Reliability of Repetitively Avalanched Wire-Bonded Low-Voltage Discrete Power Trench n-MOSFETs

Alatise, Olayiwola; Kennedy, Ian; Petkos, G.; Koh, Adrian

doi:10.1109/tdmr.2010.2102026

Cited by 15 publications

(5 citation statements)

References 14 publications

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“…At a given working condition, as long as the working condition is not changed, the predicted real-time power loss should have almost the same value as the normal power loss [10][11][12][13][14]. Thus, a significant difference between real-time power loss and normal power loss is an indication that there are some problems.…”

Section: Introductionmentioning

confidence: 99%

Power Loss Prediction for Aging Characteristics and Condition Monitoring for Parallel‐Connected Power Modules Using Nonlinear Autoregressive Neural Network

Yang

et al. 2019

Complexity

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Power modules connected in parallel may have different electrothermal performance variances resulting from aging because of the nonuniform rate of degradation; different electrothermal performance variances mean different current sharing, different junction temperature, and power losses, which will directly influence the overall characteristics of them. Thus, it is essential to monitor the condition and evaluate the degradation grade to improve the reliability of large-scale power modules. In this paper, the impact of thermal resistance difference on current sharing, junction temperature, and power loss of parallel-connected power modules has been discussed and analyzed. Additionally, a methodology is proposed for condition monitoring and evaluation of the power modules without intruding them by recognizing the increase in external power loss due to internal degradation from aging. In this method, power modules are deemed as a whole system considering only external factors associated with them, all important electrical and thermal parameters are classified as the inputs, and power loss is considered as the output. Firstly, power dissipation is predicted by models using NARX (nonlinear autoregressive with exogenous input) neural network. Then, a monitoring method is illustrated based on the prediction model; a reasonable criterion for the error between the normal and the predicted real-time power loss is established. Finally, the real-time condition and the degradation grade of aging can be evaluated so that the operator can take suitable operating measures by means of this approach. Experimental results validated the effectiveness of the proposed methodology.

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Section: Introductionmentioning

confidence: 99%

Power Loss Prediction for Aging Characteristics and Condition Monitoring for Parallel‐Connected Power Modules Using Nonlinear Autoregressive Neural Network

Yang

et al. 2019

Complexity

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“…Devices connected in parallel may begin the operational mission profile with almost identical thermal and electrical parameters, however, over time, may develop variations resulting from non-uniform rates of degradation. For instance, the thermal resistances of the power devices typically increase as a result of solder joint degradation due to thermo-mechanical stresses arising from coefficient of thermal expansion (CTE) mismatch between the die and the substrate [1][2][3][4]. Depending on the position of the device on the heat-sink, this effect of mechanical degradation may not occur at the same rate.…”

Section: Introductionmentioning

confidence: 99%

“…Another source of possible variation is the electrical switching time constant, which is determined by the gate resistance and internal capacitances. Over the operating life of the power device, thermomechanical stresses from temperature and power cycles mean that the gate resistance is likely to increase as a result of wirebond mechanical degradation [2,5]. If this degradation occurs at a non-uniform rate between parallel connected devices, then a situation can arise whereby parallel connected devices have significantly different gate resistances and therefore switch at different rates.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Electrothermal Nonuniformities on Parallel Connected SiC Power Devices Under Unclamped and Clamped Inductive Switching

Alatise

Gonzalez

et al. 2016

IEEE Trans. Power Electron.

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“…Methods of gate voltage VG behaviour monitoring [12,20,27,28] and gate current IG measurement [29][30][31] have also been researched recently. Precision measurement of resistances can monitor bond wire lift-off, as increases in conductive resistance is the direct impact of the failure [32][33][34]. By monitoring the capacitance of the flying capacitor Css , one of the major origins of failure in IGBT, voltage unbalance can be detected [35].…”

Section: Introductionmentioning

confidence: 99%

State Detection of Bond Wires in IGBT Modules Using Eddy Current Pulsed Thermography

Tian

Cheng

et al. 2014

IEEE Trans. Power Electron.

167

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Insulated gate bipolar transistor (IGBT) modules are important safety critical components in electrical power systems. Bond wire lift-off, a plastic deformation between wire bond and adjacent layers of a device caused by repeated power/thermal cycles, is the most common failure mechanism in IGBT modules. For the early detection and characterisation of such failures, it is important to constantly detect or monitor the health state of IGBT modules， and the state of bond wires in particular. This paper introduces eddy current pulsed thermography (ECPT), a non-destructive evaluation (NDE) technique, for the state detection and characterisation of bond wire lift-off in IGBT modules. After the introduction of the experimental ECPT system, numerical simulation work is reported. The presented simulations are based on the 3-D electromagnetic-thermal coupling finite-element-method (FEM) and analyse transient temperature distribution within the bond wires. This paper illustrates the thermal patterns of bond wires using inductive heating with different wire statuses (lifted-off or well bonded) under two excitation conditions: non-uniform and uniform magnetic field excitations. Experimental results show that uniform excitation of healthy bonding wires, using a Helmholtz coil, provides the same eddy currents on each, whilst different eddy currents are seen on faulty wires. Both experimental and numerical results show that ECPT can be used for the detection and characterisation of bond wires in power semiconductors through the analysis of the transient heating patterns of the wires. The main impact of this work is that it is the first time electromagnetic induction thermography, so-called ECPT, has been employed on power/electronics devices. Because of its capability of contactless inspection of multiple wires in a single pass, and as such it opens a wide field of investigation in power/electronics devices for failure detection, performance characterisation and health monitoring.

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Reliability of Repetitively Avalanched Wire-Bonded Low-Voltage Discrete Power Trench n-MOSFETs

Cited by 15 publications

References 14 publications

Power Loss Prediction for Aging Characteristics and Condition Monitoring for Parallel‐Connected Power Modules Using Nonlinear Autoregressive Neural Network

Power Loss Prediction for Aging Characteristics and Condition Monitoring for Parallel‐Connected Power Modules Using Nonlinear Autoregressive Neural Network

The Effect of Electrothermal Nonuniformities on Parallel Connected SiC Power Devices Under Unclamped and Clamped Inductive Switching

State Detection of Bond Wires in IGBT Modules Using Eddy Current Pulsed Thermography

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