Torque allocation strategy based on economy and stability for electric vehicle considering controllability after motors failure

To reduce the energy consumption and improve the stability of distributed drive electric vehicles, a torque allocation strategy based on an economy and stability optimisation function (ESOF) and a fuzzy proportional-integral-derivative rule control (FPRC) strategy are proposed while considering motor efficiency, braking energy recovery and motor failure. First, the vehicle dynamics and motor equivalent models are established. Subsequently, a torque prediction model and fuzzy controller for the vehicle are designed to calculate the total desired torque and yaw moment, respectively. A torque optimisation function is established to minimise power losses in the electric motor and maximise braking energy recovery, and it is solved using an improved genetic algorithm. While satisfying vehicle driving constraints, the ESOF-based controller can effectively coordinate the operation of each motor in the high-efficiency range under driving and braking conditions. After one motor fault is detected, the ESOF-based controller is replaced with an FPRC-based controller to distribute the vehicle demand torque. A co-simulation platform integrating MATLAB/Simulink and CarSim is developed to verify the effectiveness of the proposed ESOF-based controller in the New European Driving Cycle (NEDC) and Federal Test Procedure 75 (FTP75) driving cycles. The effectiveness of the FPRC-based controller in step steering condition is verified using the co-simulation platform. The simulation results indicate that the vehicle economy and driving range of the ESOF-based controller improved compared with the results afforded by the typical torque distribution strategy based on the front-rear axle dynamic load ratio. The average efficiencies of the motors in the NEDC and FTP75 driving cycles increased by 2.94% and 2.4%, respectively. More importantly, the FPRC-based controller can more significantly improve the steering stability of a vehicle with motor failure compared with the ESOF-based controller.