Optimization Design of Shelter Temperature Control based on Neural Network and NSGA-Ⅱ Algorithm
Considering the thermal environment influence of heat transfer outside the shelter and the power load of the e-lectronic equipment in the shelter,we took the layout of the car air conditioner and the air supply angle as design variables,and took the withstand temperature of electronic equipment in the shelter and occupant comfort as the objective function,and BP neural network mapping relationship between variables and objective was established.By using no-dominated sorting genetic algorithm,the optimization of airflow layout and ambient temperature gradient were done,and we achieved Pareto front solution.The optimization results showed that under the premise of constant cooling power,the optimal solution set was mainly concentrated in the air conditioner close to the electronic equipment.This method saved the simulation optimiza-tion cost,and had important engineering guiding significance for the temperature and flow field environment control in the shelter.
thermal environment in shelteranalogue simulationBP neural networkNSGA-Ⅱ algorithmair-condi-tioners
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