Model Predictive Control of a Hybrid Thermal Management System using State of Charge Estimation

In this paper, we consider the problem of controlling a hybrid thermal management system (TMS) in which thermal energy may be temporarily rejected to a phase change material (PCM)-based energy storage device. We define the state of charge (SOC) as the amount of thermal energy that can yet be absorbed by the PCM at that instant. The hybrid TMS control objective is to optimally determine when and by how much heat should be rejected to (discharge) the PCM, or removed from (recharge) it during the operation, while meeting some system performance specification. In order to design the feedback control scheme, we require knowledge of the temperature and/or melt fraction across the PCM volume to determine SOC at each sampling instant. Using a graph-based diffusion model of the heat transfer in the PCM volume, we show that the temperature distribution across the PCM may be estimated using a State-Dependent Riccati Equation Estimator (SDRE). Thus, we develop a model predictive control (MPC) scheme in which the SDRE is used to estimate the temperature distribution, and hence the SOC. The MPC is designed to minimize the system’s pump energy requirement, maximize the SOC at the end of the operation period, and satisfy critical temperature constraints. Through simulation results, we demonstrate the importance of the SOC estimate in achieving control objectives in a hybrid thermal management system.