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%0 Thesis
%A Chen, Bicheng
%T Thermal behavior impact on electric motor sizing in battery electric vehicles
%I Rheinisch-Westfälische Technische Hochschule Aachen
%V Dissertation
%C Aachen
%M RWTH-2025-09415
%P 1 Online-Ressource : Illustrationen
%D 2025
%Z Veröffentlicht auf dem Publikationsserver der RWTH Aachen University
%Z Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2025
%X The increasing popularity of electric vehicles (EVs) as eco-friendly alternatives in the automotive industry has been impeded by consumer apprehensions regarding limited driving range. This work addresses this challenge by focusing on two pivotal factors crucial for enhancing EV efficiency and extending driving range: accurate temperature monitoring and optimal sizing for electrical machines (EMs). In response to the critical need for monitoring temperatures in electric drivetrain components, a centralized compact lumped parameter thermal network (LPTN) model is proposed. Departing from conventional distributed thermal models for each component, this thermal model considers the intricate thermal coupling between the inverter, EM and gearbox. Utilizing the measured and validated loss maps including the detailed losses distribution in the permanent magnet synchronous machine (PMSM), the model accurately calculates component losses. A global linear parameter-varying (LPV) identification approach is then applied to determine the parameters of the LPTN model. Cross-validation with independent experimental data of the US06 cycle on the chassis dynamometer yields a maximum estimation error of approximately 7 ◦C. Simulation results demonstrate the effectiveness of the centralized thermal model in estimating temperatures of critical parts while considering the thermal coupling between components. Additionally, this work introduces a promising approach known as "right-sizing" for EMs. This involves an efficient scaling of thermal parameters in a low-order LPTN model, enabling the estimation of temperature for the scaled PMSM. The proposed scaling approach facilitates a preliminary evaluation of the thermal limits of the PMSM during the early stages of development. Validation for both axial and radial scaling, with scaling factors ranging from 0.8 to 1.2, is conducted on a previously validated Ansys Motor-CAD model for typical automotive driving cycles, revealing a maximum temperature scaling error of less than 3.5 ◦C. The integration of the LPTN model and the scaling approach into a whole vehicle simulation model becomes instrumental in determining the optimal size of a specific EM for diverse driving scenarios, including urban and highway conditions. The pursuit of optimization is guided by considering critical factors such as the thermal constraints of the EM, the overall efficiency and performance of the EV. Employing the ant colony optimization (ACO) optimization algorithm results in the identification of a Pareto front for urban and highway scenarios. The optimization results suggest that a shorter motor length is advantageous in both urban and highway cycle scenarios. In urban scenarios, the optimized motor enhances acceleration performance while lowering energy consumption. However, in highway scenarios, there’s a trade-off between energy consumption and acceleration, with the optimized motor leading to a 2.84
%F PUB:(DE-HGF)11
%9 Dissertation / PhD Thesis
%R 10.18154/RWTH-2025-09415
%U https://publications.rwth-aachen.de/record/1021037