Performance Improvement of Magnet Temperature Estimation Using Kernel Method Based Non-Linear Parameter Estimator for Variable Leakage Flux IPMSMs

This paper proposes the novel approach employing the kernel method as regression model to describe the dependency of magnet flux linkage on applied current, which is suitable for magnet temperature estimation. The model estimates flux linkage values with mean relative error of less than 2% compared to values calculated from finite element analysis (FEA). Magnet temperature is estimated by comparing a magnet flux linkage under loaded condition to the values from the regression models built under fixed temperatures. Results of the magnet temperature estimation method is about the same accuracy of the results using look-up table (LUT), hence it suggests the approach is suitable for non-linear motor property modeling.