Online Inductance Identification Using Extended Kalman Filter for Adaptive Vector Control of Synchronous Reluctance Machine
Publication Name: 2024 23rd International Symposium on Electrical Apparatus and Technologies Siela 2024 Proceedings
Publication Date: 2024-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
This study presents an adaptive vector control method for reducing the inductance sensitivity of synchronous reluctance machine drives. In the proposed control structure, the direct and quadrature inductances are identified online by using an extended Kalman filter. Therefore, only the stator resistance of the machine parameters needs to be pre-identified during the installation process. Since variations in inductances can be tracked by the estimator, the proposed adaptive vector control is able to outperform the conventional field-oriented control in cases of inductance uncertainties, as shown by the simulation results.
Open Access: Yes