Abstract
This paper presents a diagnostic and prognostic condition monitoring method for insulated-gate bipolar transistor (IGBT) power modules for use primarily in electric vehicle applications. The wire-bond-related failure, one of the most commonly observed packaging failures, is investigated by analytical and experimental methods using the on-state voltage drop as a failure indicator. A sophisticated test bench is developed to generate and apply the required current/power pulses to the device under test. The proposed method is capable of detecting small changes in the failure indicators of the IGBTs and freewheeling diodes and its effectiveness is validated experimentally. The novelty of the work lies in the accurate online testing capacity for diagnostics and prognostics of the power module with a focus on the wire bonding faults, by injecting external currents into the power unit during the idle time. Test results show that the IGBT may sustain a loss of half the bond wires before the impending fault becomes catastrophic. The measurement circuitry can be embedded in the IGBT drive circuits and the measurements can be performed in situ when the electric vehicle stops in stop-and-go, red light traffic conditions, or during routine servicing.
Highlights
OVER THE last 20 years, electric vehicle (EV) technologies have taken a significant leap forward, primarily aided by advances in electrical motor drives, power converters, batteries and system configuration
In the test bench developed for diagnostics and prognostics of insulated-gate bipolar transistor (IGBT) power modules, three half-bridge open modules of SKM 50GB063D are mounted on a forced air-cooled heat sink
This paper has described an in-situ diagnostic and prognostic health monitoring method for IGBT power modules with a focus on the wire bonding faults and their failure mechanisms
Summary
OVER THE last 20 years, electric vehicle (EV) technologies have taken a significant leap forward, primarily aided by advances in electrical motor drives, power converters, batteries and system configuration. Traditional reliability prediction methods include Mil-HDBK-217, 217-PLUS, PRISM, Telcordia and FIDES These are empirical methods based on statistical data and average performance of a large number of identical products. A range of detecting elements may be embedded within the host device and their failures provide an early warning signal This is called the Canary method [42]. The cumulative fatigue (or damage) of an IGBT is calculated based on actual operational conditions and its remaining useful life (RUL) is expressed as the number of cycles to failures [25][48][49]. The third method is the failure precursor method This is realized by observing changes in either fault-related parameters [28] or by adding purpose-built embedded sensors [50][51].
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