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

机译:基于运动最优估计策略的四轮驱动电动汽车轮胎摩擦系数估计

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摘要

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.
机译:考虑到可以获得转矩和轮速的特性,提出了一种四轮驱动电动汽车的运动视界估计策略。基于HSRI轮胎模型,设计了两种估算路面摩擦系数的方法。第一种方法间接使用利用率摩擦系数来估算路面摩擦系数。第二种方法通过变换HSRI的方程并将隐式形式更改为显式形式来执行估计。该估计算法可以充分考虑实际物理条件下估计量的约束,而不依赖于初始估计信息的选择。然后,利用这两种方法的优点,进行组合优化设计以获得准确的估计值。最后,通过AMESim和Simulink联合仿真平台,在高摩擦系数路面,低摩擦系数路面和变化的摩擦系数路面条件下,验证了估计器的有效性。

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