Parameter Estimation of Asynchronous Motors Via Trust Region and Pattern Search Optimization Methods

Since their first invention by Nikola Tesla, asynchronous motors (Induction Motors ‘IM’) have been enormously employed in versatile industrial applications. Therefore, researchers pay undividable attention to different research aspects related to these machines. Parameter estimation of an IM is considered a vital research area as identification of IM's parameters is crucial for precise performance of their control drive. The traditional method that used for the aforementioned purpose is through experimental blocked rotor and no load tests based on IEEE Standard 112–1996, which is not efficient as the rotor should be mechanically locked. However, this issue can be resolved thanks to the development of optimization methods, which allow estimation of the parameters accurately. In this paper, two optimization methods are investigated for identification of asynchronous motors, the methods are Trust Region Method ‘TRM’ and Pattern Search Algorithm ‘PSA’. The simulation results show that both methods are effectively able to reach the optimal solution, with a superior advantage to TRM method as it can achieve the same results with less time-consumption.