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.
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