Coefficients identification in electronic system cooling simulation through genetic algorithm

An inverse procedure is presented based on the improved genetic algorithm and is applied in electronic system cooling simulation to identify heat transfer coefficients through temperature distributions. This procedure includes forward and inverse procedures. Commercial software, I-deas (ESC and TMG), is adopted for forward computation and uniform-micro-genetic algorithm (μGA) is for inverse procedure. μGA is global optimization but its slow convergence affects its computational efficiency. A search domain narrowing operation is proposed to speed up the convergence so that the whole computational procedure can be carried out within an acceptable time. As an example, an electronic system cooling simulation, which includes fan cooling, water duct flow cooling and several printed circuit boards inside an electronic enclosure, is carried out and the efficiency increases approximate 33%.