Extended Kalman filter‐based method for inter‐turn fault detection of the switched reluctance motors. Issue 8 (1st September 2016)

• Record Type: Journal Article
• Authors: Khayam Hoseini, Seyed Reza; Farjah, Ebrahim; Ghanbari, Teymoor; Givi, Hadi
• Is Part Of: IET electric power applications. Volume 10:Issue 8(2016)
• Page Start: 714
• Page End: 722
• Publication Date: 2016-09-01
• Subjects: Kalman filters -- reluctance motors -- nonlinear filters -- electric vehicles -- fault diagnosis; extended Kalman filter‐based method -- interturn fault detection -- switched reluctance motors -- SRM -- electric vehicles -- EV -- fault tolerant structure -- fault occurrence -- fault diagnosis -- winding interturn short‐circuit fault; Electric power -- Periodicals; Electric power systems -- Periodicals; 621.305
• DOI: 10.1049/iet-epa.2015.0602
• Languages: English
• ISSNs: 1751-8660

Abstract

Abstract : Switched reluctance motors (SRMs) are extensively utilised in electric vehicles (EVs) due to some outstanding capabilities such as rugged and fault tolerant structure. Since the excitation of the phases is performed independently in the SRM, the motor could continue operation even in case of fault occurrence in one of the phases by disabling the faulty phase. However, to improve the reliability of the SRM for EV applications, an efficient fault diagnosis approach should be employed. In this study, an on‐line method for detection of winding inter‐turn short‐circuit fault in the SRMs is presented. The proposed technique is based on a model, in which the extended Kalman filter is utilised. The method achieves a fast response, thus, the remedial strategies could be employed at the initial moments after fault occurrence. The proposed method is simple to implement and reliable in practice. The performance of the proposed approach is verified using some simulations and experiments. The results confirm high capability of the method in different conditions.