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Chapitre D'ouvrage Année : 2014

Use of external magnetic field for supervision and diagnosis of electrical traction motors

Résumé

The work presents a supervision method for the detection of AC electrical machine faults, generally used in electrical traction, exploiting the information given by the external magnetic field in the vicinity of the machine. This field is an image of the air-gap flux density and consequently, it contains information concerning the failure presence. In this work, two methods based on the analysis of the magnetic field outside the machine are presented. They are reliable, original, inexpensive, and simple to implement in electrical automotive vehicles. They have the advantage of being non-invasive and just get rid of the main drawback presented by other diagnostic methods based on a comparison with a healthy state assumed to be known. The both methods need simple coil sensors placed in particular positions of the motors for flux density measurements. These sensors are simple, non-invasive, low cost and they induce an electromotive force whose derivative effect amplifies the low and medium frequencies. These methods are developed in the case of AC electrical rotating machines (induction and synchronous machines) often used in electrical traction. The analysis is focused on the low-frequency components of the magnetic field which is not influenced by the presence of electronic converters always used in traction applications. The theoretical analysis and his experimental validation are also presented.
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Dates et versions

hal-04330359 , version 1 (08-12-2023)

Identifiants

  • HAL Id : hal-04330359 , version 1

Citer

Remus Pusca, Raphael Romary, Adrian Ceban. Use of external magnetic field for supervision and diagnosis of electrical traction motors. Nicu Bizon, Lucian Dascalescu and Naser Mahdavi Tabatabaei. Autonomous Vehicles: Intelligent Transport Systems and Smart Technologies, NOVA Publishers, 2014, 978-1- 63321-326-5. ⟨hal-04330359⟩

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