Parameter Identification of Maritime Vessel Rudder PMSM Based on Extended Kalman Particle Filter Algorithm
Abstract
:1. Introduction
2. Establishing the Parameter Identification Model for PMSM
3. Particle Filter
3.1. Bayesian State Estimation
3.2. Establishment of the Particle Filter
4. Extended Kalman Particle Filter
5. Simulation Analysis and Comparison
5.1. PF Simulation Analysis
5.2. EKPF Simulation Analysis
5.2.1. Steady-State Performance
5.2.2. Robustness Verification
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Electromagnetic Parameters | Value | Unit |
---|---|---|
DC voltage | 24 | V |
Stator resistance | 0.84 | Ω |
d-axis inductance | 3 | mH |
q-axis inductance | 3 | mH |
Flux linkage | 0.01 | Wb |
Number of pole pairs | 4 | - |
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Yuan, T.; Wang, T.; Bai, J.; Fan, J. Parameter Identification of Maritime Vessel Rudder PMSM Based on Extended Kalman Particle Filter Algorithm. J. Mar. Sci. Eng. 2024, 12, 1095. https://doi.org/10.3390/jmse12071095
Yuan T, Wang T, Bai J, Fan J. Parameter Identification of Maritime Vessel Rudder PMSM Based on Extended Kalman Particle Filter Algorithm. Journal of Marine Science and Engineering. 2024; 12(7):1095. https://doi.org/10.3390/jmse12071095
Chicago/Turabian StyleYuan, Tianqing, Tianli Wang, Jing Bai, and Jingwen Fan. 2024. "Parameter Identification of Maritime Vessel Rudder PMSM Based on Extended Kalman Particle Filter Algorithm" Journal of Marine Science and Engineering 12, no. 7: 1095. https://doi.org/10.3390/jmse12071095