Electronic Differential Control Research Of Rear?wheel Independent Drive Electric Vehicle

In order to take into account the control effect and energy-saving performance of electronic differential control(EDC)system,a novel EDC strategy is proposed when rear-wheel independent drive electric vehicle is on a curve.The characteristic of the control strategy is that the hierarchical structure design is used to improve dynamic performance of vehicle when cornering by tracking the desired longitudinal speed at the center and desired slip ratio of the driving wheel which can also improve the efficiency of the motor and the yaw stability of the vehicle.In this paper,the research object is rear-wheel independent drive electric vehicle.And this paper builds a seven-degree-of-freedom(DOF)dynamic model including a three-DOF body model and a wheel dynamic model of four rotational degrees of freedom.The longitudinal and lateral dynamics of wheels is described by Magic formula.Magic formula is used to build the tire model for describing the longitudinal and lateral dynamics of tires.Based on “preview following theory”,the driver model concludes preview optimal curvature model and accelerator pedal model.Ackerman steering model considering wheel sideslip angle is used to describe the relationship of vehicle longitudinal speed,longitudinal speed at the center of wheel and front wheel steering angle.The linear 2-DOF model can serve as a dynamic reference model.Acquisition of state parameters and road type identification is the necessary condition of exercising EDC.According to driven wheel speed,the estimation of longitudinal speed is obtained.In order to improve the accuracy and reliability of the estimation,Extended Kalman Filter is used to estimate the vehicle lateral speed and sideslip angle.Based on the linear 2-DOF model,the front and rear axle sideslip stiffness is estimated in real time.BP neural network algorithm is used to train the non-linear relationship between road type,slip rate,sideslip angle and vertical load,and a BP-based road type identification method is established.A hierarchical structured electronic differential control is built considering the impact of system energy consumption.In the upper control,the method of estimating the desired acceleration is designed by using the fuzzy algorithm,acceleration pedal opening value and its change rate.The desired driving torque is obtained on the basis of the desired acceleration.According to the sliding mode algorithm,two calculation variables for calculating yaw moment(namely vehicle state function and switching surface of sliding mode)are obtained.The middle control takes as much high motor efficiency as possible as the performance requirement goal and distributes the desired torques of left and right rear wheels according to the desired driving torque and the calculation variables for calculating yaw moment.The desired longitudinal speeds at the centers of left and right rear wheels are corrected once based on Ackerman steering model considering wheel sideslip angle and then corrected for the second time when considering the yaw stability of vehicle.In the low control,the desired slip ratios of left and right rear wheels can be obtained based on the inverse model of Magic formula and then the angular speeds of the left and right rear wheels can be calculated.Finally,angular speed and current closed-loop control strategy of brushless direct current motor(BLDCM)is used to track the desired angular speed and output the torques of in-wheel-motors.The proposed EDC strategy with hierarchical structured is simulated in road conditions of step steering and snake shape.The simulation results show that the designed EDC can restrain the slip ratios of the driving wheels and reduce the tracking errors of longitudinal speed at the center of the driving wheels,slip ratio of the driving wheels and road trajectory.The designed EDC can also improve motor efficiency.