A Model Predictive Control Approach With Slip Ratio Estimation for Electric Motor Antilock Braking of Battery Electric Vehicle

被引:26
|
作者
He, Zejia [1 ]
Shi, Qin [1 ]
Wei, Yujiang [1 ]
Gao, Bingzhao [2 ]
Zhu, Bo [3 ]
He, Lin [4 ]
机构
[1] Hefei Univ Technol, Sch Automot & Transportat Engn, Hefei 230009, Peoples R China
[2] Jilin Univ, Coll Automot Engn, Changchun 130022, Peoples R China
[3] Hefei Univ Technol, Automot Res Inst, Hefei 230009, Peoples R China
[4] Hefei Univ Technol, Lab Automot Intelligence & Electrificat, Hefei 230009, Peoples R China
关键词
Wheels; Electric motors; Roads; Vehicle dynamics; Estimation; Torque; Permanent magnet motors; Adhesion coefficient estimation; braking force observer; ground slip map; optimal slip ratio; wheel dynamics model; REGENERATIVE BRAKING; SYSTEM; OPTIMIZATION; DESIGN;
D O I
10.1109/TIE.2021.3112966
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, based on the estimation of optimal slip ratio, a model predictive control approach is proposed for the antilock braking system with motor of a battery electric vehicle. A wheel dynamics model with a virtual control quantity is established. A method for estimating the optimal slip ratio of different roads is introduced, which consists of a sliding mode observer for longitudinal braking force and a recognizer of slip ratio. A ground slip map that describes the relationship between slip ratio and ground adhesion coefficient is proposed, which is utilized to identify the optimal slip ratio. Based on the model predictive control algorithm, a braking torque controller is designed to track the optimal slip ratio for good performance of braking stability and security. The vehicle control unit embedded with the estimator and model predictive control law is tested in a battery electric vehicle on the dry and wet roads. The experimental results indicate that the proposed approach has a good performance for the estimation and control of slip ratio during the antilock braking with electric motor, especially suitable for the low adhesion road conditions.
引用
收藏
页码:9225 / 9234
页数:10
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