Efforts on real-time implementation of PSO based PMSM parameter identification

Permanent magnet synchronous motors (PMSM) are widely used in high performance applications. Accurate PMSM model is very important to advanced control system designs. However, the identification of PMSM parameters is very difficult due to the model complexity. In our previous paper, we proposed a particle swarm optimization (PSO) based parameter identification algorithm. In that paper, it has been shown that the algorithm could successfully identify model parameters from simulated and experimental data. In this paper, we describe how the algorithm can be implemented in real time. Real time implementation will result in more efficient and more accurate identification. Some preliminary simulation results are provided in this paper. The algorithm can be easily implemented in dSPACE controller and tested via real time hardware-in-the- loop (HIL) simulations. The implementation techniques can be extended to other online identification applications.