Journal of South China University of Technology (Natural Science Edition) ›› 2021, Vol. 49 ›› Issue (7): 42-50,65.doi: 10.12141/j.issn.1000-565X.200531

Special Issue: 2021年交通运输工程

• Traffic & Transportation Engineering • Previous Articles     Next Articles

Adaptive Regenerative Braking Control Strategy of Range-Extended Electric Vehicle Based on Multi-Objective Optimization

LIU Hanwu LEI Yulong FU Yao LI Xingzhong   

  1. State Key Laboratory of Automotive Simulation and Control，Jilin University，Changchun 130022，Jilin，China
  • Received:2020-09-03 Revised:2021-04-23 Online:2021-07-25 Published:2021-07-01
  • Contact: 付尧 ( 1986-) ，男，博士，副教授，主要从事汽车传动系统理论与控制技术研究。 E-mail:fu_yao@jlu. edu.cn
  • About author:刘汉武 ( 1991-) ，男，博士生，主要从事混合动力汽车理论与控制技术研究。E-mail: hwliu19@mails.jlu.edu.cn
  • Supported by:
    Supported by the Development of Science and Technology Planning Project of Jilin Province ( 20170204073GX， 20180520071JH) and the“Thirteenth Five-Year”Science and Technology Research Planning Project of Jilin Provincial Department of Education ( JJKH20200957KJ)

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Abstract: Aiming at the multi-objective optimization ( MOO) problem of the range-extended electric vehicle regenerative braking control strategy，a real-time adaptive regenerative braking control strategy was proposed based on the MOO model and optimal optimization theory． Firstly，the vehicle simulation model was established on AVL / Cruise and Matlab /Simulnk software，and a MOO model was built with the system braking performance ( BP) ， regenerative braking loss efficiency ( RBLE) and battery capacity loss rate ( BCLR) as the objective functions based on NSGA-Ⅱ algorithm． Then Parato optimal solution was obtained through off-line optimization under the comprehensive regenerative braking performance． Combined with the optimization results，a real-time adaptive fuzzy controller was designed． The controller considers the road adhesion and the state of battery，and can adjust the distribution of the regenerative braking work-point online． Simulation results on WLTP driving cyclic conditions show that the adaptive regenerative braking control strategy can effectively balance the relationship among BP，RBLE and BCLR，and it can effectively reduce BP and RBLE while maintaining a small BCLR．

Key words: range-extended electric vehicle, regenerative braking, NSGA-Ⅱ algorithm, multi-objective optimization, adaptive fuzzy control

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