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Institut für Leistungselektronik und Elektrische Antriebe
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Hermann, M.Sc., Chris

Chris Hermann, M.Sc.

Akademischer Mitarbeiter
Institut für Leistungselektronik und Elektrische Antriebe

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+49 711 685 67387
+49 711 685 67378
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Pfaffenwaldring 47
70569 Stuttgart
Deutschland
Raum: 0.252, ETI 1

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2023
1. Chu, A., Xie, X., Hermann, C.M., Stork, W., Roth-Stielow, J.: Towards Predictive Lifetime-Oriented Temperature Control of Power Electronics in E-vehicles via Reinforcement Learning. In: IEEE (ed.) 2023 IEEE International Conference on Big Data (BigData). pp. 1667–1676 (2023).
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  @inproceedings{10386292, abstract = {As the electric vehicle (EV) industry rapidly grows, the reliability of EVs is an ongoing challenge to the automotive industry. Among them, due to the introduction of electric motors, the aging and degradation of power electronics in EVs have a direct influence on the overall system safety and may lead to total failure. Therefore, extending the lifetime of power electronics has been a focus in the last decades, where reducing the temperature swings is the key to achieving the goal. However, temperature optimization usually requires future information on power loads, which is not available in classic approaches. Therefore, in this paper, we propose a baseline framework for lifetime-oriented temperature control with reinforcement learning (RL). Focusing on long-term prediction, the framework integrates various physical modelings of EV modules (sensors, actuators, vehicle dynamics and temperature management) and utilizes real-time route information to train an agent for driving behavior prediction. Based on further interaction with the EV model, future temperature development can be estimated in advance, thus enabling better swing optimization. Experiments demonstrate the effectiveness of our approach and the lifetime of power electronics can be extended by up to 63% on a representative test route. Compared to the classic approach, our predictive temperature control shows impressive energy efficiency by achieving up to 2.8x power loss reduction with better lifetime optimization.}, author = {Chu, Anqi and Xie, Xiang and Hermann, Chris Manuel and Stork, Wilhelm and Roth-Stielow, Jörg}, booktitle = {2023 IEEE International Conference on Big Data (BigData)}, editor = {IEEE}, language = {en}, month = {12}, pages = {1667-1676}, title = {Towards Predictive Lifetime-Oriented Temperature Control of Power Electronics in E-vehicles via Reinforcement Learning}, url = {https://ieeexplore.ieee.org/document/10386292}, year = 2023 }
  Link
  https://ieeexplore.ieee.org/document/10386292
2. Chu, A., Hermann, C.M., Silz, J., Pfau, J., Barón, K.M., Anantharajaiah, N., Schmidt, P., Hotfilter, T., Xie, X., Becker, J., Kallfass, I., Roth-Stielow, J., Stork, W.: LETSCOPE: Lifecycle Extensions Through Software-Defined Predictive Control of Power Electronics. In: IEEE (ed.) IEEE EUROCON 2023 - 20th International Conference on Smart Technologies. pp. 665–670 (2023).
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  @inproceedings{10199076, abstract = {In the era of electric vehicles, the reliability of power electronics has become a crucial part as the industry evolves. Changes in electrical parameters caused by aging and degradation can lead to performance deterioration and eventually the total failure (end-of-life) of power electronic components, whereas the lifetime of power transistors depends to a large extent on the temperature fluctuations. Therefore, it is desired to extend the lifetime by minimizing the temperature swings without affecting the vehicle dynamics. In this paper, we propose the LETSCOPE (Lifecycle Extensions through Software-Defined Predictive Control of Power Electronics) framework for the lifetime extension with a neural-network-based intelligent management system. The driving behavior in the near future is estimated based on information fusion, which enables the predictive optimization of the temperature fluctuations. Besides, to perform real-time on-board management, an integrated SoC with hardware accelerator is developed for an efficient execution under resource constraints. Proof-of-concept experiments on a benchmark route show that the LETSCOPE framework can improve the expected lifetime of power electronics by up to 87% without vehicle dynamics degradation. Moreover, the monitoring of critical parameters provides an early warning of total failure, which contributes to the overall system reliability.