Road tire friction coefficient estimation for four wheel drive electric vehicle based on moving optimal estimation strategy

By Feng Yuchi, Hong Chen, Haiyan Zhao, Hao Zhou. 2020

53 citations recorded by the source corpus.

Abstract In this paper, a moving horizon estimation strategy for the four-wheel drive electric vehicle is proposed considering the characteristic that the torque and wheel speed can be obtained. Based on the HSRI tire model, two methods for estimating the friction coefficient of the road surface are designed. The first method indirectly uses the utilization friction coefficient to estimate the road surface friction coefficient. The second method performs the estimation by transforming the equation of the HSRI and changing the implicit form into a explicit form. The estimation algorithm can fully consider the constraints of the estimated amount under actual physical conditions, and not depend on the selection of the initial estimate information. Then, using the advantages of the two methods, the combined optimization design is performed to obtain the accurate estimation. Finally, the effectiveness of the estimator was verified by the joint simulation platform of AMESim and Simulink under high friction coefficient pavement, low friction coefficient pavement and varying friction coefficient pavement conditions.

Subfields: Automotive Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/e442bddedf5cfca080af25c78af43836b5c9f4b1