Application of multivariable adaptive control to automotive air conditioning systems

This paper presents the application of a multivariable adaptive control strategy to a typical automotive air conditioning system. First, an experimentally validated physical model for the air conditioning cycle is introduced. This is followed by the application of a multi-input multi-output (MIMO) parameter estimation algorithm to recursively identify an equivalent discrete time state space model of the system. A Linear Quadratic Regulator (LQR) design is implemented on the estimated model with the objectives of reference tracking and disturbance rejection. Simulation studies are performed to explore the idea of modulating the electronic expansion valve opening and air flow rate over the evaporator for controlling the efficiency and capacity of a general automotive air conditioning unit. The results demonstrate the efficacy of the MIMO controller for these objectives.