A review of the design process of energy management systems for dual-motor battery electric vehicles

被引:11
|
作者
Louback, Eduardo [1 ]
Biswas, Atriya [1 ]
Machado, Fabricio [1 ]
Emadi, Ali [1 ]
机构
[1] McMaster Univ, McMaster Automot Resource Ctr MARC, Hamilton, ON L8P 0AL, Canada
来源
RENEWABLE & SUSTAINABLE ENERGY REVIEWS | 2024年 / 193卷
基金
加拿大自然科学与工程研究理事会;
关键词
Energy management system; Design process; Dual-motor powertrain; Battery electric vehicles; Reinforcement learning; Hardware-in-the-loop test; MODEL-PREDICTIVE CONTROL; REGENERATIVE BRAKING; DISTRIBUTION STRATEGY; POWER DISTRIBUTION; OPTIMIZATION; TRANSMISSION; EFFICIENCY; FRONT;
D O I
10.1016/j.rser.2024.114293
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Dual -motor battery electric vehicles (DM-BEVs) are a trending technology in the electric vehicle market. They have the potential to achieve higher energy savings and dynamic performances compared to singlespeed, single -motor BEVs. However, a more complex and robust energy management system (EMS) is needed to achieve these benefits. Hence, this work reviews the design process and real-time implementation of EMSs tailored for DM-BEVs, starting from the fundamental concepts of two -motor coupling. The advantages and disadvantages of the most popular dual -motor architectures and their influence on the EMS design complexity are presented, followed by a revision of the reported energy management controllers. Besides the most prominent methods, classified as rule -based or optimization -based techniques, reinforcement learningbased EMSs are discussed in detail, given their near -optimal, real-time implementation and adaptability to newer, unforeseen drive cycles. Finally, the standard procedures and equipment required to assess the EMS' performance with hardware -in -the -loop tests are presented. Conclusions and open challenges for the energy management controllers of DM-BEVs are discussed at the end of this work.
引用
收藏
页数:19
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