Online parameter identification of SPMSM based on improved artificial bee colony algorithm

• Autorzy: Wu Chunli , Jiang Shuai , Bian Chunyuan

Identyfikatory

DOI

10.24425/aee.2021.138260

• Języki publikacji: EN

Abstrakty

EN

The artificial bee colony (ABC) intelligence algorithm is widely applied to solve multi-variable function optimization problems. In order to accurately identify the parameters of the surface-mounted permanent magnet synchronous motor (SPMSM), this paper proposes an improved ABC optimization method based on vector control to solve the multi-parameter identification problem of the PMSM. Because of the shortcomings of the existing parameter identification algorithms, such as high computational complexity and data saturation, the ABC algorithm is applied for the multi-parameter identification of the PMSM for the first time. In order to further improve the search speed of the ABC algorithm and avoid falling into the local optimum, Euclidean distance is introduced into the ABC algorithm to search more efficiently in the feasible region. Applying the improved algorithm to multi-parameter identification of the PMSM, this method only needs to sample the stator current and voltage signals of the motor. Combined with the fitness function, the online identification of the PMSM can be achieved. The simulation and experimental results show that the ABC algorithm can quickly identify the motor stator resistance, inductance and flux linkage. In addition, the ABC algorithm improved by Euclidean distance has faster convergence speed and smaller steady-state error for the identification results of stator resistance, inductance and flux linkage.

Słowa kluczowe

EN

artificial bee colony algorithm; Euclidean distance; online identification; parameter identification; urface-mounted permanent magnet synchronous motor

PL

algorytm sztucznej kolonii pszczół; odległość euklidesowa; identyfikacja online; identyfikacja parametrów; silnik synchroniczny z magnesami trwałymi montowany na powierzchni czołowej

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2021
• Tom: Vol. 70, nr 4
• Strony: 777--790
• Opis fizyczny: Bibliogr. 19 poz., rys., tab., wz.

Twórcy

autor

Wu Chunli

• College of Information Science and Engineering, Northeastern University China

• https://orcid.org/0000-0003-0685-4114

autor

Jiang Shuai

• College of Information Science and Engineering, Northeastern University China

autor

Bian Chunyuan

• College of Information Science and Engineering, Northeastern University China

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).