Acker, L., Hofmann, P., & Konrad, J. (2026). Battery Thermal Management for Fast Charging based on Nonlinear Model Predictive Control. In A. Heintzel (Ed.), Elektrische Antriebe und Energiesysteme 2025 : Conference proceedings (pp. 109–122). Springer Vieweg.
19. MTZ-Fachtagung Elektrische Antriebe und Energiesysteme 2025
de
Event date:
26-Mar-2025 - 27-Mar-2025
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Event place:
Germany
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Number of Pages:
14
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Publisher:
Springer Vieweg, Wiesbaden
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Keywords:
Battery electric vehicle; battery thermal management; nonlinear model predictive control; fast charging
en
Abstract:
Thermal management of the battery during fast charging is crucial for charging time, energy consumption and safety. To address this challenge, this paper introduces a novel battery thermal management strategy for fast charging of battery electric vehicles based on nonlinear model predictive control (NMPC). First, a control-oriented model is parameterized using measurement data of a state-of-the-art battery electric vehicle (BEV). The optimal thermal management strategy for fast charging under a wide range of conditions is then calculated. Based on the optimization results, battery temperature thresholds as functions of the state of charge are used as references within the real-time capable controller. The controller's performance is subsequently tested using a validated high-fidel-ity simulation model. Compared to the baseline rule-based strategy, the NMPC can save up to 51% in auxiliary energy consumption at medium and high ambient temperatures through efficient cooling, while reducing charging time by up to 4.5% at low ambient temperatures through aggressive heating.
