Centralised yaw and lateral motion control for future electric vehicles

Abstract

The disruptive innovation in the ever-growing and developing automotive industry has centralised advanced driver assistance systems (ADAS) and autonomous driving (AD) concepts. The innovations are only enhanced by the rapid electrification of powertrain systems due to strict environmental regulations, allowing for extended functionalities in vehicle motion control. This master’s thesis investigates the possibilities of vehicle motion control systems for future electric vehicles using an over-actuated vehicle with four individual electric motors in both simulations and real-time in a test vehicle. Three different concepts for yaw and lateral motion control are developed. The first concept is geometric path tracking, where two controllers are developed to control the vehicle’s lateral motion in an AD scenario. The second concept is a steer by torque vectoring controller where the lateral motion of the vehicle is controlled using only differential torque to act as a backup safety system in case of steering actuator failures. Finally, an energy-efficient torque vectoring controller is developed to evaluate the possibility of reducing the vehicle’s energy consumption by optimising the torque allocation. The controllers were developed in Matlab Simulink and evaluated in a simulation environment consisting of a vehicle model of the test vehicle in IPG CarMaker. The comparison between the two path tracking controllers, i.e. the Pure Pursuit and the Stanley controller, were evaluated based on precision, comfort and robustness. The steer by torque vectoring controller was developed with experimental data from simulations and the test vehicle to design a look-up table for the steering capability. Finally, to develop the energy-efficient torque vectoring controller, an offline optimisation strategy was used to construct a rule-based and a look-up table method for the torque allocation. The work proved that the Pure Pursuit controller was superior to the Stanley controller and could remain within limits given by regulations, both in the simulations and the test vehicle. Integrated with the steer by torque vectoring controller, the vehicle’s lateral motion could be controlled using only differential torques. The possibility of reducing energy consumption by optimising the torque allocation was highly dependent on compromising the precision performance of the path tracking and the torque allocation. With tuning, the controllers could be combined to reduce the vehicle’s energy consumption by 1.14 %.