Development of a traction controller for drivability improvement of electric vehicles

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Title
Development of a traction controller for drivability improvement of electric vehicles

CoPED ID
fe157532-31cf-4c92-a8c8-c353784752ca

Status
Closed


Value
No funds listed.

Start Date
Jan. 1, 2017

End Date
Dec. 31, 2019

Description

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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.

Patrick Gruber SUPER_PER
Aldo Sorniotti SUPER_PER

Subjects by relevance
  1. Control engineering
  2. Vehicles
  3. Adjustment systems
  4. Motor vehicles
  5. Automotive engineering
  6. Electric vehicles
  7. Electric cars
  8. Motors and engines
  9. Control technology
  10. Adjustment
  11. Steering systems

Extracted key phrases
  1. Novel nonlinear explicit model predictive traction controller
  2. Traction controller development
  3. Explicit nonlinear model predictive controller
  4. Jerk controller
  5. Feedback controller
  6. Pure feedforward controller
  7. Innovative controller
  8. Nonlinear explicit model predictive control technology
  9. Electric vehicle demonstrator
  10. Preliminary development
  11. Central electric motor
  12. Target vehicle
  13. Drive vehicle
  14. Electric lorry
  15. Drivability improvement

Related Pages

UKRI project entry

UK Project Locations