾4.15 V), confirmed by pulse tests at 100% SOC showing a sharp resistance increase at elevated voltages. UR - https://doi.org/10.1149/1945-7111/ae0fe8 Y1 - 2025 UR - https://doi.org/10.1149/1945-7111/ae0fe8 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63053 SN - 1945-7111 VL - 172 IS - 10 PB - IOP Publishing CY - Bristol ER - TY - JOUR A1 - Kohler, Markus A1 - Mitsios, Dionysios A1 - Endisch, Christian T1 - Reconstruction-based visual anomaly detection in wound rotor synchronous machine production using convolutional autoencoders and structural similarity JF - Journal of Manufacturing Systems N2 - Manufacturing wound rotor synchronous machines (WRSMs) for electric vehicle traction systems necessitates rigorous quality inspection to ensure optimal product performance and efficiency. This paper presents a novel visual anomaly detection method for monitoring the needle winding process of WRSMs, utilizing unsupervised learning with convolutional autoencoders (CAEs) and the structural similarity index measure (SSIM). The method identifies deviations from the desired orthocyclic winding pattern during each stage of the winding process, enabling early detection of winding errors and preventing resource wastage and potential damage to the product or winding machinery. Trajectory-synchronized frame extraction aligns the visual inspection system with the winding trajectory, ensuring precise monitoring traceable to a specific point in the winding process. We present the comprehensive Winding Anomaly Dataset (WAD), which comprises images of WRSM rotor prototypes with and without winding faults recorded in different lighting conditions. The proposed reconstruction-based anomaly detection technique is trained on fault-free data only and utilizes the introduced masked mean structural dissimilarity index measure (MMSDIM) to focus on the relevant sections of the winding during inference. Comprehensive comparative analysis reveals that the CAE with unregularized latent space and the maximum mean discrepancy Wasserstein autoencoder (MMD-WAE) outperform the beta variational autoencoder (beta-VAE) in terms of anomaly detection performance, with the CAE and WAE delivering comparable results. Extensive testing confirms the approach’s effectiveness, achieving 95.6 % recall at 100 % precision, an AUROC of 99.9 %, and an average precision of 99.1 % on the challenging WAD, considerably outperforming state-of-the-art visual anomaly detection models. This work thus offers a robust solution for WRSM production quality monitoring and promotes the incorporation of visual inspection in electric drive manufacturing systems. UR - https://doi.org/10.1016/j.jmsy.2024.12.005 Y1 - 2024 UR - https://doi.org/10.1016/j.jmsy.2024.12.005 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-55371 SN - 1878-6642 VL - 2025 IS - 78 SP - 410 EP - 432 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schmid, Michael A1 - Vögele, Ulrich A1 - Endisch, Christian T1 - A novel matrix-vector-based framework for modeling and simulation of electric vehicle battery packs JF - Journal of Energy Storage UR - https://doi.org/10.1016/j.est.2020.101736 KW - Electric vehicle KW - Lithium-ion battery pack KW - Control-oriented modeling KW - Electro-thermal model KW - Fault diagnosis KW - Performance analysis Y1 - 2020 UR - https://doi.org/10.1016/j.est.2020.101736 SN - 2352-1538 VL - 2020 IS - 32 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schmid, Michael A1 - Endisch, Christian T1 - Online diagnosis of soft internal short circuits in series-connected battery packs using modified kernel principal component analysis JF - Journal of Energy Storage N2 - Safe operation of large battery storage systems requires advanced fault diagnosis that is able to detect faults and provide an early warning in the event of a fault. Since Internal Short Circuits (ISC) are the most common abuse condition leading to thermal runaway, this study addresses the early detection of incipient soft ISCs at the stage when the fault is still uncritical and does not lead to significant heat generation. The differences in cell voltages as measured by conventional battery management systems prove to be indicative features for ISC diagnosis. However, due to poor balancing and parameter variations, the cell voltage differences exhibit nonlinear variations. This work addresses this challenge with a nonlinear data model based on Kernel Principal Component Analysis (KPCA). To enable an online application in a vehicle, the present work reduces the computational complexity of the method by an optimal choice of training data. An analysis of the contribution of each cell to the fault statistics enables identification of the faulty cell. Since early-stage ISCs can exhibit a wide range of short-circuit resistances, experimental validation is performed with resistances from 10Ω to 10kΩ, which are correctly detected and isolated by the optimized cross-cell monitoring in all cases. UR - https://doi.org/10.1016/j.est.2022.104815 KW - lithium-ion battery KW - internal short circuit KW - fault diagnosis KW - fault isolation KW - kernel principal component analysis KW - battery safety Y1 - 2022 UR - https://doi.org/10.1016/j.est.2022.104815 