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

Yanjun Huang, Amir Khajepour, Farshid Bagheri and Majid Bahrami

Applied Energy, 2016, vol. 184, issue C, 605-618

Abstract: 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.

Keywords: Air-conditioning/refrigeration systems; Frosting; Discrete MPC; Robust MPC; Hybrid controller (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:184:y:2016:i:c:p:605-618

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DOI: 10.1016/j.apenergy.2016.09.086

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