Optimization of Control Parameters of Vehicle Air-Conditioning System for Maximum Efficiency 2020-01-1242
Modern automotive heating, ventilation, and air-conditioning (HVAC) systems have multiple and often redundant actuators. Design of a control system that optimally synthesizes multiple control actions while satisfying control set points and system hardware-related constraints is necessary to maximize HVAC efficiency. To this end, an optimization approach to control system design is proposed in this paper and demonstrated for a generic air-conditioning (A/C) system. The paper first outlines a nonlinear 12th-order A/C dynamics model based on the moving-boundary method. Then, the A/C control system is defined, which combines feedback controllers commanding the compressor speed and expansion valve opening, and open-loop actions of condenser and blower fans. Next, a three-stage, multi-objective genetic algorithm-based approach of control system optimization is proposed. The first-stage is aimed at finding a rough estimate of all control inputs, which maximizes the A/C system efficiency while satisfying relaxed control set point constraints. In the second stage, the closed-loop controller parameters are optimized for the operating point obtained in the first stage with the aim to provide a favorable trade-off between the control error suppression and control effort. The third stage includes refined optimization of fans open-loop actions to maximize efficiency, where firmer thermal comfort and safety-related constraints are provided by feedback controllers. Finally, the optimization procedure is carried out for multiple control set points to provide control parameter maps, which are aimed to be used in the form of a gain-scheduling algorithm. Analysis of optimization computational efficiency shows that a substantial improvement is achieved with the proposed, comprehensive three-stage approach when compared to using only the first stage one.