Temperature Control Optimization for Heat Pipe Based on Particle Swarm Optimization

In order to optimize the parameters of heat pipe temperature control during the thermal vacuum test, the particle swarm optimization (PSO) algorithm is used to tune the PID control parameters. According to the heat response data of heat pipe, the temperature control system model of heat pipe is established. The time integral of the absolute value of the control error is selected as the objective function. The parameters of the particle swarm optimization algorithm are compared with those of the attenuation curve method, and compares the control result based on parameter from PSO and the attenuation curve method. The simulation result shows that the optimization algorithm can accelerate the convergence rate. The setting time of system is cut down from 10h to 3.7h, and the maximum overshoot decreases from 16.7% to 1.4%. The dynamic performance of system is effectively improved.

I. Introduction

These are Heat pipe is one of the main means of spacecraft thermal control, especially the high-capacity communication satellites. Because of its large thermal power consumption and high power density of transponders, a large number of heat pipes are used on the satellites to form a heat pipe network system to solve the problem of temperature control^[1]. In thermal vacuum test, the satellites are divided into zones for temperature control, which are divided by the location of critical equipment. Generally, the temperature control of the key equipment is realized by controlling the temperature of the heat pipe.