Abstract
This research deals with the optimization of a single-phase brushless DC motor (BLDCM) by substituting a commercial single-phase BLDCM for pump application in order to satisfactorily improve its efficiency regarding the required performance of a motor for pump systems (pump load 1,800 rpm, at 2 Nmm). The reliability of the results is verified between simulation and experiment using performance tests. In the sampling process, latin hypercubic sampling (LHS), the subject of many experiments, is usually used. However, this method requires a great deal of time and expense. This paper utilizes the table of orthogonal array in order to use the smallest possible number of experiments. In addition, a metamodel with second approximation polynomials is made using response surface methodology (RSM). The adjusted coefficients of multiple determinations which shows the reliability of the metamodel (multiobjective functions) is 100%. This result shows that the table of orthogonal array with the smallest number of experiments is suitable for sampling. The genetic algorithm (GA) is implemented to search for optimum solutions on the constructed metamodel which consists of two objective functions. With the optimal design set, predicted results of the GA are better than the generalized reduced gradient (GRG) algorithm. Nevertheless, verification results of the GRG are better than the GA. This result has an error within 1%.
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