Research On State Parameter Observation And Stability Control Of Distributed Electric Vehicle

This paper made an intensive study on the state estimation and stability control of distributed electric drive vehicle.In order to implement the theoretical study into actuality and bulid an experimental equipment for the new hub-motor that was developing,laboratory was buliding a distributed electric vehicle for testing,and this paper involved in the work of vehicle refitting and establishe the communication network.The main contents of this paper are as follows.1)Built a seven degrees of freedom dynamics simulation model of distributed drive electric vehicle based on Simulink,including the body dynamics model,wheel dynamic model and tire model.Contrasted and analysised the different tire model,this paper selected the Dugoff tire model for the study.Finally,compared the Simulink simulation model and CarSim model to verify its reliability.2)Considering the real-time of vehicle control system,this paper set up two kinds of state estimation method to reduce the computation scale in different ways: dimensionality reduction unscented Calman filter(UKF)estimator and spherical unscented Calman filter(SSUKF)estimator.The reduced dimension UKF refers to the estimator that use three freedom of degree estimation method,it reduce the computation scale by reducing dimension of state parameters;and SSUKF can reduce the computation scale by reducing the sigma point.Finally,compared the two new state estimation methods with the full dimensional UKF state estimator.The simulation results showed that the SSUKF estimator can not only guarantee the estimation accuracy but also reduce the computation scale under different operating conditions.3)A stability control system of distributed electric vehicle was established by means of hierarchical control based on modular hierarchical idea.The system consists of target yaw moment setting layer and drive torque distribution layer.The target yaw moment setting layer including linear two degrees of freedom vehicle reference model and fuzzy controller,subtract the target yaw rate and sideslip angle that the two degrees of freedom reference model output from the output of state estimator estimates,and send them into fuzzy controller.Then the fuzzy controller will output a target yaw moment value through the fuzzy rules.The driving torque distribution layer allocate the target yaw moment value according to the optimization objective under different constraints,and send the optimization results to the four wheels to perform the stability control.4)Participate in the refit task of the distributed electric drive test vehicle,and build the communication network of the whole vehicle.Sensor parameters acquisition and vehicle controller control for four wheel motors are realized,and the purpose of distributed driving is achieved.Finally,the collected vehicle status parameters are uploaded to the upper computer based on Labview for real-time display.