Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

June 7, 2024


Pages


DOI

Article

Intelligent design of cold storage room system based on low temperature process

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Authors

Juntong Yang Affiliation:
Shanxi Vocational & Technical College of Finance & Trade, Taiyuan, Shanxi, 030000, China.


Abstract

In this study, we address the intelligent design requirements of a cold storage system by developing a monitoring module for operational oversight, setting up the requisite hardware and software operating environment, and establishing a three-dimensional digital twin-based intelligent decision-making system with the digital twin model serving as the core framework. In order to seek the best path for the operation of the refrigeration system and achieve the lowest energy consumption in the refrigeration system, the dynamic planning algorithm is used to configure the refrigeration system power-consuming equipment and analyze the energy consumption of the system unit under different θW values. For the control algorithm of the electronic expansion valve in the application of a low-temperature process in cold storage, the PID algorithm is introduced and optimized using a variable domain fuzzy control algorithm to explore the degree of system energy saving and control accuracy under the two algorithmic control methods. Under the same working conditions, the fluctuation range of the PID control effect is ± 0.8 ℃, the fluctuation range of the fuzzy PID control effect is ± 0.4 ℃, the fluctuation range of fuzzy PID control superheats is smaller, the system superheat maintenance is more stable, which is in line with the design of an intelligent system for cold storage room.


Keywords

Fuzzy PID algorithm, Digital twin model, Dynamic programming algorithm, Cold storage machine room system, 97P10


Citation

Yang, J. (2024). Intelligent design of cold storage room system based on low temperature process. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-1408
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