系统仿真学报 ›› 2016, Vol. 28 ›› Issue (3): 600-609.

• 仿真应用工程 • 上一篇    下一篇

纯电动汽车动力系统匹配优化与再生制动策略

张奇1, 符晓玲1,2, 李珂1, 邢国靖1, 张承慧1   

  1. 1.山东大学控制科学与工程学院,山东 济南 250061;
    2.昌吉学院物理系,新疆 昌吉 831100
  • 收稿日期:2014-11-13 修回日期:2015-02-06 发布日期:2020-07-02
  • 通讯作者: 李珂(1979-),男,山东,博士,副教授,研究方向为新能源与电气传动。
  • 作者简介:张奇(1987-),男,山东,助理实验师,研究方向为电动汽车;符晓玲(1977-),女,新疆,博士生,讲师,研究方向为电动汽车;
  • 基金资助:
    国家自然科学基金(51277116, 61304130,61304029)

Powertrain System Matching Optimization and Regenerative Braking Strategy for Pure Electric Vehicle

Zhang Qi1, Fu Xiaoling1,2, Li Ke1, Xing Guojing1, Zhang Chenghui1   

  1. 1. School of Control Science and Engineering, Shandong University, Jinan 250061, China;
    2. Department of Physics, Changji University, Changji 831100, China
  • Received:2014-11-13 Revised:2015-02-06 Published:2020-07-02

摘要: 通过组合矩阵实验和多目标优化方法评价了不同匹配方案,设计了一种新型电动汽车再生制动控制策略。根据整车性能指标分析电机、电池、主减速器等需求;采用线性加权法设计了兼顾动力性与经济性的多目标优化函数,并通过Cruise组合矩阵实验,衡量了不同匹配方案的优劣;最后,依据车速和制动踏板强度设计了基于前后轮制动力分配的再生制动策略。仿真结果表明电动汽车动力系统的选型匹配对整车动力性和经济性影响很大,再生制动控制策略兼顾了能量回收和制动安全性。

关键词: 电动汽车, 匹配优化, 再生制动策略, 建模与仿真, AVL Cruise

Abstract: Different matching proposals meeting the constraints were multi-objective optimized with the combined matrix, and a new regenerative braking control strategy for electric vehicle was designed. According to the design targets of pure electric vehicle, the parameters of drive motor, battery pack and reducer were analyzed. Multi-objective optimization function was designed with the linearity weighted aggregation method, considering both power and economy of electric vehicle, and the vehicle performance of different proposals was comparatively measured through Cruise combined matrix simulation. The front and rear braking force distribution control strategy was designed based on the velocity and brake pedal intensity. Simulation results show that the selection and matching of powertrain system has a great impact on the electric vehicle's power and economy, and the regenerative braking control strategy takes into account both energy recovery and braking safety.

Key words: electric vehicle, matching optimization, regenerative braking strategy, modeling and simulation, AVL Cruise

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