Master Thesis Robust Optimal Vehicle Motion Control

The opportunity
The increased global average temperature and extreme weather events raise the need for immediate actions to combat climate change. Polestar is committed to driving change towards a climateneutral future with sustainable electric mobility. Electric vehicles with its increased mass pose new challenges for vehicle dynamics attributes. Active chassis systems can be used to compensate for the increased mass and give the driver a safe and exciting experience behind the steering wheel.

Industry vehicle motion controllers are often simple and robust. This means that the performance varies for different operating conditions but the controller itself is robust. These systems do not off the best performance in terms of maintaining the desired vehicle characteristics for different operating conditions e.g. change of tires different road surfaces e.t.c.

Vehicle motion controller in Academia often uses quite complex vehicle models where a lot of assumptions are made regarding the vehicle characteristics. These controllers offer superior performance compared to the simple controllers that are currently most common in the industry.

In normal driving the vehicle behavior can be accurately estimated by a linear model and can therefore be well handled with simpler control algorithms. For on limit driving e.g. evasive maneuvers the vehicle behavior is highly nonlinear and dependent on the road surface and other operating conditions.

When the nonlinear vehicle behavior is modelled accurately the stateoftheart controllers have high performance. However there is a lack of understanding regarding how robust these controllers are with respect to changes in vehicle characteristics and how these controllers can be adapted in realtime to the changing operating conditions.

This master thesis has three main goals:

• Investigate the robustness of stateoftheart vehicle motion control systems with wheel torque and angle control to different operating conditions in critical driving situations.
• Increase the robustness how the stateoftheart vehicle motion control systems by online adaption to operating conditions and vehicle parameters.
• Investigate how the state estimation and controller can be integrated to reduce the uncertainty in operating conditions and vehicle states in critical situations.

The responsibilities

• Create an MPC controller for vehicle motion control using active steering and torque control
• Investigate robustness to operating conditions
• Stretched target: Investigate how parameters and operating conditions can be estimated in real time and used to improve MPC robustness.

The ideal candidate

• M.Sc. in Vehicle Engineering Control Theory System and Mechatronics
• Good knowledge in MATLAB/Simulink
• Interest and good knowledge in vehicle dynamics
• Completed courses with a good background within optimal control and control theory
• Analytical and independent

Duration

• 20 weeks / 30 ECTS
• Starting date: Spring 2024
• Number of students: 12 students
• This position is based at our HQ in Gothenburg Sweden

The process

Attach your resume and cover letter stating your interests within the given area and your thoughts and credentials. We want your application as soon as possible but no later than . Please note that applications via email will not be accepted. Selection will be ongoing during the application period.