An integrated control strategy of path following and lateral motion stabilization for autonomous distributed drive electric vehicles

This article proposes an integrated control strategy of autonomous distributed drive electric vehicles. First, to handle the multi-constraints and integrated problem of path following and the yaw motion control, a model predictive control technique is applied to determine optimal front wheels' steering angle and external yaw moment synthetically and synchronously. For ensuring the desired path-tracking performance and vehicle lateral stability, a series of imperative state constraints and control references are transferred in the form of a matrix and imposed into the rolling optimization mechanism of model predictive control, where the detailed derivation is also illustrated and analyzed. Then, the quadratic programming algorithm is employed to optimize and distribute each in-wheel motor's torque output. Finally, numerical simulation validations are carried out and analyzed in depth by comparing with a linear quadratic regulator-based strategy, proving the effectiveness and control efficacy of the proposed strategy.

Automated summary

The proposed integrated control strategy uses model predictive control to determine optimal front wheels' steering angle and yaw moment, and employs quadratic programming algorithm to optimize torque output for each in-wheel motor. Numerical simulation validations demonstrate the effectiveness and control efficacy of the strategy when compared with a linear quadratic regulator-based strategy.