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Optimal energy-efficient predictive controllers in automotive air-conditioning/refrigeration systems

Huang, Yanjun, Khajepour, Amir, Bagheri, Farshid, Bahrami, Majid
Applied energy 2016 v.184 pp. 605-618
case studies, controllers, energy efficiency, frost, heat, models, temperature
This paper presents several robust model predictive controllers that improve the temperature performance and minimize energy consumption in an automotive air-conditioning/refrigeration (A/C-R) system with a three-speed and continuously-varying compressor. First, a simplified control-oriented model of the A/C-R system is briefly introduced. Accordingly, a discrete Model Predictive Controller (MPC) is designed based on the proposed model for an A/C-R system with a three-speed compressor. A proper terminal weight is chosen to guarantee its robustness under both regular and frost conditions. A case study is conducted under various heating load conditions. Two hybrid controllers are made, which combine the advantages of both the on/off controller and discrete MPC such that they will be more efficient under any ambient heating condition. In addition, a continuous MPC is developed for systems with continuous variable components. Finally, the experimental and simulation results of the new controllers and the conventional on/off controller are provided and compared to show that the proposed controllers can save up to 23% more energy.