双电机四驱电动汽车自适应复合防抱死控制

doi:10.13229/j.cnki.jdxbgxb201605004

吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (5): 1405-1413.doi: 10.13229/j.cnki.jdxbgxb201605004

双电机四驱电动汽车自适应复合防抱死控制

孙大许^1,2, 兰凤崇^1,3, 何幸福^1,3, 陈吉清^1,3

1.华南理工大学机械与汽车工程学院,广州 510640;
2.广东机电职业技术学院,广州 510515;
3.华南理工大学广东省汽车工程重点实验室,广州 510640

收稿日期:2014-06-17 出版日期:2016-09-20 发布日期:2016-09-20
通讯作者: 陈吉清(1966-),女,教授,博士生导师.研究方向:汽车结构与安全.E-mail:chjq@scut.edu.cn
作者简介:孙大许(1973-),男,讲师,博士研究生.研究方向:新能源汽车.E-mail:sundx55@126.com
基金资助:
广东省科技计划项目(2014B010106002,2014B010125001).

Self-adaptive composite ABS of dual-motor four-wheel drive electric vehicle

SUN Da-xu^1,2, LAN Feng-chong^1,3, HE Xing-fu^1,3, CHEN Ji-qing^1,3

1.School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640,China;
2.Guangdong Mechanical & Electrical Polytechnic, Guangzhou 510515,China;
3.Guangdong Key Laboratory of Vehicle Engineering, South China University of Technology, Guangzhou 510640, China

Received:2014-06-17 Online:2016-09-20 Published:2016-09-20

摘要/Abstract

摘要： 为了进一步提高双电机四驱电动汽车防抱死控制的响应速度和精度,在电液复合变参数PID防抱死系统的基础上,采用径向基函数神经网络系统对电动汽车电液复合制动系统进行在线辨识,利用车轮滑移率对于电机制动转矩变化的灵敏度信息对PID的控制参数进行滚动优化调整,实现自适应复合防抱死控制。运用离线仿真和快速控制原型在环实时实验对控制算法和在线实时控制效果进行了验证,结果表明:改进的控制算法提高了系统的控制精度和响应速度,而且满足控制系统的实时性要求。

关键词: 车辆工程, 径向基函数, 神经网络, 防抱死系统, 电动汽车

Abstract: On the basis of electro-hydraulic varying parameters PID control, to further improve the response rate and accuracy of anti-lock breaking system of a dual-motor four-wheel drive electric vehicle, the neural network system based on radial basis function is introduced to realize online identification of electro-hydraulic braking system. The sensitivity of the wheel slip ratio to motor braking torque is used to achieve scroll optimal adjustment of parameters of PID control, and to increase the response rate and accuracy. The off-line simulation and hardware in loop real time simulation are carried out to test the control algorithm. Results show that the improve control algorithm can increase the accuracy and regulating rate of the system, and meet the real time requirements of the control system.

Key words: vehicle engineering, radial basis function, neural network, anti-lock braking system(ABS), electric vehicle

中图分类号:

U461.3

孙大许, 兰凤崇, 何幸福, 陈吉清. 双电机四驱电动汽车自适应复合防抱死控制[J]. 吉林大学学报(工学版), 2016, 46(5): 1405-1413.

SUN Da-xu, LAN Feng-chong, HE Xing-fu, CHEN Ji-qing. Self-adaptive composite ABS of dual-motor four-wheel drive electric vehicle[J]. 吉林大学学报(工学版), 2016, 46(5): 1405-1413.

参考文献

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双电机四驱电动汽车自适应复合防抱死控制

Self-adaptive composite ABS of dual-motor four-wheel drive electric vehicle

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