A Data Based Diagnostic Method for Current Sensor Fault in Permanent Magnet Synchronous Motors (PMSM)

Shen, Tunan; Chen, Yuping; Thulfaut, Christian; Reuss, Hans-Christian

doi:10.1109/iecon.2019.8927667

Cited by 4 publications

(4 citation statements)

References 7 publications

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“…4 are related to the case of reduction and increase of 50% of the gain of a single sensor, respectively. From the inspection of these figures it is immediate to note that the contribution of the terms obtained in (17) for n > 3 is very low. Therefore, n = 3 can be assumed with a very good approximation.…”

Section: Model Numerical Validationmentioning

confidence: 94%

“…In the most general case, that is when (26) is not satisfied, the solution of ( 21) is the better approximated the greater is the value of n in (17). Obviously, the degree of approximation of the solution found for a given value of n depends on the values of the functions f d,n+1 , g d,n+1 , f q,n+1 , g q,n+1 in correspondence of the solution found.…”

Section: Modelling Of Smpmsm Drive With Gain Faults Of Current Sensor...mentioning

confidence: 98%

“…As regards the choice of n, that is the number of terms to be considered for the analytical determination of the currents i d and i q expressed by (17), it should be noted that if the two PI controllers are the same, that is if:…”

Section: Modelling Of Smpmsm Drive With Gain Faults Of Current Sensor...mentioning

confidence: 99%

“…Many solutions have been proposed in literature for the diagnosis of gain faults in phase current sensors. In [17], a comparison between three different machine learning algorithms based on linear regression, decision tree and neural network is performed for the diagnosis of phase current gain faults. Three features are extracted from virtual experiments data, such as peak to peak difference and variance of the phase current measurement.…”

Section: Introductionmentioning

confidence: 99%

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Modeling and Detection of Phase Current Sensor Gain Faults in PMSM Drives

et al. 2022

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The fault of current sensors in AC electric drives can cause inaccurate tracking of the control reference and torque oscillations, that can lead to damage of mechanical components. Therefore, the development of accurate detection techniques of these faults plays a crucial role for the proper management of the electric drive and for the fault isolation and estimation. In the paper, a model-based method for the detection of phase current sensor gain faults in a Permanent Magnet Synchronous Motor (PMSM) drive with Field Oriented Control (FOC) is proposed. At first, a mathematical model is presented, which allows an accurate determination of the analytical closed-form expression of the steady-state stator currents, taking into account the effects both of the current control regulators and of any current sensors gain faults. Starting from this model, a low-computation algorithm has been carried out, which allows not only to detect and isolate the current sensors affected by the gain fault, but also to estimate the gain values starting from the measured phase currents and motor speed. The model and the diagnostic algorithm performance is verified by means of numerical and experimental results.INDEX TERMS Current sensor fault, PMSM drives, Fault diagnosis.

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Section: Model Numerical Validationmentioning

confidence: 94%

Section: Modelling Of Smpmsm Drive With Gain Faults Of Current Sensor...mentioning

confidence: 98%

Section: Modelling Of Smpmsm Drive With Gain Faults Of Current Sensor...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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