Advanced Dead-Time Compensation Techniques for Enhanced Position Estimation in Sensorless SynRM Control
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Abstract
In this paper, a new Version-II framework of sensorless rotor position estimation of Synchronous Reluctance Motors (SynRMs) has been proposed with the objective of enhancing robustness, computational efficiency and practical feasibility. To overcome the drawbacks of the prior Version-I method that minimized various parameters such as (i d ), (i q ), dead time compensation, and harmonic injection levels to achieve a RMS rotor position error as low as 43.04 rad but with high complexities Version-II simplifies by adding only one compensation gain (k ). This scalar multiplier scales the dead-time and the harmonic effects simultaneously, greatly decreasing the dimensionality of the optimization problem of five parameters into just one, and thus, allowing faster convergence and decreasing the computational cost to alternative metaheuristic optimization algorithms, including Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization, and Differential Evolution. The Version-II model includes long-period harmonic modeling, high-frequency signal injection, and disturbance modeling of rotor speed variations, DC-link voltage ripple, and load torque variations to critically evaluate estimator stability and reliability in realistic, disturbance rich operating conditions. The error in the baseline RMS rotor position has grown to about 1780.8 rad with injected non-idealities but the optimized results have a tight cluster of about 1780-1801 rad, showing that the approach is sensitive to constant and strong estimation and not aggressive error reduction. Particle Swarm Optimization and Simulated Annealing are the most appropriate methods to be used in real-time applications where convergence time does not exceed 5 seconds. In general, the Version-II approach offers an effective, computationally solvable, and practical solution to sensorless SynRM control to supplement Version-I adherence approach and promote consistent motor drive control in industry.
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References
S. Yingjun, W. Zhenglong, and F. Yuanyuan, “An adaptive extended Kalman filter observer-for permanent magnet synchronous motor position sensorless control systems,” pp. 1–15, 2025.
H. Cai and W. Luo, “Full-speed sensorless control system of synchronous reluctance motor with flux saturation model,” pp. 1–15, 2025.
I. Ferdiansyah, “Dissertation Doctor of Engineering FPGA-based Sensorless Control Strategy for Permanent Magnet Synchronous Motor using High- Frequency Injection with Loaded Start-up Capability Graduate School of Life Science and Systems Engineering Department of Life Science and Systems Engineering Kyushu Institute of Technology Japan,” 2025.
D. Studi, D. I. Parma, M. L. Tutor, A. S. Dottorando, and H. Sadeghlafmejani, “Self-Commissioning and Estimation Techniques for Sustainable Synchronous Reluctance Motor Drives in Industrial Applications,” 2025.
Y. Ran, M. Qiao, L. Sun, and Y. Xia, “Review of Position Sensorless Control Technology for Permanent Magnet Synchronous Motors,” Energies, vol. 18, no. 9, 2025, doi: 10.3390/en18092302.