基于I-PSO算法和Simulink的湿式离合器优化设计

为提高湿式离合器的轻便性和可靠性，提出了一种I-PSO算法与MATLAB/Simulink相结合的湿式离合器优化设计新方法。对湿式离合器进行动力学分析，并基于MATLAB/Simulink搭建湿式离合器动力传递的仿真模型。引入模拟退火算法中对粒子进行扰动的思想对改进的粒子群算法再度进行改进，并基于某测试函数验证了算法改进的效果，选择离合器的滑磨功与体积为优化目标。最终联合改进粒子群算法与MATLAB/Simulink中建立的湿式离合器仿真模型对某具体型号湿式离合器进行多目标优化设计。结果表明，改进后的粒子群算法在寻优的速率和精度上有一定效果；优化后的湿式离合器与原设计相比，总目标函数缩小约40.12%，滑磨功减小了约61.8%，优化效果明显。

Optimal design of wet clutch based on I-PSO algorithm and Simulink

In order to improve the lightness and reliability of wet clutch, this paper proposed a new method of wet clutch optimization design based on I-PSO algorithm and MATLAB/Simulink. It carried out the dynamic analysis of wet clutch, and built the simulation model of power transmission of wet clutch based on MATLAB / Simulink. The method introduced the idea of perturbation of particles in simulated annealing algorithm to improve the improved particle swarm optimization algorithm again, and verified the effect of the improved algorithm based on a test function. It selected sliding grinding power and volume of the clutch as the optimization objective. Finally, combined with the improved particle swarm optimization algorithm and the wet clutch simulation model established in MATLAB/Simulink, it carried out the multi-objective optimization design of a specific type of wet clutch. The results show that the improved particle swarm optimization algorithm has a certain effect on the speed and accuracy of the optimization. Compared with the original design, the total objective function of the optimized wet clutch is reduced by about 40.12%, and the sliding grinding work is reduced by about 61.8%. The optimization effect is obvious.