Title: Temperature and humidity optimisation control of cold chain vehicle carriage based on Gray Wolf algorithm

Authors: Yulong Wan; Xinchun Li

Addresses: School of Economics and Management, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, China; School of Business, Jiangsu Vocational College of Electronics and Information, Huai'an, Jiangsu 223003, China ' School of Economics and Management, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, China

Abstract: There are some problems in the traditional temperature and humidity control of cold chain transportation vehicles, such as poor control effect, poor real-time control, etc. The paper introduces Descartes coordinate system to construct the air motion tensor model in the carriage of cold chain transportation vehicles. The influence parameters of temperature and humidity of cold chain transport vehicles are divided into different temperature and humidity parameters. The Gray Wolf algorithm is used to search for the optimal solution of humidity influence parameters, and different wolf fitness models are constructed to determine the optimal solution of parameters to realise optimal control. The comparison shows that: the control deviation of temperature and humidity of cold chain transport vehicle compartment is always lower than 0.4, and the control efficiency coefficient is higher than 0.9.

Keywords: cold chain transport vehicle; compartment temperature and humidity; Gray Wolf algorithm; tensor model; temperature and humidity comprehensive parameters; comfort index.

DOI: 10.1504/IJVD.2022.128010

International Journal of Vehicle Design, 2022 Vol.89 No.1/2, pp.24 - 37

Received: 21 Jan 2021
Accepted: 06 Jul 2021
Published online: 04 Jan 2023 *

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