Genetic-Algorithm-Based Controlling of Microcontact Distributions to Minimize Electrical Contact Resistance

Abstract

When two large conductors are in contact over a finite area, the real contact area is determined by the number of clusters of microcontacts where the positions of the clusters are determined by the large-scale waviness of the surface. In addition, the microcontacts are influenced by the small-scale surface roughness. It is widely recognized that the constriction resistance is determined partly by the number and size of the microcontacts and partly by their grouping into clusters. This paper focuses on a parameter study and on the design of the microcontact clusters in terms of the electrical contact resistance (ECR). This paper investigates the positioning and/or sizing optimization of microcontact spots in order to minimize the ECR. The optimal solutions are obtained by a novel method of a real-coded genetic-algorithm implemented with a subpopulation-based selection method and a normal-distribution-probability-based crossover. Also, this paper emphasizes the advantage of the formal optimization method when a total contact area limitation is imposed as a constraint.