Temperature influenced online stator resistance estimation using an improved swarm intelligence technique for induction machine

The percentage of copper losses in the induction machine (IM) governs the performance and hence the efficiency of the machine. The temperature dependence of stator resistance results in inaccurate performance prediction if temperature is not taken into account in advance. Hence, it is imperative to determine the relationship between temperature and stator resistance. This research paper investigates the change in stator resistance with increase in temperature over a period of time. An improved particle swarm optimization based scheme is developed for the estimation of stator resistance with the help of the two-axis model of induction machine, taking into account the temperature effect on the resistance.

Further, a 15 kW copper-rotor IM has been tested using a PLC based drive system and the increase in temperature is measured using resistance temperature detectors to obtain online stator resistance. A comparative analysis of the experimentally measured stator resistance with that obtained from the numerical investigation of the temperature based two-axis model has been performed.

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