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-25282 SN - 2352-1538 VL - 2022 IS - 53 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Lewerenz, Meinert A1 - Rahe, Christiane A1 - Fuchs, Georg A1 - Endisch, Christian A1 - Sauer, Dirk Uwe T1 - Evaluation of shallow cycling on two types of uncompressed automotive Li(Ni1/3Mn1/3Co1/3)O2-Graphite pouch cells JF - Journal of Energy Storage UR - https://doi.org/10.1016/j.est.2020.101529 KW - NMC KW - Compression KW - Cyclic aging tests KW - Differential voltage analysis KW - Post-mortem analysis KW - Irreversible aging KW - Anode overhang KW - Homogeneity of lithium distribution Y1 - 2020 UR - https://doi.org/10.1016/j.est.2020.101529 SN - 2352-1538 VL - 2020 IS - 30 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kleiner, Jan A1 - Stuckenberger, Magdalena A1 - Komsiyska, Lidiya A1 - Endisch, Christian T1 - Real-time core temperature prediction of prismatic automotive lithium-ion battery cells based on artificial neural networks JF - Journal of Energy Storage UR - https://doi.org/10.1016/j.est.2021.102588 KW - Lithium-ion battery KW - Battery modeling KW - Electro-thermal model KW - Thermal model KW - Neural network KW - Real-time application Y1 - 2021 UR - https://doi.org/10.1016/j.est.2021.102588 SN - 2352-1538 VL - 2021 IS - 39 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kleiner, Jan A1 - Heider, Alexander A1 - Komsiyska, Lidiya A1 - Elger, Gordon A1 - Endisch, Christian T1 - Thermal behavior of intelligent automotive lithium-ion batteries: Experimental study with switchable cells and reconfigurable modules JF - Journal of Energy Storage UR - https://doi.org/10.1016/j.est.2021.103274 KW - lithium-ion KW - intelligent battery KW - switchable cell KW - reconfiguration KW - smart cell KW - thermal management Y1 - 2021 UR - https://doi.org/10.1016/j.est.2021.103274 SN - 2352-1538 VL - 2021 IS - 44, Part A PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schmid, Michael A1 - Kleiner, Jan A1 - Endisch, Christian T1 - Early detection of Internal Short Circuits in series-connected battery packs based on nonlinear process monitoring JF - Journal of Energy Storage UR - https://doi.org/10.1016/j.est.2021.103732 KW - Lithium-ion battery KW - Internal Short Circuit KW - Fault diagnosis KW - Kernel Principal Component Analysis KW - Cell inconsistencies KW - Battery safety Y1 - 2022 UR - https://doi.org/10.1016/j.est.2021.103732 SN - 2352-1538 VL - 2022 IS - 48 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kleiner, Jan A1 - Lechermann, Lorenz A1 - Komsiyska, Lidiya A1 - Elger, Gordon A1 - Endisch, Christian T1 - Thermal behavior of intelligent automotive lithium-ion batteries BT - operating strategies for adaptive thermal balancing by reconfiguration JF - Journal of energy storage UR - https://doi.org/10.1016/j.est.2021.102686 KW - intelligent battery KW - thermal management KW - balancing KW - cell-to-cell variations KW - inhomogeneities KW - thermal modeling Y1 - 2021 UR - https://doi.org/10.1016/j.est.2021.102686 SN - 2352-1538 VL - 2021 IS - 40 PB - Elsevier CY - Amsterdam 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 - CHAP A1 - Rauscher, Andreas A1 - Braun, Julian A1 - Hiemer, Rainer A1 - Heldwein, Marcelo Lobo A1 - Endisch, Christian T1 - Convolutional Neural Networks and Thresholding Approaches for Single and Multi-Sensor Detection of Partial Discharges in Electrical Machine Stators T2 - Proceedings of the 15th International 2025 IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED) UR - https://doi.org/10.1109/SDEMPED53223.2025.11153974 Y1 - 2025 UR - https://doi.org/10.1109/SDEMPED53223.2025.11153974 SN - 979-8-3503-8820-6 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Vögele, Ulrich A1 - Endisch, Christian T1 - Predictive Vehicle Velocity Control Using Dynamic Traffic Information JF - SAE Technical Paper UR - https://doi.org/10.4271/2016-01-0121 Y1 - 2016 UR - https://doi.org/10.4271/2016-01-0121 SN - 0148-7191 SN - 2688-3627 PB - SAE CY - Warrendale ER - TY - CHAP A1 - Ziegmann, Johannes A1 - Denk, Florian A1 - Vögele, Ulrich A1 - Endisch, Christian T1 - Stochastic Driver Velocity Prediction with Environmental Features on Naturalistic Driving Data T2 - 2018 IEEE Intelligent Transportation Systems Conference UR - https://doi.org/10.1109/ITSC.2018.8569767 KW - Velocity prediction KW - driver behavior modeling KW - energy prediction KW - Kalman filter KW - Particle filter KW - switching hidden Markov model Y1 - 2018 UR - https://doi.org/10.1109/ITSC.2018.8569767 SN - 978-1-7281-0323-5 SP - 1807 EP - 1814 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Morales Torricos, Pablo A1 - Gallenberger, Andreas A1 - Droese, Dominik A1 - Kowal, Julia A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Analyzing the Impact of Electrolyte Motion Induced Salt Inhomogeneity Effect on Apparent Aging: Role of Current Rates and Temperature Effects in Accelerated Cyclic Aging Tests in Li-Ion Batteries JF - Batteries & Supercaps N2 - Accurate and rapid assessment of lithium-ion battery lifetime is essential for predicting remaining lifespan, enabling the selection of appropriate cells for specific applications and determining