Adaptive suspension state estimation based on IMMAKF on variable vehicle speed, road roughness grade and sprung mass condition.

ABSTRACT: Vehicle speed, road roughness grade and sprung mass are the three main factors to influence suspension control and state estimation. Aiming at the problem that fixed state observer cannot guarantee the estimation accuracy of suspension with driving scenario changes, a suspension state observer based on interactive multiple model adaptive Kalman filter (IMMAKF) is established. Firstly, an adaptive control suspension is proposed based on LQR algorithm and multi-objective optimization algorithm, which can automatically adjust the controller parameters according to the vehicle speed, road roughness grade and sprung acceleration parameters, so as to keep the optimal control effect of the suspension. Secondly, the theoretical model of IMMAKF is derived, and two kinds of IMMAKF suspension state o

SUBMITTER: Wu X 

PROVIDER: S-EPMC10799087 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature