In order to achieve high responsiveness in motor control, it is necessary to accurately predict the behavior of a running motor. Since motor parameters used in observer models are conventionally composed of constant terms independent of the operating points on the controller side, there was a problem with the tracking capability of the output for command values. For this reason, in the end, a physical machine was needed for parameter tuning.
This issue can be resolved by using the JMAG-RT model, which is a high-fidelity motor model generated from the FEA model. JMAG-RT motor models can reproduce characteristics of a physical machine with high fidelity. In other words, a high-fidelity observer model can be created by extracting motor parameters required for them from high-fidelity motor models.