Novel Known Regressor Active Flux Full-Order Model for Sensorless Control of Permanent Magnet Synchronous Motors

To address the issue of local stability in the speed-adaptive observer stemming from unknown speed regressors in the full-order model of interior permanent magnet synchronous motors (IPMSM), a novel active flux full-order model incorporating known speed regressors for IPMSM is proposed. Initially, this paper redefines the state variables of the active flux full-order model of IPMSM and formulates the dynamic equations of IPMSM based on these new state variables to conform to the Brunovsky canonical form, ensuring that the speed regressors in the new model are solely comprised of known measured values. Subsequently, a tailored nonlinear high-gain observer algorithm is introduced for this model to achieve globally stable rotor position and speed estimation. The effectiveness and practicality of the proposed sensorless control algorithm are then validated through experimentation on a 0. 75 kW IPMSM test platform. The results indicate that the new full-order model enhances the dynamic performance of the sensorless control system for IPMSM, extending the stable operational range of the full-order observer. The structure of the full-order observer overcomes the local stability limitations of reduced-order observers while simplifying coefficient tuning. In fast reversing test, compared to conventional methods, the proposed observer achieves approximately a 42 % faster convergence speed in position estimation errors and reduces error magnitudes by about 44. 4%. In steady-state conditions, the fluctuation amplitude of the quadrature current decreases by roughly 35%. Notably, the proposed sensorless control method successfully suppresses disturbances under rated load at 0. 15% of rated speed (5 r/min). © 2024 Xi'an Jiaotong University. All rights reserved.