University of Hertfordshire Research Archive

        JavaScript is disabled for your browser. Some features of this site may not work without it.

        Browse

        All of UHRABy Issue DateAuthorsTitlesThis CollectionBy Issue DateAuthorsTitles

        Arkivum Files

        My Downloads
        View Item 
        • UHRA Home
        • University of Hertfordshire
        • Research publications
        • View Item
        • UHRA Home
        • University of Hertfordshire
        • Research publications
        • View Item

        Fault Detection and Isolation in Electric Vehicle Powertrain

        View/Open
        Fault_Detection_and_Isolation_in_Electric_Vehicle_Powertrain_final2.pdf (PDF, 1Mb)(embargoed until 31/12/2099)
        Author
        Jombo, Gbanaibolou
        Zhang, Yu
        Attention
        2299/25378
        Abstract
        The powertrain of an electric vehicle (EV) consists mainly of the battery, electric motor and power electronics. The safe and reliable operation of the electric vehicle depends on their fault-free operation. Fault detection and isolation methods work on the premise that small changes as a result of faults affecting a system causes variation in its operational response. This property can be used for the detection of such faults and their severity. This chapter discusses methods for detection and isolation of faults in electric vehicle powertrain components. Powertrain configuration and technologies are identified. Battery technology such as Lithium-ion batteries have gained a significant application as energy storage source in electric vehicles due to their high energy and power density, long lifespan, and low self-discharge performance under extreme temperatures. Model-based approaches are discussed for the determination of battery state of charge, state of health and effect of accelerated degradation. Fault detection in electric motor is considered. Brushless asynchronous induction motor, brushed externally excited synchronous motor and brushless permanent magnet synchronous motor are the options adopted for the electric vehicle powertrain. Signal processing-based approach such as the motor current signature analysis is explored for detection of broken rotor bar, shorten stator windings, air gap eccentricity, bearing failure and load variation effects. Lastly, fault detection in power electronics is explored. Electric vehicle electric components need complex electronics to control them. These come in the form of a power electronics module (PEM), and an inverter, which can be integral with the PEM or the electric motor itself. Inverters provide the interface between an alternating current electric component and the direct current battery. The current focus for electric vehicle power electronics is controllable solid-state switches such as insulated gate bipolar transistor. For these power drives, the major faults are: open switch fault and short switch fault. Signal processing-based approached are considered for detection of these fault.
        Publication date
        2022-02-15
        Published in
        Modern Automotive Electrical Systems
        Other links
        http://hdl.handle.net/2299/25378
        Relations
        School of Physics, Engineering & Computer Science
        Metadata
        Show full item record
        Keep in touch

        © 2019 University of Hertfordshire

        I want to...

        • Apply for a course
        • Download a Prospectus
        • Find a job at the University
        • Make a complaint
        • Contact the Press Office

        Go to...

        • Accommodation booking
        • Your student record
        • Bayfordbury
        • KASPAR
        • UH Arts

        The small print

        • Terms of use
        • Privacy and cookies
        • Criminal Finances Act 2017
        • Modern Slavery Act 2015
        • Sitemap

        Find/Contact us

        • T: +44 (0)1707 284000
        • E: ask@herts.ac.uk
        • Where to find us
        • Parking
        • hr
        • qaa
        • stonewall
        • AMBA
        • ECU Race Charter
        • disability confident
        • AthenaSwan