A Novel Method for Identifying Parameters of Induction Motors at Standstill Using ADALINE

In this paper, we propose a new method for an online electric parameters identification of an induction motor (IM). This method is carried out in the IM standstill configuration and uses adaptive linear neuron (ADALINE) networks. In order to simplify the identification process, the IM model is approximated by two first-order subsystems: one is valid at low frequencies (LFs), called the slow system and the other is valid at high frequencies (HFs), called the fast system. By means of two ADALINE networks, the parameters of the slow system and the fast system are identified in LFs and HFs, respectively, and thus, the required IM parameters are derived. Finally, experimental results are presented in order to validate the proposed method and to check the accuracy of the obtained parameters. The originality of this paper is the building of a model representation that is suitable for implementation with ADALINE networks. This leads to a simple implementation and ease of parameters identification.