Induction motor Parameter Estimation Using Hybrid Genetic Algorithm

The main objective of this work is to develop a cost effective off-line method for determination of induction motor equivalent circuit parameters by conducting a single load test on the motor. The proposed scheme is an alternative viable method to conventional means of no-load and blocked rotor tests. The identification of motor parameters is redrafted as a multi-objective optimization problem and solution is sought through conventional optimization method as well as Genetic Algorithm (GA). The conventional method employed is the well known Rosenbrock's (RB) rotating coordinates method. When the results of the two methods are analyzed, it is observed that while GA offers near optimal solution to the problem, the method of RB always results in global optima, provided initial values are chosen judiciously. Hence, it is proposed to combine these two methods to gain the advantages of both the methods. In such a hybrid optimization method, the task of global search is carried out by GA, while Rosenbrock's method is devoted to local search. Comparison of these two techniques are discussed and presented in conjunction with computed and practical results. It is shown that combination of GA with conventional method yields improved results.