首页|State Estimation of Drive-by-Wire Chassis Vehicle Based on Dual Unscented Particle Filter Algorithm

State Estimation of Drive-by-Wire Chassis Vehicle Based on Dual Unscented Particle Filter Algorithm

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Accurate vehicle dynamic information plays an important role in vehicle driving safety.However,due to the characteristics of high mobility and multiple controllable degrees of freedom of drive-by-wire chassis vehicles,the current mature application of traditional vehicle state estimation algorithms can not meet the requirements of drive-by-wire chassis vehicle state estimation.This paper proposes a state estimation method for drive-by-wire chassis vehicle based on the dual unscented particle filter algorithm,which make full use of the known advantages of the four-wheel drive torque and steer angle parameters of the drive-by-wire chassis vehicle.In the dual unscented particle filter algorithm,two unscented particle filter transfer information to each other,observe the vehicle state information and the tire force parameter information of the four wheels respectively,which reduce the influence of parameter uncertainty and model parameter changes on the estimation accuracy during driving.The performance with the dual unscented particle filter algorithm,which is analyzed in terms of the time-average square error,is superior of the unscented Kalman filter algorithm.The effectiveness of the algorithm is further verified by driving simulator test.In this paper,a vehicle state estimator based on dual unscented particle filter algorithm was proposed for the first time to improve the estimation accuracy of vehicle parameters and states.

Drive-by-wire chassis vehicleVehicle state estimationDual unscented particle filterTire force estimationUnscented particle filter

Zixu Wang、Chaoning Chen、Quan Jiang、Hongyu Zheng、Chuyo Kaku

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State Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun 130022,China

Jiangsu Chaoli Electric Co.Ltd.,Zhenjiang 212321,China

国家重点研发计划Science and Technology Department Program of Jilin Province of China

2021YFB250070320230101121JC

2024

中国机械工程学报
中国机械工程学会

中国机械工程学报

CSTPCD
影响因子:0.765
ISSN:1000-9345
年,卷(期):2024.37(1)