Optimization of Environmental Conditioning Equipment Based on Particle Swarm Optimization Algorithm and Genetic Algorithm

Abstract

The purpose of this paper is to systematically analyze and design the appearance of the 3-in-1 environmental conditioning device by using particle swarm optimization algorithm and genetic algorithm. Firstly, the particle swarm optimization algorithm (PSO) is applied to simulate the indoor temperature change for the placement of air conditioners, the location of the inlet and outlet, and the direction of airflow to design the optimal shapes and sizes to improve the temperature control efficiency. Second, a genetic algorithm optimization model was constructed for the relationship between the shape of the air purifier and the purification effect, aiming to determine the best design that can maximize the purification effect. Next, an optimization analysis of the shape of the humidifier is introduced, and a multi-objective optimization model for the 3-in-1 device is developed using PSO to maximize energy efficiency, comfort, and air quality. The algorithms and models used in this paper not only enhance the comprehensive performance of the device, but also provide a scientific basis for future product development and promote the innovation and application of smart home devices.