Research On Stability Control System Of Electric Vehicles Based On The ADBR Motor

After entering the21stcentury, people started to pay more and more attention to protectthe environment, and the traditional internal combustion engine caused two importantproblems: global fuel quantity limit and environmental pollution caused by automobileexhaust. Because pure electric vehicle has the advantages of zero pollution and low noise, ithas a vast prospect. In this paper, a new type of motor driven in the form of a hybrid electricvehicle is studied. This paper is mainly about the analysis of stability control system of thehybrid electric vehicle based on ADBR motors.The hybrid vehicle in this article has used a new type of dual rotor motor, this kind ofmotor could be used to establish a new type of electric driving system. This vehicle adoptsdouble rotor motor direct drive form, and can be arbitrary switching drive mode. This motorinstalled directly in the drive axle, used to replace conventional mechanical differential driveaxle shaft of the reducer components. The planetary gear mechanism which used fordeceleration and reversing deceleration installed on both side of the motor, the power afterreduction structure and universal joint to the wheels. ADBR motor drive system integratesdriving, differential, regenerative braking, compared with the traditional electric motor hashigher efficiency and lighter weight.This paper mainly about the handling and stability control strategy of electric vehiclebased on ADBR motor. According to the characteristics of the ADBR motor control systemsimulation model is established, the characteristics of ADBR motor and electric cars havecarried on the simulation research. The result shows that the ADBR motor can drive cars andwith differential turning function through simulation analysis. According to the vehicle modeldata and driving form, the vehicle dynamic model is established. The yaw rate and side-slipangle are two main references to judge the stability of the vehicle. Among them, the yaw ratecan be achieved through kalman filter, but the side-slip angle must be obtained by estimation.So the speed estimation and the side-slip angle estimation were designed, and the simulationanalysis of the estimation accuracy. The desired yaw rate and side-slip angle are estimated byestablishing an ideal vehicle model. The phase method was used to detect the stable state ofvehicle. Fuzzy yawing moment controller is needed to estimate the compensation yawingmoment according to the vehicle’s instability situation. Slip rate controller needed to estimatetarget wheel slip rate and the required value reached by PID controller and fuzzy PIDcontroller.The simulation was carried on by Vedyna, and the road coefficients were0.4and0.8, thespeed were80km/h and60km/h. The simulate result shows that the proposed controlalgorithm significantly enhances the active safety performance of vehicles.