Multi-Stage Optimization of Induction Machines Using Methods for Model and Parameter Selection

Abstract

Optimization methods are increasingly used for the design process of electrical machines. The quality of the optimization result and the necessary simulation effort depend on the optimization methods, machine models and optimization parameters used. This paper presents a multi-stage optimization environment for the design optimization of induction machines. It uses the strategies of simulated annealing, evolution strategy and pattern search. Artificial neural networks are used to reduce the solution effort of the optimization. The selection of the electromagnetic machine model is made in each optimization stage using a methodical model selection approach. The selection of the optimization parameters is realized by a methodical parameter selection approach. The optimization environment is applied on the basis of an optimization for the design of an electric traction machine using the example of an induction machine and its suitability for the design of a machine is verified by a comparison with a reference machine.

Approach for the Model and Parameter Selection for the Calculation of Induction Machines

“…The parameter selection procedure provides an approach to identify machine parameters that have a high impact on the defined target variable. This procedure lends itself to the selection of optimization parameters in machine design optimizations as presented in [3].…”

“…Here, a problem-specific, experience-based selection of upper and lower bounds of the parameters is important to reduce the size of the solution space and thus the computational effort. A multi-step optimization environment for the design of an IM using the model and parameter selection procedure presented here is given in [3].…”

“…The resulting simulated temperature curves are compared with measured results of the same machine at the same operating point. The use of the parameter selection in combination with the model selection is investigated in [3] using a multi-stage optimization of the design of an IM.…”

“…The proposed model selection approach can also be used in machine optimization problems in which machines of similar power range but different designs are simulated to determine the appropriate models in individual optimization stages. Such an example is given in [3]. In such optimization environments, the choice of optimization parameters is crucial and can also be done methodically.…”

“…As an example, a weakly coupled electromagnetic-thermal simulation of an IM is used to analyze the thermal operating behavior of the machine. The parameter selection in combination with the model selection is applied in [3] in an optimization of the machine design of an IM.…”