Active systems for drivability improvement of electric vehicles

Vehicle drivability includes all the driver’s complex perceptions related with the longitudinal vehicle motion, including comfort and perceived safety. Vehicle drivability is strongly affected by the vehicle body longitudinal acceleration, ax. Oscillations in ax are uncomfortable and are typically caused by drivetrain torsional oscillations. Also, electric drivetrains are, usually, more prone than internal combustion engine drivetrains to generate torsional oscillations in the drivetrain. An-anti jerk controller aims to alleviate, or completely remove, the drivetrain torsional vibrations, through an opportune modification of the motor torque requested by the driver. Anti-jerk control structures have been extensively reviewed and a novel real-time capable explicit nonlinear model predictive anti-jerk controller has been developed. Different prediction models have been compared to select the most suitable. The novel anti-jerk controller has been assessed in an experimentally validated simulation environment, and compared with five controllers, selected from the literature. All controllers have been tuned with an objective routine. The main conclusions are: i) the MPC controller performed well, excelling in the case of injection in the system of measurement noise. Its main drawback is the requirement of an accurate estimation of the drivetrain torsion. ii) the anti-jerk system adopting the measured wheel speed in their control structure gives a tangible advantage to the controller performance. iii) the controller based on the vibrating component of the motor speed, which is the system usually adopted on production vehicles, provides excellent robustness with respect to external disturbances, but its comfort indicators are usually worse than the comfort indicators of the more advanced control structures. To increase the drivability during cornering a novel real-time capable nonlinear explicit model predictive traction controller has been developed. The study demonstrates how the inclusion of a combined slip tyre model in the prediction model enhances the performance of the traction controller in cornering conditions