State Parameter Estimation And Yaw Stability Control Of Distributed Drive Electric Vehicle

With a large number of cars pouring into the streets,energy shortage,environmental pollution and road safety issues grow more critical.Distributed drive electric vehicles have become one of the main directions of research in universities and major automobile companies because of their advantages of high controllability,compact vehicle structure,energy saving and emission reduction.Because the distributed drive electric vehicle has four fast-responding and autonomously controlled drive motors,it has great research value in yaw stability control.Simultaneously,the main basis of vehicle yaw stability management is real-time precise assessment of some important state parameters of the electric vehicle driving process.In summary,this paper estimates the important parameter states of distributed drive electric vehicles and conducts research on yaw stability.The main contents are as follows.(1)Dynamic modeling of distributed drive electric vehicle.The distributed drive electric vehicle model is jointly constructed using two software programs,Carsim and simulink.Under double line shift and step conditions,the model is compared to the traditional car model in Carsim,and the emulation results verify that the distributed drive electric vehicle model built in this paper has high accuracy.(2)Estimation of vehicle key state parameters.Due to the limitation of vehicle cost requirement and sensor reliability,some important driving state parameters of vehicles are not easy to obtain directly,so it is very important to use cheap sensors to obtain some conventional parameters and then use stable and reliable algorithms to estimate them.In this paper,considering that the measured noise varies with the environment during the actual driving of the vehicle,an improved suboptimal unbiased great a posteriori noise estimator is proposed to combine with the Cubature Kalman Filter to form a noise adaptive Cubature Kalman filter for online estimation of vehicle parameters.The simulation results show that the proposed noise adaptive Cubature Kalman Filter has a good estimation effect under both double-shifted and serpentine operating conditions.(3)Research on yaw stability controller based on layered structure.In order to ensure the safety of the vehicle in the process of driving,this paper designed a layered yaw stability controller.the upper layer controller adopts the model prediction control method to obtain the corrected yaw moment value,the lower layer moment distribution controller is tested in comparison with both optimized distribution and load distribution.The lowest tire consumption rate is the control target in the optimum distribution,and the longitudinal tire force must fulfill the road adhesion,corrected yaw moment,tire adhesion limit,and hub motor peak value restrictions,and the load distribution only considered the upper of correction yawing moment value should meet the requirements of vehicle control,using Carsim and simulink software to jointly build a test platform.In both double shift and serpentine conditions,the simulation results show that both optimized distribution and load distribution can improve the yaw stability of the vehicle to a certain extent,and the control effect of optimized distribution is better than that of load distribution.