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Absfrmf -Induction motor behavior is commonly simulated by a fifth order differential equation model which includes two stator state variables, two rotor state variables, and shaft speed. Normally two more variables must be added to account for the effects of a second rotor circuit representing deep bars, a starting cage, or rotor distributed parameters. This paper presents a technique for including the effects of a second rotor circuit without adding more state variables to the fifth order model. Transient, as well as steady state effects are included. The model may be useful in cases where switching introduces transient torques and losses that are invisible to the fifth order model, and it is not desirable to expand the model to include two more state variables. A laboratory test is included.

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Genetic algorithms can be used to find the global minimum of functions that are multimodal or that contain noisy data that render them intractable to gradient descent methods. Furthermore, the genetic approach is robust, requiring little preprocessing of data. The algorithm employs a random starting point, and is compatable with parallel processing.In this paper, the method is applied to identifying the parameters of an induction motor from load test data.

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