An Energy-Saving Torque Vectoring Control Strategy for Electric Vehicles Considering Handling Stability Under Extreme Conditions

Four-wheel independently actuated electric vehicles (FWIA EVs) allow variable distributions of driving torques among individual wheels to improve vehicle performance. To reduce energy consumption while ensuring handling stability, we propose an optimal torque vectoring control strategy based on a two-level distribution formula. This strategy can naturally decouple front/rear axle torque vectoring from left/right torque vectoring and avoid the contradiction between stability and energy saving. First, considering the motor efficiency, the vehicle's total torque is optimally distributed to the front and rear axles based on model predictive control. Then, based on the front/rear axle distribution ratio, the left/right torque vectoring is revised to produce a suitable additional yaw moment to improve the handling stability. A sliding mode controller is designed to track the reference yaw rate calculated from a nonlinear reference model. The nonlinear reference model is more suitable for extreme conditions due to the accurate reflection of the nonlinear characteristics. A suitable additional yaw moment can ensure vehicle stability and avoid excessive energy consumption due to vehicle instability. The simulation and hardware-in-the-loop experimental results demonstrate that the proposed control strategy can reduce energy consumption while ensuring vehicle stability.