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

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  • Huang, Yanjun
  • Khajepour, Amir
  • Bagheri, Farshid
  • Bahrami, Majid

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.

Suggested Citation

  • Huang, Yanjun & Khajepour, Amir & Bagheri, Farshid & Bahrami, Majid, 2016. "Optimal energy-efficient predictive controllers in automotive air-conditioning/refrigeration systems," Applied Energy, Elsevier, vol. 184(C), pages 605-618.
    • Handle: RePEc:eee:appene:v:184:y:2016:i:c:p:605-618
    DOI: 10.1016/j.apenergy.2016.09.086
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    Cited by:

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    2. Jia, Chunchun & Li, Kunang & He, Hongwen & Zhou, Jiaming & Li, Jianwei & Wei, Zhongbao, 2023. "Health-aware energy management strategy for fuel cell hybrid bus considering air-conditioning control based on TD3 algorithm," Energy, Elsevier, vol. 283(C).
    3. Zhao, Yihang & Dan, Dan & Zheng, Siyu & Wei, Mingshan & Xie, Yi, 2023. "A two-stage eco-cooling control strategy for electric vehicle thermal management system considering multi-source information fusion," Energy, Elsevier, vol. 267(C).
    4. Huang, Yanjun & Khajepour, Amir & Ding, Haitao & Bagheri, Farshid & Bahrami, Majid, 2017. "An energy-saving set-point optimizer with a sliding mode controller for automotive air-conditioning/refrigeration systems," Applied Energy, Elsevier, vol. 188(C), pages 576-585.
    5. Bai, Hongyu & Zhu, Jie & Chen, Xiangjie & Chu, Junze & Cui, Yuanlong & Yan, Yuying, 2020. "Steady-state performance evaluation and energy assessment of a complete membrane-based liquid desiccant dehumidification system," Applied Energy, Elsevier, vol. 258(C).
    6. Qi, Ronghui & Li, Dujuan & Zhang, Li-Zhi, 2017. "Performance investigation on polymeric electrolyte membrane-based electrochemical air dehumidification system," Applied Energy, Elsevier, vol. 208(C), pages 1174-1183.
    7. Whei-Min Lin & Chung-Yuen Yang & Ming-Tang Tsai & Hong-Jey Gow, 2019. "The Optimized Energy Saving of a Refrigerating Chamber," Energies, MDPI, vol. 12(10), pages 1-16, May.
    8. Ma, Junhai & Hou, Yaming & Wang, Zongxian & Yang, Wenhui, 2021. "Pricing strategy and coordination of automobile manufacturers based on government intervention and carbon emission reduction," Energy Policy, Elsevier, vol. 148(PA).
    9. Huang, Xianghui & Li, Kuining & Xie, Yi & Liu, Bin & Liu, Jiangyan & Liu, Zhaoming & Mou, Lunjie, 2022. "A novel multistage constant compressor speed control strategy of electric vehicle air conditioning system based on genetic algorithm," Energy, Elsevier, vol. 241(C).

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