suitability for second-life use. However, accelerated cyclic aging tests may underestimate a cell's total lifespan due to exaggerated capacity fade that does not occur under real-world conditions. This increased capacity fade is primarily driven by electrolyte motion induced salt inhomogeneity (EMSI) and loss of homogeneity of lithium distribution (HLD). This study investigates the impact of varying charge and discharge currents on capacity loss during accelerated testing in compressed NMC-Gr pouch cells. Most of the capacity loss observed during cycling is fully recoverable after a resting period, with some cells regaining up to 81% of their lost capacity. Contrary to expectations, cells subjected to the highest cycling currents do not exhibit the greatest recoverable capacity loss. This phenomenon can be attributed to the interplay between current and temperature: While higher cycling currents exacerbate EMSI and HLD loss, they simultaneously elevate cell temperature, which mitigates EMSI by weakening polarization, enhancing electrolyte salt diffusion and homogenizing lithium distribution in the anode. Consequently, higher temperatures counteract HLD and EMSI-effect and therefore reduce apparent capacity loss. UR - https://doi.org/10.1002/batt.202500559 Y1 - 2025 UR - https://doi.org/10.1002/batt.202500559 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-62944 SN - 2566-6223 VL - 9 IS - 4 PB - Wiley CY - Weinheim ER - TY - JOUR A1 - Theiler, Michael A1 - Nörpel, Felix A1 - Baumann, Alexander A1 - Endisch, Christian T1 - Thermal fault detection in battery systems using principal component analysis with adaptive thresholding JF - Journal of Energy Storage N2 - Lithium-ion cells pose serious safety risks when they enter a state with highly exothermic reactions known as thermal runaway. Because elevated temperature is the ultimate trigger for this failure mode, reliable and timely detection of abnormal cell temperature is critical. Early detection enables, user warning, fast emergency response, and provides the basis for effective active prevention strategies. In this work, we present an unsupervised data-driven approach that detects thermal faults by monitoring inter-cell voltage deviations. We apply principal component analysis (PCA) to capture systematic changes in voltage homogeneity that occur when a cell within a battery module heats abnormally. By systematically analyzing the effects of thermal stress on voltage homogeneity under varying operating conditions, we reveal requirements for a reliable detection method. Leveraging these insights, we introduce an adaptive thresholding mechanism. This novel approach significantly boosts the sensitivity to faults for a wide range of operating conditions while maintaining detection robustness. We validate the method through extensive experiments in which we externally heat a single cell within a module with the power of 1 W. Compared to both conventional linear PCA and nonlinear kernel PCA with a constant threshold, linear PCA with adaptive thresholding achieves a significantly better balance between sensitivity and robustness across the full range of test conditions. UR - https://doi.org/10.1016/j.est.2025.119101 Y1 - 2025 UR - https://doi.org/10.1016/j.est.2025.119101 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63603 SN - 2352-1538 VL - 2026 IS - 141, Part B PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Azzam, Mohamed A1 - Sauer, Dirk Uwe A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Comprehensive Analysis of Float Current Behavior and Calendar Aging Mechanisms in Lithium‐Ion Batteries JF - Batteries & Supercaps N2 - Aiming to quantify degradation currents from solid electrolyte interphase formation (ISEIgrowth) and gain of active lithium due to cathode lithiation (ICL), resulting from electrolyte decomposition, the float current behavior of lithium-ion batteries is investigated with different cathode materials. The float current, IFloat , represents the recharge current required to maintain the cell at a fixed potential during calendar aging. This current arises as lithium is irreversibly consumed at the anode or inserted into the cathode, shifting the electrode potentials. To account for the asymmetric response of the electrodes, a voltage-dependent scaling factor, SF, is introduced, derived from the slopes of the electrode-specific voltage curves. Using this factor in combination with measured float currents and capacity loss rates from check-up tests, ISEIgrowth and ICL is quantified at 30 °C across various float voltages. Although the SF and capacity data are limited to 30 °C, the model is extended to a range of 5–50 °C using only float current measurements. The results show that using capacity loss rates alone underestimate ISEIgrowth and that ICL, contributes significantly to the observed float current at elevated voltages, indicating that cathode lithiation plays an increasingly important role in high-voltage calendar aging. UR - https://doi.org/10.1002/batt.202500349 Y1 - 2025 UR - https://doi.org/10.1002/batt.202500349 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-68054 SN - 2566-6223 VL - 9 IS - 1 PB - Wiley CY - Weinheim ER -