Study On The Control Strategy Of Straight-ahead Driving Condition Of Distributed Drive Electric Vehicle

The study focuses on the control of distributed drive electric vehicles’ longitudinal motion of straight-ahead driving condition. Seven DOF vehicle dynamics model is established to reflect the basic states of motion. The yawing motion is controlled based on linear quadratic optimal control theory. The longitudinal tire forces are distributed by optimizing the tire workload. The tire longitudinal forces are controlled through Dugoff tire inverse model and sliding mode control theory. The main works of this research are as follows.First of all, seven DOF vehicle dynamics model and associated models such as tire model, wheel model, driver model, motor model are established. The longitudinal tire force and lateral tire force curves under different road adhesion coefficient conditions are fitted based on the established magic formula tire model. The tires’ characteristic parameters under different road conditions are estimated based on those curves.Then longitudinal force demand model is established to solve the requirement of longitudinal force. A linear two degrees of freedom vehicle model and the linear quadratic optimal control theory are used to control the vehicle’s yaw rate and sideslip angle. The constraint equations are established according to the vehicle’s longitudinal force and yaw moment of demand. Then the longitudinal force on each wheel is distributed by optimizing the tire workload.Then Dugoff tire inverse model is established through Dugoff tire model. It is difficult to observe and control the tire force directly. So tire forces are converted to slip rates of the tire. The sliding mode controller is establisher based on sliding mode control theory and reaching law theory. The longitudinal force of the tire is controlled by the slip ratio of the tire.Finally, two Simulink models of the control strategy of straight-ahead driving condition of distributed drive electric vehicle are built. The driving control strategies are simulated on different road conditions. The comparative analysis of the two control strategies’ simulation results is used to prove the correctness of the way used in this paper.