Feedback Linearization-based Thermal Control Strategy for Electrified Vehicles

Modern electric vehicles (EVs) have complex thermal systems due to stringent energy efficiency requirements. The thermal systems of such vehicles have highly nonlinear and strongly coupled dynamics as they operate under various thermal modes. Extracting the maximum performance benefits from such complex systems requires elaborate and modern control strategies since classic and rule-based strategies cannot effectively control them. This is becoming a challenge for electric vehicles. Feedback linearization is a control approach that is designed based on the mathematical model of the system. It has the advantage of requiring low computational resources, specifically, low-computational-time and low-memory usage when compared to control strategies such as Model Predictive Control (MPC).

This paper presents a feedback linearization controller that is designed using a nonlinear physics-based model for cabin heating of an electric vehicle. The nonlinear physics-based model is derived from cabin heating governing equations and is correlated with a 1-D model of the thermal systems of the target vehicle. The controller is composed of an Input-Output Feedback Linearization and a Proportional-Integral control. The controller is implemented in an onboard embedded Electronic Control Unit (ECU) and tested on an electrified vehicle. The performance of the classic or Rule-Based controller and the Feedback-Linearization controller are compared.