Investigation of Open-Loop Predictor Implementation Methods for Online Parameter Estimation of IPMSM

Abstract

Due to the sensitivity to parametric errors, open-loop current predictor-based estimators offer good online tracking of electric machine parameters, however at the price of rotor-speed dependent predictor pole-trajectories, thus the digital implementation needs caution. This paper aims to investigate, firstly, the discrete-time domain stability of the predictor when implemented using different discretization methods in the processor. Secondly, to assess the impact of the integration time-step (h) on the predictor stability, the microprocessor- and Field-Programmable Gate Array (FPGA)- based implementations are investigated. A System-on-Chip (SoC) that integrates both the processor and the FPGA is exploited in this study, for online identification of permanent magnet flux linkage Psim and stator resistance Rs of Interior Permanent Magnet Synchronous Machine (IPMSM). The experiments are conducted using an Embedded Real-Time Simulator (ERTS), which shows that when the approach is based on the DSP, the trapezoidal rule offers full speed-range stability while the FPGA-based implementation with inherent shorter h yields overall better performance irrespective of the discretization strategy.