Reliability and cost optimization of power electronic devices considering the component failure rate uncertainty

The objective of this paper is to present an efficient methodology to obtain the optimal system structure for power electronic devices using various component types, while considering the constraints on reliability and cost. The component failure rate uncertainty is taken under consideration and it is modeled with two alternative probability distribution functions. The Latin Hypercube Sampling method is used to simulate the probability distributions and the efficiency of this stratified sampling method is compared with the typical Monte Carlo analysis method. The optimization methodology being used was the simulated annealing algorithm because of its flexibility to be applied in various system types with various constraints and its efficiency in computational time. The developed methodology was applied to a power electronic device and the results were compared with the results of the complete enumeration of the solution space. The stochastic nature of the top solutions was sampled extensively and the robustness of the optimization methodology was demonstrated. Finally, a typical power electronic device is used as a case study and the obtained results are presented.