Nonlinear optimal control of heat pumps in electric vehicles

Heat pumps can be used for thermal management of electric vehicles (EVs) in a low-cost and environmentally friendly manner. Heat pumps can exploit the heat that is diffused by the vehicle’s batteries so as to perform temperature control of the passengers cabin. A heat-pump-based thermal management system of EVs has the dual objective of (a) stabilizing temperature in the passenger cabin at the desirable levels so as to ensure the passengers’ comfort and (b) stabilizing temperature at the batteries so as to avoid degradation of the batteries’ power storage capacity and of their regenerative charging capability. So far, nonlinear model predictive control (NMPC) methods have been mainly applied for the nonlinear optimal control problem of heat pumps in EVs. In this article a novel nonlinear optimal control method is proposed for solving the nonlinear optimal control problem of heat pumps. This method is computationally simple, has clear implementation stages, and is of proven global stability. The dynamic model of the heat pump undergoes approximate linearization with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrices. Linearization takes place at each sampling instance, around a temporary operating point that is defined by the present value of the heat pump’s state vector and by the last sampled value of the control inputs vector. For the approximately linearized model of the heat pump an H-infinity stabilizing controller is designed. The feedback gains of the controller are computed through the solution of an algebraic Riccati equation, at each time step of the control method. The global stability properties of the control scheme are proven through Lyapunov analysis. Moreover, to enable state estimation-based control, the H-infinity Kalman filter is used as a robust observer. The method achieves fast and accurate tracking of reference setpoints under moderate variations of the control inputs.