}, author = {Chu, Anqi and Hermann, Chris Manuel and Silz, Johannes and Pfau, Johannes and Barón, Kevin Muñoz and Anantharajaiah, Nidhi and Schmidt, Patrick and Hotfilter, Tim and Xie, Xiang and Becker, Jürgen and Kallfass, Ingmar and Roth-Stielow, Jörg and Stork, Wilhelm}, booktitle = {IEEE EUROCON 2023 - 20th International Conference on Smart Technologies}, editor = {IEEE}, month = {07}, pages = {665-670}, title = {LETSCOPE: Lifecycle Extensions Through Software-Defined Predictive Control of Power Electronics}, url = {https://ieeexplore.ieee.org/document/10199076}, year = 2023 }
  Link
  https://ieeexplore.ieee.org/document/10199076
3. Ketchedjian, V., Haspel, A., Hermann, C., Roth-Stielow, J.: A Novel Weight Function and Interpolation Method for the Field Weakening Strategy of a Synchronous Reluctance Machine. In: 2023 IEEE 8th Southern Power Electronics Conference and 17th Brazilian Power Electronics Conference (SPEC/COBEP). pp. 1–8 (2023).
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  @inproceedings{10407299, abstract = {In this paper a new field weakening strategy is proposed for the torque control of a synchronous reluctance machine. The control strategy does not require any machine parameters. It uses an interpolation method between the MTPA-and MTPV-trajectories to move along a path, which is very similar to that of the constant torque contour lines. It also reduces the copper losses in the field weakening region. The strategy uses look-up tables for the trajectories determined from measurement results and does not require any additional cascade controller. Hence the stability and the dynamic of the current controller are not degraded. The control strategy is validated experimentally using an 11kW synchronous reluctance machine.}, author = {Ketchedjian, Vasken and Haspel, André and Hermann, Chris and Roth-Stielow, Jörg}, booktitle = {2023 IEEE 8th Southern Power Electronics Conference and 17th Brazilian Power Electronics Conference (SPEC/COBEP)}, issn = {2832-2983}, month = {11}, pages = {1-8}, title = {A Novel Weight Function and Interpolation Method for the Field Weakening Strategy of a Synchronous Reluctance Machine}, url = {https://ieeexplore.ieee.org/document/10407299}, year = 2023 }
  Link
  https://ieeexplore.ieee.org/document/10407299
2019
1. Ruthardt, J., Hermann, C., Wölfle, J., Fischer, M., Roth-Stielow, J.: Gate-driver circuit with a variable supply voltage to influence the switching losses. The Journal of Engineering. 2019, 3692--3695 (2019). https://doi.org/10.1049/joe.2018.8129.
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  @article{Ruthardt_2019, abstract = {The lifetime of semiconductor devices used in power electronics depends on the junction temperature. With a suitable junction temperature control system, the lifetime of semiconductor devices is extended. These control systems require a possibility to influence the power losses of the semiconductor devices and therefore the junction temperature. The proposed gate-driver circuit has a variable supply voltage in order to influence the switching speed of the semiconductor devices. This affects the switching losses. In addition, the adjustable switching speed can be used to prevent voltage overshoots during the switching transition or to decrease electromagnetic emission. The main advantage of this gate-driver circuit is its simple structure. This study focuses on the switching losses. }, author = {Ruthardt, Johannes and Hermann, Chris and Wölfle, Julian and Fischer, Manuel and Roth-Stielow, Jörg}, doi = {10.1049/joe.2018.8129}, issn = {2051-3305}, journal = {The Journal of Engineering}, language = {English}, month = {06}, number = 17, pages = {3692--3695}, publisher = {Institution of Engineering and Technology ({IET})}, title = {Gate-driver circuit with a variable supply voltage to influence the switching losses}, url = {https://digital-library.theiet.org/content/journals/10.1049/joe.2018.8129}, volume = 2019, year = 2019 }
  Link
  https://digital-library.theiet.org/content/journals/10.1049/joe.2018.8129

Chris Hermann, M.Sc.

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