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.
机构:
Korea Adv Inst Sci & Technol, Grad Sch Automobile Technol, Taejon 305701, South KoreaKorea Adv Inst Sci & Technol, Grad Sch Automobile Technol, Taejon 305701, South Korea
机构:
Hefei Univ Technol, Automot Res Inst, Hefei 230009, Peoples R ChinaHefei Univ Technol, Automot Res Inst, Hefei 230009, Peoples R China
He, Lin
;
Ye, Wei
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机构:
Hefei Univ Technol, Sch Automot & Transportat Engn, Hefei 230009, Peoples R ChinaHefei Univ Technol, Automot Res Inst, Hefei 230009, Peoples R China
Ye, Wei
;
He, Zejia
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机构:
Hefei Univ Technol, Sch Automot & Transportat Engn, Hefei 230009, Peoples R ChinaHefei Univ Technol, Automot Res Inst, Hefei 230009, Peoples R China
He, Zejia
;
Song, Ke
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机构:
Tongji Univ, Sch Automot Studies, Shanghai 201804, Peoples R China
Tongji Univ, Clean Energy Automot Engn Ctr, Shanghai 201804, Peoples R ChinaHefei Univ Technol, Automot Res Inst, Hefei 230009, Peoples R China
Song, Ke
;
Shi, Qin
论文数: 0引用数: 0
h-index: 0
机构:
Hefei Univ Technol, Sch Automot & Transportat Engn, Hefei 230009, Peoples R ChinaHefei Univ Technol, Automot Res Inst, Hefei 230009, Peoples R China
机构:
Korea Adv Inst Sci & Technol, Grad Sch Automobile Technol, Taejon 305701, South KoreaKorea Adv Inst Sci & Technol, Grad Sch Automobile Technol, Taejon 305701, South Korea
机构:
Hefei Univ Technol, Automot Res Inst, Hefei 230009, Peoples R ChinaHefei Univ Technol, Automot Res Inst, Hefei 230009, Peoples R China
He, Lin
;
Ye, Wei
论文数: 0引用数: 0
h-index: 0
机构:
Hefei Univ Technol, Sch Automot & Transportat Engn, Hefei 230009, Peoples R ChinaHefei Univ Technol, Automot Res Inst, Hefei 230009, Peoples R China
Ye, Wei
;
He, Zejia
论文数: 0引用数: 0
h-index: 0
机构:
Hefei Univ Technol, Sch Automot & Transportat Engn, Hefei 230009, Peoples R ChinaHefei Univ Technol, Automot Res Inst, Hefei 230009, Peoples R China
He, Zejia
;
Song, Ke
论文数: 0引用数: 0
h-index: 0
机构:
Tongji Univ, Sch Automot Studies, Shanghai 201804, Peoples R China
Tongji Univ, Clean Energy Automot Engn Ctr, Shanghai 201804, Peoples R ChinaHefei Univ Technol, Automot Res Inst, Hefei 230009, Peoples R China
Song, Ke
;
Shi, Qin
论文数: 0引用数: 0
h-index: 0
机构:
Hefei Univ Technol, Sch Automot & Transportat Engn, Hefei 230009, Peoples R ChinaHefei Univ Technol, Automot Res Inst, Hefei 230009, Peoples R China