A Comparative Study of Permanent Magnet Motor Cost Minimization Dedicated to Electric Traction

In this paper, we present a permanent magnet motor cost minimization dedicated to the electric traction based on a genetic algorithms (GAs) method. Our objective is to minimize this cost by taking account of certain constraints. The choice of a suitable coding is a critical element which depends largely on the genetic algorithm effectiveness. That is why we present a comparative study between two types of genetic algorithms i.e. a binary coded genetic algorithm (BCGA) and a real coded genetic algorithm (RCGA).