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Integrated model predictive and torque vectoring control for path tracking of 4-wheel-driven autonomous vehicles

Integrated model predictive and torque vectoring control for path tracking of 4-wheel-driven autonomous vehicles

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In this study, an integrated path tracking control framework is proposed for the independent-driven autonomous electric vehicles. The proposed control scheme includes three parts: the non-linear model predictive path tracking controller, the lateral stability controller, and the optimal torque vectoring controller. Firstly, the upper bound speed limit is regulated based on the known curvature and adhesion coefficient of the road to prevent the tyre saturation. The model predictive controller generates the steering angle and the desired longitudinal force for path tracking. Simultaneously, the lateral stability controller calculates the desired yaw moment to balance the vehicle stability and motility under different situations. Finally, the optimal torque vectoring controller distributes the wheel torques to generate the desired longitudinal force and yaw moment. Three test cases are designed and verified based on a Carsim/Simulink platform to evaluate the control performance. The test results illustrate that the proposed control framework has satisfactory path tracking performance, and the desired balance between vehicle mobility and stability is achieved under different road conditions.

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