纯电动汽车的复合制动系统多目标控制研究

邢志伟; 毕凤荣; 马小强; 马腾; 吕振鹏; 黄宇

doi:10.13433/j.cnki.1003-8728.20190339

纯电动汽车的复合制动系统多目标控制研究

doi: 10.13433/j.cnki.1003-8728.20190339

邢志伟^1,,
毕凤荣^{1, 2, ,},
马小强³,
马腾^{1, 2},
吕振鹏¹,
黄宇^{1, 2}

1.
天津大学机械工程学院，天津　300072
2.
天津大学内燃机燃烧学国家重点实验室，天津　300072
3.
天津内燃机研究所，天津　300072

基金项目: 国家重点研发计划项目（面向重型载货车用燃料电池发动机集成与控制——燃料电池重型载货车整车集成）与天津市自然科学基金一般项目（18JCYBJC20000）资助

详细信息

作者简介:
邢志伟（1994−），硕士研究生，研究方向为汽车动力学、电动汽车复合制动等，xingzhiwei@tju.edu.cn

通讯作者:
毕凤荣，教授，博士生导师，fr_bi@tju.edu.cn

中图分类号: U469.72; U461.3
计量
- 文章访问数: 337
- HTML全文浏览量: 117
- PDF下载量: 86
- 被引次数: 0
出版历程
- 收稿日期: 2019-09-14
- 网络出版日期: 2021-02-02
- 刊出日期: 2020-12-05

Research on Multiobjective Control of Compound Braking System for Pure Electric Vehicle

Xing Zhiwei^1
,,
Bi Fengrong^{1, 2
, ,},
Ma Xiaoqiang³,
Ma Teng^{1, 2},
Lü Zhenpeng¹,
Huang Yu^{1, 2}

1.
School of Mechanical Engineering, Tianjin University, Tianjin 300072, China
2.
State Key Laboratory of Engines, Tianjin University, Tianjin 300072, China
3.
Tianjin Internal Combustion Engines Research Institute, Tianjin 300072, China

摘要

摘要: 以电动汽车的复合制动系统作为研究对象，设计并优化了其转矩分配控制策略。为了使汽车在制动时能同时满足制动稳定性和提高制动回收率的多目标需求，采用了带精英策略的多目标优化算法（NSGA-II）进行优化求解，针对其帕累托解集的决策过程提出基于模糊控制的改造理想解法选择最优方案，利用Simulink-Cruise联合仿真的方式进行了电动汽车的模拟计算。仿真结果验证了所提决策方法相较于其他决策方法更加符合实际的制动需求。
- 电动汽车 /
- 复合制动 /
- 多目标优化 /
- 帕累托解集 /
- 模糊控制 /
- 决策 /
- 联合仿真
Abstract: In this paper, the control strategy of torque distribution is designed and optimized based on the composite braking systesm of electric vehicle. In order to meet the multiobjective requiremaents of braking stability and improve brake energy recovery rate at the same time, a multiobjective optimization algorithm with elite strategy (NSGA-II) is adopted in this paper to solve the problem. At the same time, according to the dsecision making process of Pareto solution set, an improved ideal solution based on fuzzy control is proposed to select the optimal solution. Finally, the simulation on composite braking of electric vehicle is carried out based on Simulink-Cruise joint simulation, and the results verify the proposed decision method is more realistic than the other decision methods.
- electric vehicle (EV) /
- composite braking /
- multiobjective optimization /
- Pareto solution set /
- fuzzy control /
- decision making /
- joint simulation

HTML全文

图 1 机电复合制动系统机构

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图 2 安全制动范围

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图 3 NSGA-II多目标优化流程图

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图 4 多目标优化结果

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图 5 决策流程图

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图 6 模糊求解过程

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图 7 输入变量隶属度函数曲线图

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图 8 输出变量隶属度函数曲线图

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图 9 车辆整车模型

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图 10 Simulink控制模型

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图 11 前后轴需求制动力控制分配结果

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图 12 电机转矩输出值

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表 1 车辆参数

参数名称及单位	数值
整车质量/kg	800
轴距/mm	2467
质心到前轴距/mm	1200
质心高度/mm	500
迎风面积/m²	1.97
电机最大功率/kW	55
电池组容量/Ah	10
电池组最小电压/V	220
电池组最大电压/V	420
电池个数	5
电池初始SOC	0.5
车轮半径/mm	287

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表 2 制动能量回收情况表

制动力分配控制策略	回收的制动能量/kJ	制动能量回收提高率/%
方案1	798.1	－
方案2	975.9	22.8
方案3	1183.7	48.3
单独模糊控制	1064.2	33.3

下载: 导出CSV

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