Estimation Algorithm for Road Adhesion Coefficient of Distributed Electric Drive Vehicle Based on Left Inverse System

Abstract

The invention discloses a distributed electrically driven automobile road adhesion coefficient estimating algorithm based on a left inverse system and belongs to the technical field of electric automobiles. The road adhesion coefficient estimating algorithm comprises the following steps that 1, an original system model of the left inverse system relevant to road adhesion coefficients is established; 2, a vehicle double-nominal-amount effective piecewise function representation method based on a nominal lateral acceleration and nominal yaw velocity is designed, a nonlinear state of side deviation and yaw response during vehicle steering is comprehensively reflected, and an adhesion estimation deviation compensating algorithm is designed according to the relation of an effective piecewise function and road adhesion utilization rate; 3, it is proved through deduction that the original system has the left inverse system. Compared with an existing road adhesion coefficient estimating technology, the distributed electrically driven automobile road adhesion coefficient estimating algorithm has the advantages of having no need for parameter fitting, good in real-timeliness, high in reliability and capable of achieving wide application.

Description

technical field [0001] The invention belongs to the technical field of distributed electric drive vehicles, and in particular relates to an estimation algorithm for the road surface adhesion coefficient of distributed electric drive vehicles based on a left inverse system. Background technique [0002] Distributed electric drive vehicles are directly driven / braked by hub motors. Compared with traditional vehicles, their main structural features are short transmission chains, efficient transmission and compact structure. The in-wheel motor can be controlled by an independent controller, and its driving / braking torque can be accurately and independently measured and dynamically controlled. It has better response characteristics, higher response accuracy and faster response speed. Accurate identification of road conditions will help the vehicle stability control system to more effectively perform dynamic control and optimal distribution of four-wheel drive / braking torque, impro...

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Problems solved by technology

[0003] Chinese patent CN104354697A discloses a method for estimating the road surface adhesion coefficient using the on-line corrected vehicle state parameters. This invention needs to use the magic formula to estimate the quasi-static lateral force of the tire, and it is necessary to know when seeking the dynamic lateral force from the quasi-static lateral Influence factor K L , there are many parameters that need to be fitted, and the limitations in practical applications are relatively large; Chinese patent CN103612634A discloses a method for estimating the road adhesion coefficient of a decentralized in-wheel motor driven electric vehicle, by calculating the current corresponding point on the μ-λ curve Slope, and observe whether the slope exceeds a certain value within 1s to judge whether the road surface adhesion coefficient of the current distributed in-wheel motor driven electric vehicle reaches the peak value, and then judge the road surface type (homogeneous, split, docking or single-wheel independent road surface), this method does not give a specific value for the fixed value, and the judgment period of 1s is debatable, and the real-time performance of this method is not demonstrated

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