Estimating Electrical Parameters of the Induction Motor by Measuring the Components Temperatures

In this article the electrical parameters of the induction motor are estimated by measuring temperature of its components. This process consists of four sections: 1- Thermal resistance model 2- Electrical parameters model of the motor and the model gives us corresponding temperatures as output 3- Electrical model and 4- Neural network which presents motor parameters and operational status compatible with corresponding learning data. In thermal resistance model, we use physical and geometrical properties of motor components to formulate thermal resistance of each component of the motor. In electrical model, electrical losses are calculated by electrical variables. In neural network the temperature of the motor components is used as input data and stator current and maximum torque are used as target data. as input data in the electrical These temperatures were used for training network (temperatures as input data and stator current and maximum torque as target data) in the neural network. After measuring temperatures of the components and using them as inputs to neural network, the corresponding stator current and maximum torque (target data) are estimated. All the stator currents referred to this paper were validated by experimental measurements.