PMSM Drive Position Estimation: Contribution to the High-Frequency Injection Voltage Selection Issue

Medjmadj, Slimane; Diallo, Demba; Mostefai, Messaoud; Delpha, Claude; Arias, A.

doi:10.1109/tec.2014.2354075

Cited by 82 publications

(36 citation statements)

References 27 publications

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“…Beside the fault detection and diagnosis, the residuals are used to estimate the load torque. This is a non-measured variable but its knowledge can be useful in the monitoring but also in the improvement of position or speed estimation [18][19] This paper is organized as follows: section II is devoted to the description of the principle of ARRs computation to form the residuals. In section III, two methods of threshold computation dedicated to Gaussian signals are presented.…”

Section: Figure 3 Diagram Of the Fdimentioning

confidence: 99%

Robust Fault Diagnosis and Load Torque Estimation in Electrical Drives Using Analytical Redundancy Relations and Sliding Mode Observer

Medjmadj

Mostefai

2018

IJEEI

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Electrical drives are more and more used in transportation applications and industrial process because of their effective cost and high efficiency. They have become critical components and therefore any fault or failure affecting them may seriously endanger the users and/or induce huge financial costs. As a consequence, early detection and isolation of these faults is recommended if not mandatory to enhance the safety, the availability, the reliability and improve the maintenance and the operational efficiency. Analytical Redundancy Relations (ARR) are used to compute to structured residuals on which the diagnosis is based. To smooth the residuals and enhance the fault detection capability, a sliding mode observer is developed to compute the derivatives. The analysis of the residuals reveals that they are Gaussian signals with a change in the mean. The comparison between the two-sigma and the two-sided CUSUM methods has shown that the latter is more efficient to compute the thresholds. Therefore with the two-sided CUSUM, the rotor resistance fault is detected with no false alarm. Moreover it is proved that the fault diagnosis is robust to the load torque variations. Beside, thanks to the residual, a load torque estimator is also developed. Extensive simulation results prove the validity of our approach.

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Section: Figure 3 Diagram Of the Fdimentioning

confidence: 99%

Robust Fault Diagnosis and Load Torque Estimation in Electrical Drives Using Analytical Redundancy Relations and Sliding Mode Observer

Medjmadj

Mostefai

2018

IJEEI

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“…In general there are three different approaches [3][4]. The first approach focuses on estimation of the motor back electromotive force (EMF) [5][6][7].The second uses position dependence on motor inductances due to magnetic saliency [8] while the third one is based on the linear or non-linear state observers, such as: Luenberger observer, reduced order observer, Fuzzy logic control, sliding mode observer and Kalman filter, [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Fault Tolerant Control of PMSM Drive Using Luenberger and Adaptive Back-EMF Observers

Medjmadj¹

2019

EJEE

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In this paper, we propose to design a sensorless controller that can cope both with performance and robustness by the hybridization of two controllers. The strategy introduced in this paper includes the sensorless active fault tolerant controller of the PMSM drive at high speed. It is built with the combination of a vector controller, two virtual sensors: Luenberger and adaptive back-EMF observers, and a voting algorithm using Newton-Raphson method. Simulation results are provided to verify effectiveness of the proposed strategy of a 1kW PMSM motor driven by fault tolerant control in case of position sensor outage.

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“…In the literature of high-frequency injection (HFI) position estimation, there exist several tracking algorithms (PLLs [11], mechanical observers [12], the inverse of tangent [13]). These methods suffer from the knowledge of machine parameters (L d ,L q inductances, inertia J, viscous friction K f ,...) and the dependency of injected signal characteristics (frequency ω c , magnitude V c ).…”

Section: Introductionmentioning

confidence: 99%

A Robust Observer of Rotor Position and Speed for IPMSM HFI Sensorless Drives

Messali

Ghanes

Koteich

et al. 2018

2018 IEEE 9th International Symposium on Sensorless Control for Electrical Drives (SLED)

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This paper proposes a new tracking algorithm associated to high frequency (HF) signal injection techniques for sensorless control of Interior Permanent Synchronous Machine (IPMSM). The proposed strategy allows to overcome the knowledge of the machine parameters and HF signal characteristics which are the main drawbacks of the existing tracking algorithms (phase-locked loop (PLLs), mechanical system observers, inverse of tangent). Several simulation experimental results are provided to verify and to test the robustness of the proposed sensorless control method in the framework of electric propulsion used in automotive applications.

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PMSM Drive Position Estimation: Contribution to the High-Frequency Injection Voltage Selection Issue

Abstract: Abstract--High

Cited by 82 publications

References 27 publications

Robust Fault Diagnosis and Load Torque Estimation in Electrical Drives Using Analytical Redundancy Relations and Sliding Mode Observer

Robust Fault Diagnosis and Load Torque Estimation in Electrical Drives Using Analytical Redundancy Relations and Sliding Mode Observer

Fault Tolerant Control of PMSM Drive Using Luenberger and Adaptive Back-EMF Observers

A Robust Observer of Rotor Position and Speed for IPMSM HFI Sensorless Drives

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