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Estimation of Road Friction Coefficient in Different Road Conditions Based on Vehicle Braking Dynamics 被引量:10
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作者 You-Qun Zhao Hai-Qing Li +2 位作者 Fen Lin Jian Wang Xue-Wu Ji 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2017年第4期982-990,共9页
The accurate estimation of road friction coeffi- cient in the active safety control system has become increasingly prominent. Most previous studies on road friction estimation have only used vehicle longitudinal or la... The accurate estimation of road friction coeffi- cient in the active safety control system has become increasingly prominent. Most previous studies on road friction estimation have only used vehicle longitudinal or lateral dynamics and often ignored the load transfer, which tends to cause inaccurate of the actual road friction coef- ficient. A novel method considering load transfer of front and rear axles is proposed to estimate road friction coef- ficient based on braking dynamic model of two-wheeled vehicle. Sliding mode control technique is used to build the ideal braking torque controller, which control target is to control the actual wheel slip ratio of front and rear wheels tracking the ideal wheel slip ratio. In order to eliminate the chattering problem of the sliding mode controller, integral switching surface is used to design the sliding mode sur- face. A second order linear extended state observer is designed to observe road friction coefficient based on wheel speed and braking torque of front and rear wheels. The proposed road friction coefficient estimation schemes are evaluated by simulation in ADAMS/Car. The results show that the estimated values can well agree with the actual values in different road conditions. The observer can estimate road friction coefficient exactly in real-time andresist external disturbance. The proposed research provides a novel method to estimate road friction coefficient with strong robustness and more accurate. 展开更多
关键词 Road friction coefficient Real timeestimation External disturbance Different roadconditions
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