Research On Intelligent Control Strategy Of Refrigerator Truck Based On Predictive Model Of Respiratory Heat

As a major agricultural province in China,the output of fruits and vegetables has been increasing year by year,which has put forward higher requirements on China's logistics transportation,especially cold chain transportation.At the same time,the rapid development of the Internet+cold chain model has increased the demand for cold chain transportation in China,while China's cold chain logistics transportation still has a large gap in technology and circulation rate compared with foreign countries.According to the national conditions of cold chain transportation in China,short-distance refrigerated truck transportation is an important way in cold chain transportation.In the research of refrigerated trucks,the main problems addressed are to reduce the energy consumption of refrigerated trucks,and to ensure the quality of the products during transportation.The main energy consumption problem of refrigerated trucks is refrigeration and air conditioning.Being able to accurately calculate the heat load of refrigerated trucks is the key to accurately regulate the cooling air speed of refrigeration air conditioners and ensure the quality of product transportation.Therefore,based on the above problems,this article studies the refrigerated truck from the following aspects:(1)Respiratory heat is an important component of heat load during refrigerated truck transportation,and respiration rate is a physical parameter that characterizes respiratory heat.Taking potato as a research object,the oxygen consumption and carbon dioxide generation of potatoes at different temperatures were experimentally studied,and the formula was converted into a breathing rate.Based on the respiratory rate values obtained from the experimental data,the maximum respiratory rate and the dependence of respiratory entropy on temperature were analyzed.Prediction models of potato respiration rate at different temperatures were established by enzyme kinetic model,first-order regression model and SVR model.The accuracy of several prediction models is analyzed,and the results show that the SVR model is more accurate in predicting potato respiratory rate.(2)Based on the established breathing rate prediction model,a formula for calculating the respiratory heat of potatoes is established.The steady-state experimental data of potato at three temperatures of 0?,12?,and 20?,and the transient experimental data of 0? to 20? and ? to 0? were obtained through the incubator temperature experiment.Establish a three-dimensional calculation model of the incubator.Based on the experimental data and respiratory heat calculation formula,simulate the temperature change of the incubator during transient and steady state calculations.By comparing the simulation and experimental data,verify the practicability and validity of the established thermal model accuracy.Qualitative analysis of temperature changes of potatoes under natural convection.(3)Taking a refrigerated truck as a research object,analyze the influencing factors of the thermal load of the refrigerated truck,and establish a thermal load calculation model of the refrigerated truck based on the theoretical formula,and analyze the vehicle speed,ambient temperature,radiation,respiratory heat and leakage Calculation of calories.Then,based on the established mathematical model of heat load and the corresponding cooling wind speed,a training sample of BP neural network is established.The training sample is randomly processed and trained to obtain the cooling wind speed test result of the refrigerated vehicle based on BP neural network.It shows that the BP neural network has higher accuracy in real-time control of the cooling wind speed of refrigerated trucks.