| Autor: |
Jilei Xing, Junzhi Zhang, Xingming Zhuang, Yao Xu |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
World Electric Vehicle Journal, Vol 15, Iss 1, p 35 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2032-6653 |
| DOI: |
10.3390/wevj15010035 |
| Popis: |
Sensorless control of permanent magnet synchronous motors is preferable in some applications due to cost and mounting space concerns. The performance of most existing position estimation methods greatly depends on the accuracy of the motor inductance. As the estimated position should not be involved in the parameter identification process in a sensorless control system, an online inductance identification method independent of the rotor position information is developed in this paper. The proposed method utilizes the recursive least square algorithm and the particle swarm optimization algorithm to realize real-time identification of the inductance along the direct axis and the quadrature axis, respectively, based on the deduced parametric equations without position information. The proposed method is efficient enough to be implemented within 0.2 ms and does not introduce any additional signal injection. A test bench is built to validate the characteristics of the method, and the experimental results show that the identified inductance can converge to the actual value rapidly and is robust to changes in the initial values and stator current. With the proposed method, accurate estimation of the rotor position and speed can be obtained using traditional model-based position estimators, and the stability of the sensorless control system can be improved significantly. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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