ALL-WHEEL DRIVE ELECTRIC VEHICLE MODELING AND PERFORMANCE OPTIMIZATION 2019-36-0197
Electrification of the powertrain is one of the most promising trends in the automotive industry. Among the novel architectures, this paper aims to study the latent advantages provided by in-wheel motors, particularly an All-Wheel-Drive powertrain composed by four electric machines directly connected to each wheel-hub of a high performance vehicle. Beyond the well-known packaging advantage allowed by the in-wheel motor, the presence of four independent torque sources allows more flexible and complex control strategies of torque allocation. The study explores three different control modules working simultaneously: torque vectoring, regenerative braking and energy efficiency optimization protocol. The main objectives of the project are: improving handling, measured through the lap time of the virtual driver in a simulated track, and enhance energy efficiency, assessed by the battery state of charge variation during standard events. The torque vectoring strategy is based on a feedback PID controller working in parallel to a feedforward logic that predict the desired behavior based on the driver demands (such as steering angle) and vehicle states (chassis accelerations and velocities). The regenerative braking manages the demand of the driver by transferring decelerating torque from mechanical brakes to electric motors, based on their saturation condition, longitudinal slip of tires and the harmony with torque vectoring. Furthermore, a simulated ‘engine braking’ is developed and analyzed. The energy efficiency optimization protocol, allowed exclusively due to the presence of four independent electric motors, is an innovative approach to analyze the efficiency maps of the electric machines and find the best torque allocation in terms of power consumption without impact to longitudinal acceleration and yaw moment creation. The study successfully highlights the benefits of the all-wheel-drive in-wheel electric motors powertrain architecture and builds a solid platform to the development of the three control strategies and their relation, considering both the vehicle dynamics and the electric subsystem performance.