Research Article

A Computationally Efficient Sequential RLS Estimator for PMSM Parameters: Algorithm Design and Experimental Verification

Volume: 13 Number: 1 March 31, 2026

A Computationally Efficient Sequential RLS Estimator for PMSM Parameters: Algorithm Design and Experimental Verification

Abstract

Accurate knowledge of electrical parameters is crucial for high-performance field oriented control (FOC) of permanent magnet synchronous motors (PMSMs). However, parameters vary significantly due to thermal effects and magnetic saturation. This study proposes a computationally efficient sequential recursive least squares (SRLS) algorithm for real-time parameter identification. Unlike conventional methods, proposed approach decouples the d- and q-axis dynamics to reduce the matrix operation complexity. Identification is achieved under persistent excitation provided by the active torque current (i_q) and the standard FOC scheme at a 20 kHz sampling frequency. Experimental validation is conducted on a 500 W motor operating within a speed range of 200–1000 RPM under constant load conditions at room temperature. Results show that the SRLS algorithm achieves a relative estimation error of 2.59 % for resistance and less than 5% for inductance. The proposed algorithm executes in only 26.5µs on an STM32F427 microcontroller, resulting in a 53% CPU load, which represents a 43% reduction in computational burden compared to the standard RLS method.

Keywords

Supporting Institution

This work is supported by Pamukkale University BAP office with the research project number 2024FEBE015.

Project Number

2024FEBE015

References

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  2. Liu, Q., & Hameyer, K. (2015). A fast online full parameter estimation of a PMSM with sinusoidal signal injection. 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015, 4091–4096. https://doi.org/10.1109/ECCE.2015.7310237
  3. Ming, X., Wang, X., Liu, F., Qu, Y., Zhou, B., Zhang, S., & Yu, P. (2025). Mechanical Parameter Identification of Permanent Magnet Synchronous Motor Based on Symmetry. Symmetry 17(11), 1929. https://doi.org/10.3390/sym17111929
  4. Ortatepe, Z., & Karaarslan, A. (2020). Source current quality improvement of finite control set model predictive control-based matrix converter under distorted source voltage conditions. International Transactions on Electrical Energy Systems, 30(8), e12459. https://doi.org/10.1002/2050-7038.12459
  5. Park, G., & Bae, J. (2024). Inductance Estimation Based on Wavelet-GMDH for Sensorless Control of PMSM. Applied Sciences, 14(11), 4386. https://doi.org/10.3390/app14114386
  6. Udomsuk, S., Areerak, K., Areerak, T., & Areerak, K. (2024). Online Estimation of Three-Phase Induction Motor Parameters Using an Extended Kalman Filter for Energy Saving. Energies, 17(9), 2115. https://doi.org/10.3390/en17092115
  7. Wang, Q., Shi, H., Ye, C., & Zhou, H. (2025). Synergizing Metaheuristic Optimization and Model Predictive Control: A Comprehensive Review for Advanced Motor Drives. Energies, 18(18), 4831. https://doi.org/10.3390/en18184831
  8. Wang, X., Jing, H., Chen, Z., Wang, X., Ge, L., Zhao, H., & Xiao, D. (2024). Optimization-Based Parameter Estimation for PMSMs Under Unified Observable Conditions. IEEE Transactions on Power Electronics, 39(2), 2632–2643. https://doi.org/10.1109/TPEL.2023.3336724

Details

Primary Language

English

Subjects

Power Electronics

Journal Section

Research Article

Publication Date

March 31, 2026

Submission Date

February 17, 2026

Acceptance Date

March 24, 2026

Published in Issue

Year 2026 Volume: 13 Number: 1

APA
Ortatepe, Z., & Özlü, E. (2026). A Computationally Efficient Sequential RLS Estimator for PMSM Parameters: Algorithm Design and Experimental Verification. Gazi University Journal of Science Part A: Engineering and Innovation, 13(1), 419-433. https://doi.org/10.54287/gujsa.1891854
AMA
1.Ortatepe Z, Özlü E. A Computationally Efficient Sequential RLS Estimator for PMSM Parameters: Algorithm Design and Experimental Verification. GU J Sci, Part A. 2026;13(1):419-433. doi:10.54287/gujsa.1891854
Chicago
Ortatepe, Zafer, and Eren Özlü. 2026. “A Computationally Efficient Sequential RLS Estimator for PMSM Parameters: Algorithm Design and Experimental Verification”. Gazi University Journal of Science Part A: Engineering and Innovation 13 (1): 419-33. https://doi.org/10.54287/gujsa.1891854.
EndNote
Ortatepe Z, Özlü E (March 1, 2026) A Computationally Efficient Sequential RLS Estimator for PMSM Parameters: Algorithm Design and Experimental Verification. Gazi University Journal of Science Part A: Engineering and Innovation 13 1 419–433.
IEEE
[1]Z. Ortatepe and E. Özlü, “A Computationally Efficient Sequential RLS Estimator for PMSM Parameters: Algorithm Design and Experimental Verification”, GU J Sci, Part A, vol. 13, no. 1, pp. 419–433, Mar. 2026, doi: 10.54287/gujsa.1891854.
ISNAD
Ortatepe, Zafer - Özlü, Eren. “A Computationally Efficient Sequential RLS Estimator for PMSM Parameters: Algorithm Design and Experimental Verification”. Gazi University Journal of Science Part A: Engineering and Innovation 13/1 (March 1, 2026): 419-433. https://doi.org/10.54287/gujsa.1891854.
JAMA
1.Ortatepe Z, Özlü E. A Computationally Efficient Sequential RLS Estimator for PMSM Parameters: Algorithm Design and Experimental Verification. GU J Sci, Part A. 2026;13:419–433.
MLA
Ortatepe, Zafer, and Eren Özlü. “A Computationally Efficient Sequential RLS Estimator for PMSM Parameters: Algorithm Design and Experimental Verification”. Gazi University Journal of Science Part A: Engineering and Innovation, vol. 13, no. 1, Mar. 2026, pp. 419-33, doi:10.54287/gujsa.1891854.
Vancouver
1.Zafer Ortatepe, Eren Özlü. A Computationally Efficient Sequential RLS Estimator for PMSM Parameters: Algorithm Design and Experimental Verification. GU J Sci, Part A. 2026 Mar. 1;13(1):419-33. doi:10.54287/gujsa.1891854