Real-time path-tracking MPC for an over-actuated autonomous electric vehicle

This paper illustrates the development of a nonlinear constrained predictive path-tracking controller, including realistic vehicle dynamics and multiple actuator inputs and its implementation in real time on an experimental vehicle platform. The controller is formulated for a particular over-actuated vehicle equipped with Torque Vectoring (TV) as well as All-Wheel-Steering (AWS) functionalities, which allow for the enhanced control of vehicle dynamics. The proposed Nonlinear Model Predictive Controller (NMPC) takes into account the nonlinearities in vehicle dynamics across the range of operation up to the limits of handling as dictated by the adhesion limits of the tyres. In addition, crucial constraints regarding the actuators’ physical limits are included in the formulation. The performance of the controller is demonstrated in a high fidelity simulation environment, as well as in real-time on a test vehicle, during the execution of demanding driving scenarios

Direct yaw moment control for electric vehicles with independent motors

Direct Yaw Moment Control (DYC) systems generate a corrective yaw moment to alter the vehicle dynamics by means of active distribution of the longitudinal tire forces, and they have been proven to be an effective means to enhance the vehicle handling and stability. The latest type of DYC systems employs the on-board electric motors of electric or hybrid vehicles to generate the corrective yaw moment, and it has presented itself as a more effective approach than the conventional DYC schemes. In this thesis, a wide range of existing vehicle dynamics control designs, especially the typical DYC solutions, are investigated. The theories and principles behind these control methods are summarized, and the features of each control scheme are highlighted. Then, a full vehicle model including the vehicle equivalent mechanical model, vehicle equations of motion, wheel equation of motion and Magic Formula tire model is established. Using the derived vehicle equations of motion, the fundamental mathematical relationships between the corrective yaw moment produced by the DYC system and the crucial vehicle states (the yaw rate and vehicle side-slip) are derived. Based on these relationships, two DYC systems are proposed for electric vehicles (or hybrid vehicles) by means of individual control of the independent driving motors. These two systems are designed to track the desired yaw rate and vehicle side-slip, respectively. Extensive simulation results verify that these systems are effective in improving vehicle dynamic performance. Apart from the two systems that adjust yaw rate or vehicle side-slip individually, a novel sliding mode DYC scheme is proposed to regulate both vehicle states simultaneously, aiming to better enhance the vehicle handling and stability. This control scheme guarantees the simultaneous convergences of both the yaw rate and vehicle side-slip errors to zero, and eliminates the limitations presented in the common sliding mode DYC solutions. Comparative simulation results indicate that the vehicle handling and stability are significantly enhanced with the proposed DYC system on-board. Also, this DYC scheme is shown to outperform its corresponding counterparts in various driving conditions