Abstract
When using ”conventional” approaches for the optimal sizing of electrical machines, the application of optimization algorithms makes it possible to search for the values of their input characteristics (dimensions, power supply, materials, etc.) giving the desired performances (torque, efficiency, mass, etc.), provided that a certain number of constraints are satisfied.This (one-way) approach has several weaknesses, the main one being that it is not clearly apparent whether this sizing problem has at least one solution. If sets of solutions exist, it becomes interesting to determine the characteristics of all these valid machines. On the other hand, if no machine can be defined by exactly meeting the specifications, it becomes more useful to look for the constraints to be relaxed to reveal solutions, or to determine and then choose among all the quasi-optimal configurations those that are the most interesting.In this context, this work aims to respond to these issues by introducing a methodological procedure giving assistance in the optimal sizing of electrical machines in particular, and in optimization in general.In this procedure, a number of numerical processing tools are implemented, to offer the opportunity to understand more finely, typically through 2D graphical representations, the complexity of optimization design problems. In other words, this work is an attempt to find an intermediate configuration between the pure optimization approach and the one based solely on modeling, in the sense that these models are first represented graphically in order to understand the complexity of the corresponding optimization problem.The application of this approach is illustrated by the presentation of the main steps of the optimal design of a Permanent Magnet Synchronous Machine.
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