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

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.

An MPC-based manoeuvre stability controller for full drive-by-wire vehicles

Aiming at the actuator time delay caused by the drive-by-wire technology,a novel manoeuvre stability controller based on model predictive control is proposed for full drive-by-wire vehicles.Firstly,the future vehicle dynamics are predicted by a twodegree-of-freedom vehicle model with input delay.Secondly,in order to prevent the vehicle from destabilizing due to excessive side slip angles,the determined ideal yaw rate and side slip angle are tracked simultaneously by optimizing the front wheel angle and additional yaw moment.Moreover,in order to improve the trajectory tracking ability,a side slip angle constraint determined by phase plane stability boundaries is added to the cost function.The results of Matlab and veDYNA co-simulation show that the regulated yaw rate can track the reference value well and the side slip angle decreases.Meanwhile,the trajectory tracking ability is improved obviously by compensating the time delay.