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Dynamic modeling and control of a direct expansion air conditioning system using artificial neural network

Author

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  • Li, Ning
  • Xia, Liang
  • Shiming, Deng
  • Xu, Xiangguo
  • Chan, Ming-Yin

Abstract

An artificial neural network (ANN)-based dynamic model for an experimental variable speed direct expansion (DX) air conditioning (A/C) system has been developed, linking the indoor air temperature and humidity controlled by the DX A/C system with the variations of compressor and supply fan speeds. The values of average relative error (ARE) and maximum relative error (MRE) when validating the ANN-based dynamic model developed under three different input patterns were 0.33%, 0.27%, 0.27% and 0.89%, 0.99%, 1.15%, respectively, indicating the high accuracy of the ANN-based dynamic model developed. An ANN-based controller was then developed for controlling the indoor air temperature and humidity simultaneously by varying the compressor speed and supply fan speed in a space served by the experimental DX A/C system. The controllability tests including command following test and disturbance rejection test were carried out using the experimental DX A/C system, and the test results showed that the ANN-based controller developed was able to track the changes in setpoints and to resist the disturbances.

Suggested Citation

  • Li, Ning & Xia, Liang & Shiming, Deng & Xu, Xiangguo & Chan, Ming-Yin, 2012. "Dynamic modeling and control of a direct expansion air conditioning system using artificial neural network," Applied Energy, Elsevier, vol. 91(1), pages 290-300.
    • Handle: RePEc:eee:appene:v:91:y:2012:i:1:p:290-300
    DOI: 10.1016/j.apenergy.2011.09.037
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    References listed on IDEAS

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    Cited by:

    1. Mei, Jun & Xia, Xiaohua, 2017. "Energy-efficient predictive control of indoor thermal comfort and air quality in a direct expansion air conditioning system," Applied Energy, Elsevier, vol. 195(C), pages 439-452.
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    3. Yan, Huaxia & Pan, Yan & Li, Zhao & Deng, Shiming, 2018. "Further development of a thermal comfort based fuzzy logic controller for a direct expansion air conditioning system," Applied Energy, Elsevier, vol. 219(C), pages 312-324.
    4. Flavio Muñoz & Ramon Garcia-Hernandez & Jose Ruelas & Juan E. Palomares-Ruiz & Carlos Álvarez-Macías, 2022. "Optimal Operation for Reduced Energy Consumption of an Air Conditioning System Using Neural Inverse Optimal Control," Mathematics, MDPI, vol. 10(5), pages 1-15, February.
    5. Ascione, Fabrizio & Bellia, Laura & Capozzoli, Alfonso, 2013. "A coupled numerical approach on museum air conditioning: Energy and fluid-dynamic analysis," Applied Energy, Elsevier, vol. 103(C), pages 416-427.
    6. Lim, Dae Kyu & Ahn, Byoung Ha & Jeong, Ji Hwan, 2018. "Method to control an air conditioner by directly measuring the relative humidity of indoor air to improve the comfort and energy efficiency," Applied Energy, Elsevier, vol. 215(C), pages 290-299.
    7. Fan, Hongming & Shao, Shuangquan & Tian, Changqing, 2014. "Performance investigation on a multi-unit heat pump for simultaneous temperature and humidity control," Applied Energy, Elsevier, vol. 113(C), pages 883-890.
    8. Yan, Huaxia & Xia, Yudong & Deng, Shiming, 2017. "Simulation study on a three-evaporator air conditioning system for simultaneous indoor air temperature and humidity control," Applied Energy, Elsevier, vol. 207(C), pages 294-304.
    9. Miklos Kassai, 2019. "Energy Performance Investigation of a Direct Expansion Ventilation Cooling System with a Heat Wheel," Energies, MDPI, vol. 12(22), pages 1-16, November.
    10. Ma, Nan & Aviv, Dorit & Guo, Hongshan & Braham, William W., 2021. "Measuring the right factors: A review of variables and models for thermal comfort and indoor air quality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    11. 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.
    12. Chen, Wenjing & Chan, Ming-yin & Weng, Wenbing & Yan, Huaxia & Deng, Shiming, 2018. "An experimental study on the operational characteristics of a direct expansion based enhanced dehumidification air conditioning system," Applied Energy, Elsevier, vol. 225(C), pages 922-933.
    13. Qinghong Peng & Qungui Du, 2016. "Progress in Heat Pump Air Conditioning Systems for Electric Vehicles—A Review," Energies, MDPI, vol. 9(4), pages 1-17, March.
    14. 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).
    15. Kang, Won Hee & Lee, Jong Man & Yeon, Sang Hun & Park, Min Kyeong & Kim, Chul Ho & Lee, Je Hyeon & Moon, Jin Woo & Lee, Kwang Ho, 2020. "Modeling, calibration, and sensitivity analysis of direct expansion AHU-Water source VRF system," Energy, Elsevier, vol. 199(C).
    16. Mei, Jun & Xia, Xiaohua & Song, Mengjie, 2018. "An autonomous hierarchical control for improving indoor comfort and energy efficiency of a direct expansion air conditioning system," Applied Energy, Elsevier, vol. 221(C), pages 450-463.

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