Drive Control Strategy Study Based On4In-wheel-motor Drive Pure Electric Vehicle

In-wheel motors electric vehicles represent a brand-new kind of vehicle architecture,bringing new perspectives to the discipline of auto design. Since each wheel can becontrolled independently, this new type of drive system is able to realize advanced dynamiccontrol. Besides, powertrain and transmission systems are removed, giving engineersmore freedom to optimize layout of the automobile. As technology advances, batteries andmotors with smaller size and higher power will bring new opportunities for the developmentof in-wheel motor electric vehicles.First, this paper describes the development of a full electric vehicle prototype with ahighly control-by-wire chassis, consisting of four independently actuated in-wheel motors,an electric power steering system, an electro-hydraulic brake system and a lithium battery.After that, a CarSim vehicle model is built based on the physical structure and parameters ofthe prototype car, and calibrated according to the responses of the real prototype.Then, vehicle drive control strategy is designed. The control strategy is divided intostability control mode and economic control mode. As the car turns, stability control modesteps in. This control mode has a hierarchical structure. The upper level is responsible forcalculating total longitudinal torque and yawing moment needed under the current state. Thebottom level also called driving force distribution layer is responsible for assigning thetorque demand generated in the upper level to each wheel properly to improve the dynamicperformance and stability of the vehicle. A fuzzy logic controller is proposed as the uppercontroller of stability control. In addition, a PI control is introduced in order to compare thecontrol effects of the two methods. Driving force distribution layer employs RedistributedPseudo-inverse Method to optimize the torque supposed to be generated in each wheel. The goal is to minimize tire utilization while making sure the torque on each wheel does notsurpass the road adhesion limit. When driving in a straight road, the control strategy switchesto economy mode to enhance the vehicle efficiency. The optimized coefficients at differentspeeds and torques are calculated and tabulated according to the Map figure, then, throughlook-up table the optimal distribution coefficient of the current condition can be easilydetermined.At last, the control strategy is built in Matlab/Simulink environment and tested onCarSim vehicle dynamic model. The stability control mode is put through Hardware-in-Looptest. A chassis dynamometer experiment is carried out to verify the effect of the economymode. The experiment adopts the NEDC driving condition. The results from simulation andtest show that driving control strategy can effectively improve the stability of the vehicleduring cornering. It has a good real-time performance. The fuzzy controller has betterrobustness compared with PI controller. Besides, economy mode, to a certain extent, reducesthe energy consumption of the vehicle.