A study on the control strategy for maximum energy recovery by regenerative braking in electric vehicles

被引：0
|
作者：
Yang, Yajuan [1 ]
Zhao, Han [1 ]
Zhu, Maofei [2 ]
机构：
[1] School of Mechanical and Automotive Engineering, Hefei University of Technology, Hefei 230009, China
[2] Research Institute of New Energy Vehicles, JiangHuai Automobile Co., Ltd., Hefei 230601, China
来源：
Qiche Gongcheng/Automotive Engineering | 2013年 / 35卷 / 02期
关键词：
Fuzzy control - Hybrid vehicles - Traction motors - Quadratic programming - Recovery - Electric machine control;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The regenerative braking control strategy for a light hybrid electric vehicle (LHEV) is studied in this paper. Specifically, a braking control strategy for maximum energy recovery is proposed first with an objective of highest overall efficiency, and the charging powers are optimized by using sequential quadratic programming technique to obtain optimized torque working points of ISG motor. Then a simulation model for LHEV is built, a tracking control is performed over optimized torque of ISG motor with fuzzy control scheme, and a simulation is conducted on three different braking forces respectively with NEDC cycle to obtain energy recovery ratios in regenerative braking. Finally a real vehicle test corresponding to simulation conditions is carried out to verify the effectiveness of control strategy proposed.
引用
收藏
页码：105 / 110
相关论文
共 50 条
  • [21] Fully Electrified Regenerative Braking Control for Deep Energy Recovery and Maintaining Safety of Electric Vehicles
    Xu, Guoqing
    Xu, Kun
    Zheng, Chunhua
    Zhang, Xinye
    Zahid, Taimoor
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2016, 65 (03) : 1186 - 1198
  • [22] A PMSM fuzzy logic regenerative braking control strategy for electric vehicles
    Liu, Feng
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2021, 41 (04) : 4873 - 4881
  • [23] Regenerative braking strategy for hybrid electric vehicles based on regenerative torque optimization control
    Wang, F.
    Zhuo, B.
    [J]. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2008, 222 (D4) : 499 - 513
  • [24] Study of control strategy on regenerative braking for electric vehicle
    Ge, Hengyong
    Sun, Renyun
    Zhang, Xiaolong
    [J]. ADVANCES IN ENERGY SCIENCE AND EQUIPMENT ENGINEERING, 2015, : 2273 - 2276
  • [25] Maximum Power Recovery of Regenerative Braking in Electric Vehicles Based on Switched Reluctance Drive
    Namazi, Mohammad Masoud
    Saghaiannejad, Seyed Morteza
    Rashidi, Amir
    Ahn, Jin-Woo
    [J]. JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, 2018, 13 (02) : 800 - 811
  • [26] Energy recovery strategy for regenerative braking system of intelligent four-wheel independent drive electric vehicles
    Li, Liang
    Ping, Xianyao
    Shi, Jialei
    Wang, Xiangyu
    Wu, Xiuheng
    [J]. IET INTELLIGENT TRANSPORT SYSTEMS, 2021, 15 (01) : 119 - 131
  • [27] Research on Control Strategy of Hydraulic Regenerative Braking of Electrohydraulic Hybrid Electric Vehicles
    Zhao, Qinghai
    Zhang, Hongxin
    Xin, Yafei
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2021, 2021 (2021)
  • [28] Control strategy of regenerative braking for plug-in parallel hybrid electric vehicles
    Chen, Ze-Yu
    Yang, Ying
    Wang, Xin-Chao
    Lyu, Ming
    [J]. Dongbei Daxue Xuebao/Journal of Northeastern University, 2016, 37 (12): : 1750 - 1754
  • [29] Study on Control Strategy for Regenerative Braking in a Pure Electric Vehicle
    Ma, Kun
    Chu, Liang
    Yao, Liang
    Wang, Yanbo
    [J]. PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON ELECTRONIC & MECHANICAL ENGINEERING AND INFORMATION TECHNOLOGY (EMEIT-2012), 2012, 23
  • [30] Research on Multi-Mode Braking Energy Recovery Control Strategy for Battery Electric Vehicles
    Liu, Boju
    Li, Gang
    Wang, Shuang
    [J]. APPLIED SCIENCES-BASEL, 2024, 14 (15):
12345