Model Predictive Control Strategies for Use in Battery Electric Vehicles

Authors

Prof. Dr.-Ing. S. Pischinger, P. Schutzeich  MSc, Chair of Thermodynamics of Mobile Energy Conversion Systems (tme), RWTH Aachen University; Dr.-Ing. D. Hemkemeyer, FEV, Aachen:

Year

2023

Print Info

Production/Publication ÖVK

Summary

In this paper, the application of model predictive control (MPC) approaches for the thermal management of battery electric vehicles (BEV) is investigated. For this purpose, two applications, the battery conditioning for the targeted preparation for charging events and the cabin conditioning, are used as examples.

In a first step, the publication presents the basic principles used to formulate the optimization problem. Basic terminology and the specific features for the design of a MPC are explained.

In the following chapter, the functional architecture and the modelling of the system dynamics for the MPC will be discussed. The latter is the core of model predictive control and is decisive for the performance of the approach. For this reason, the scope and methodology for modelling the system dynamics will be examined in more detail. This is done separately for battery conditioning and cabin air conditioning.

Finally, the performance of the control strategies for both application examples is examined in comparison to a rule-based approach. Here, the MPC shows its full potential. For the battery conditioning, an improvement of the range of 2.94 % could be achieved with a simultaneous reduction of charging of 10.20 %. For cabin air conditioning, the integration of heating surfaces into an MPC strategy is evaluated. Additional energy saving potentials of up to 16.7 % could be identified here.

ISBN

978-3-9504969-2-5