An energy-efficient torque distribution strategy for in-wheel-motored EVs based on model predictive control

被引:7
|
作者
Ren, Bingtao [1 ]
Deng, Weiwen [1 ]
Chen, Hong [2 ]
机构
[1] Beihang Univ, Sch Transportat Sci & Engn, Beijing Adv Innovat Ctr Big Data & Brain Comp, Beijing 100191, Peoples R China
[2] Tongji Univ, New Energy Vehicle Engn Ctr, Shanghai 201804, Peoples R China
基金
中国国家自然科学基金; 北京市自然科学基金; 国家重点研发计划;
关键词
optimal control; electric vehicle; MPC; model predictive control; torque distribution; energy loss; computational efficiency; CONTROL ALLOCATION; ELECTRIC VEHICLE; MPC; ALGORITHM; DRIVEN; SCHEME; FRONT;
D O I
10.1504/IJVD.2020.113910
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
In order to improve the energy efficiency (EE) for in-wheel-motored electric vehicles (IWM EVs), an optimal torque distribution algorithm is investigated based on model predictive control (MPC). Firstly, an optimisation structure is developed by considering energy efficiency characteristics of the motor and energy loss of tyre slip. To achieve the driving requirements, an upper layer controller determines a desired motor torque, considering the maximum capacity of the motor drive and regenerative brake. Then, an MPC-based torque distribution algorithm in lower layer deals with this energy efficiency optimisation problem with system dynamic and torque saturation constraints. Then to obtain the optimal motor torques fast, an efficient solution approach is given by combining constraint conversion and numerical methods. Finally, simulation results in different driving cycles indicate that overall energy efficiency and computational efficiency of vehicle can be improved. Also, the real-time control performance is guaranteed in the hardware-in-the-loop (HiL) simulation.
引用
收藏
页码:18 / 44
页数:27
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