Motor-Temperature-Aware Optimal Energy Management for Dual-Motor Electric Buses

This work studies the energy management performance of heavy-duty electric buses (EBs) equipped with two electric motors onboard their powertrains. Instead of merely considering the effects of load torque and angular speed on motor efficiency, the proposed optimal scheme further includes the effect of different temperatures on motor performance. After identifying a novel motor temperature model and generating temperature-dependent three-dimensional motor efficiency maps based on experimentally collected data, the energy management task is formulated as an optimal control problem and solved by dynamic programming that guarantees the global optimality of the generated solution. Compared with an existing single-motor powertrain and dual-motor powertrain controlled by benchmark strategies, the heavy-duty EB can benefit from a maximum of 11.96% battery electric energy consumption saving after utilizing the proposed temperature-aware optimal dual-motor energy management scheme.

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Publication Details

Published
2024-10-07
DOI
https://doi.org/10.1109/vppc63154.2024.10755280
Primary Topic
Electric and Hybrid Vehicle Technologies
Type
article
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article

Motor-Temperature-Aware Optimal Energy Management for Dual-Motor Electric Buses

Simos A. Evangelou, Yaprak Yalçın, Cuneyt Haspolat, Saleh Msaddi et al.
Electric and Hybrid Vehicle Technologies
article

Motor-Temperature-Aware Optimal Energy Management for Dual-Motor Electric Buses

Simos A. Evangelou, Yaprak Yalçın, Cuneyt Haspolat, Saleh Msaddi, Boli Chen, Imad M. Jaimoukha, Sheng Yu
article en

Abstract

This work studies the energy management performance of heavy-duty electric buses (EBs) equipped with two electric motors onboard their powertrains. Instead of merely considering the effects of load torque and angular speed on motor efficiency, the proposed optimal scheme further includes the effect of different temperatures on motor performance. After identifying a novel motor temperature model and generating temperature-dependent three-dimensional motor efficiency maps based on experimentally collected data, the energy management task is formulated as an optimal control problem and solved by dynamic programming that guarantees the global optimality of the generated solution. Compared with an existing single-motor powertrain and dual-motor powertrain controlled by benchmark strategies, the heavy-duty EB can benefit from a maximum of 11.96% battery electric energy consumption saving after utilizing the proposed temperature-aware optimal dual-motor energy management scheme.

University College London (GB), Imperial College London (GB), Istanbul Technical University (TR)
Affordable and clean energy
Openalex Percentile: Top 78%
Electric and Hybrid Vehicle Technologies
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