Optimal Energy-Efficient Predictive Controllers for Automotive Air Conditioning Systems (International Journal of Innovative Research in Computer Science & Technology, 2022)
This work provides robust model predictive  controllers for a vehicle climate control (A/C-R) system  featuring a three-speed, constantly variable compressor that  improves temperate stability while lowering energy  consumption. First, a simple control-oriented paradigm is  used to explain the A/C-R system. As a consequence, the  suggested model is used to build a discrete Variable  Structure Gamepad (MPC) for something like an A/C-R  circuit with a three-speed blower. To guarantee its longevity  in both standard and cold conditions, a sufficient terminal  weight is chosen. A case study can be carried out under  various heating load scenarios. The advantages of a on/off  microcontroller and the standalone Lpc are combined to  produce two hybrid remotes that will be more reliable in  any external temperature setting. A continuously MPC is  also being created for ecosystems with continually altering  parts. Finally, the theoretical and computational results of  the innovative regulators, and also the conclusions of the  classic on/off controller, are compared and contrasted to  demonstrate that the recommended remotes can save up to  23% more energy than the conventional on/off control  system.
Keywords: Air Conditioning Systems; Discrete MPC; Frosting; Hybrid Controller; Robust MPC