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Machines
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Advanced Sensorless Control of Electrical Machines
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Advanced Sensorless Control of Electrical Machines

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Electrical Machines and Drives".

Deadline for manuscript submissions: 31 August 2026 | Viewed by 2076

Special Issue Editors

Dr. Ningfei Jiao

E-Mail Website
Guest Editor
Department of Electrical Engineering, Northwestern Polytechnical University, Xi’an 710129, China
Interests: integrated starter-generator; PMSM; fault diagnosis; position-sensorless control; motor drive
Special Issues, Collections and Topics in MDPI journals
Dr. Hang Zhang

E-Mail Website
Guest Editor
School of Electrical Engineering, Xi’an University of Technology, Xi’an 710000, China
Interests: PMSM; sensorless control; inter turn short circuit; fault diagnosis; multi-motor collaborative control

Special Issue Information

Dear Colleagues,

In the advanced control of electrical machines, vector control systems not using mechanical position sensors, otherwise known as position/speed sensorless control, has been increasingly studied and applied in both industries and household appliances.

This Special Issue aims to explore the latest innovations in sensorless control strategies that are pivotal for improving the stability and robustness of electrical machines systems. In addition, it will provide an international forum for professionals, academics, and researchers to present novel developments in the field. Topics include but are not limited to theoretical studies, computational algorithm developments, and the design and application of high-efficiency and stable-operation sensorless drives.

Furthermore, this Special Issue will accept contributions describing innovative research and developments in the advanced sensorless control of electrical machines. It will also will cover advanced algorithm design, test platforms, data analysis, and robustness improvement, as well as the following themes covered by MDPI’s Machines journal:

  • Novel observer design techniques for sensorless control;
  • Fault-tolerant sensorless control for high-reliability electrical machines;
  • High-performance sensorless-drive test platforms and experimental research;
  • Advanced model-free techniques for sensorless control;
  • Sensorless control under extreme operating conditions;
  • AI-driven approaches for enhanced sensorless control;
  • Motor design-based sensorless control methods;
  • Reliability assessment of sensorless control strategies.

Dr. Ningfei Jiao
Dr. Hang Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • electrical machines
  • sensorless control
  • high reliability
  • novel observer design
  • model-free sensorless control

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

21 pages, 20516 KB  
Article
Sensorless Sector Determination of Brushless DC Motors Using Maximum Likelihood Estimation
by Abdulkerim Ahmet Kaplan, Mehmet Onur Gulbahce and Derya Ahmet Kocabas
Machines 2026, 14(1), 42; https://doi.org/10.3390/machines14010042 - 29 Dec 2025
Viewed by 876
Abstract
Brushless DC motors are widely used for their high power density and efficiency. However, sensorless control remains challenging due to the difficulty of accurate rotor position detection, especially at low speeds. This paper proposes a novel sensorless trapezoidal control method based on Maximum [...] Read more.
Brushless DC motors are widely used for their high power density and efficiency. However, sensorless control remains challenging due to the difficulty of accurate rotor position detection, especially at low speeds. This paper proposes a novel sensorless trapezoidal control method based on Maximum Likelihood Estimation (MLE) for rotor sector detection. Unlike conventional back-EMF zero-crossing techniques, the proposed method uses a statistical algorithm to generate a probability map from prior motor state data, enabling accurate rotor position estimation without sensors. The MLE method operates with a typical computation time of 50–100 μs, offering a balanced tradeoff between speed and accuracy. It is significantly faster than Kalman filter-based approaches (200–1000 μs) and comparable to observer-based methods (20–80 μs), while being more robust than zero-crossing techniques (<5 μs). This makes it a practical and cost-effective solution for applications demanding high efficiency and reliability, such as electric mobility systems. Full article
(This article belongs to the Special Issue Advanced Sensorless Control of Electrical Machines)
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20 pages, 6876 KB  
Article
Real-Time Inductance Estimation of Sensorless PMSM Drive System Using Wavelet Denoising and Least-Order Observer with Time-Delay Compensation
by Gwangmin Park and Junhyung Bae
Machines 2025, 13(12), 1102; https://doi.org/10.3390/machines13121102 - 28 Nov 2025
Viewed by 634
Abstract
In this paper, the inductance of a sensorless PMSM (Permanent Magnet Synchronous Motor) drive system equipped with a periodic load torque compensator based on a wavelet denoising and least-order observer with time-delay compensation is estimated in real-time. In a sensorless PMSM system with [...] Read more.
In this paper, the inductance of a sensorless PMSM (Permanent Magnet Synchronous Motor) drive system equipped with a periodic load torque compensator based on a wavelet denoising and least-order observer with time-delay compensation is estimated in real-time. In a sensorless PMSM system with constant load torque, the magnetically saturated inductance value remains constant. This constant inductance error causes minor performance degradation, such as a constant rotor position estimation error and non-optimal torque current, but it does not introduce a speed estimation error. Conversely, in a sensorless PMSM motor system subjected to periodic load torque, the magnetically saturated inductance error fluctuates periodically. This fluctuation leads to periodic variations in both the estimated position error and the speed error, ultimately degrading the load torque compensation performance. This paper applies the maximum energy-to-Shannon entropy criterion for the optimal selection of the mother wavelet in the wavelet transform to remove the motor signal noise and achieve more accurate inductance estimation. Additionally, the coherence and correlation theory is proposed to address the time delay in the least-order observer and improve the time delay. A self-saturation compensation method is also proposed to minimize periodic speed fluctuations and improve control accuracy through inductance parameter estimation. Finally, experiments were conducted on a sensorless PMSM drive system to verify the inductance estimation performance and validate the effectiveness of vibration reduction. Full article
(This article belongs to the Special Issue Advanced Sensorless Control of Electrical Machines)
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