Development of a traction controller for drivability improvement of electric vehicles

This Ph.D. project aims at developing anti-jerk and traction controllers for the drivability improvement of fully electric lorries. The target vehicles will be employed for urban and extra-urban deliveries, and will face a wide range of climate and road conditions: from dry and flat tarmac to snowy uphill roads. The controllers will be tested on two different demonstrators. The first one is a two-wheel-drive vehicle with a central electric motor, a single gear transmission, an open differential connected to the wheels through half-shafts and constant velocity joints. The second one is a four-wheel-drive vehicle that uses the previous drivetrain configuration on both the front and rear axles.
The anti-jerk controller will be based on nonlinear explicit model predictive control technology, and will be compared with five different control structures from the literature: i) a pure feedforward controller; ii) a feedback controller based on the high frequency component of the motor speed; iii) a system combining a feedforward controller with a feedback disturbance observer; iv) a feedback controller based on the drivetrain torsion rate; and v) a feedback controller based on the estimated drivetrain torque.
Within the traction controller development, the benchmark will be set by a PID slip based algorithm, which will be compared with a novel nonlinear explicit model predictive traction controller. The Centre for Automotive Engineering of the University of Surrey has experience in the field of model predictive control, as it is one of the few research groups to have developed a toolbox for the design of explicit nonlinear model predictive controllers. This toolbox has been exploited for the preliminary development of a traction controller for an electric vehicle with in-wheels motors, which represents a novelty in the literature. Nevertheless, such controller is still a proof of concept, as it is not robust with respect to tyre-road parameter variations. This Ph.D. project targets the enhancement of the level of robustness and technology readiness of the controller, to achieve an industrially implementable system.
The combination of innovative controllers and their comprehensive assessment on the electric vehicle demonstrators provided by the industrial partners will allow the publication of the results in quartile 1 journals in the subject areas of mechanical and automotive engineering. Furthermore, the activity will include an extensive survey on anti-jerk controllers, as the literature misses a thorough review of this topic.