Examenspresentation av Max Liljeqvist

Examiner: Torsten Wik

Abstract:
Battery electric vehicles (BEVs) are increasingly used for the electrification of the transport sector. It is of great importance to improve vehicle range and lifetime of system components to remain competitive and ensure customer satisfaction. Control strategies aimed at reducing overall energy usage and minimizing component wear are actively being researched. This thesis suggests and simulates a model-based receding horizon control strategy for the thermal system of a battery electric heavy duty truck. The objective is to to track reference temperatures of the electric storage system (ESS) and motor drive systems (MDS) while minimizing actuator power such as heat pumps, fans, pumps and valves. Particularly, there is a focus on the mathematical modelling of dynamic coupling between the thermal loops of the ESS and MDS. The system dynamics are captured using process engineering methods including control volume analysis and heat exchanger modelling. The system has a high number of degrees of freedom. An optimal control problem is then formulated by utilizing the direct collocation method. Simulation results indicate that the final receding horizon controller improves energy usage as well as reference tracking performance by effectively anticipating future disturbances. While there is potential for developing more accurate system models compared to the real-life system, the suggested control structure is a solid foundation for future improvements.

Welcome!
Max and Torsten