Application of Particle Swarm Optimization Algorithm in Power Source Thermal Transient Prediction

Abstract

This paper proposes the usage of particle swarm optimization (PSO) algorithm in identifying system unknowns for heat source thermal transient prediction in electronics device. The proposed method shortens the calculation time and removes the difficulty of unknowns' identification for thermal transient prediction question. Result shows that the RMS error is 0.81°C which indicates the majority is well predicted and the error is 5.39°C while the power has violent variance. PSO converges Req τeq in 20 iterations from 7,000 seconds of data with given each unknown 15 particles. The usage of PSO solves the system unknowns' identification issue from performance application transient and provides reliable results.