Stringent requirements for high fuel economy and energy efficiency mandate using increasingly complex vehicle thermal systems in most types of electrified vehicles (xEVs). Enabling the maximum benefits of such complex thermal systems under the full envelope of their operating modes demands designing complex thermal control systems. This is becoming one of the most challenging problems for electrified vehicles. Typically, the thermal systems of such vehicles have several modes of operation, constituting nonlinear multiple-input/multiple-output (MIMO) dynamic systems that cannot be efficiently controlled using classical or rule based strategies. This paper covers the different steps towards the design of a model-based control (MBC) strategy that can improve the overall performance of xEV thermal control systems. To achieve the above objective, the latter MBC strategy is applied to control cooling of the cabin and high voltage battery. First, a plant model representative of a real vehicle thermal dynamics is developed in Amesim®1D Software. In order to design the model-based controller, the plant model is then utilized to obtain a linear mathematical model using system identification methods. In virtue of its suitability for multivariable systems and its low computational cost, the Linear-Quadratic-Gaussian (LQG) controller is utilized to meet energy efficiency and regulation performance objectives. The robustness against the external disturbances as well as structural uncertainties is demonstrated through rigorous simulations for the considered approach.
