Subsea power cables are critical assets within the distribution and transmission infrastructure of electrical networks. Over the past two decades, the size of investments in subsea power cable installation projects has been growing significantly. However, the analysis of historical failure data shows that the present state-of-the-art monitoring technologies do not detect about 70% of the failure modes in subsea power cables. This paper presents a modeling methodology for predicting damage along the length of subsea cables due to environmental conditions (e.g., seabed roughness and tidal flows) which result in the loss of the protective layers on the cable due to corrosion and abrasion (accounting for over 40% of subsea cable failures). For a defined cable layout on different seabed conditions and tidal current inputs, the model calculates the cable movement by taking into account the scouring effect and then it predicts the rate at which the material is lost due to corrosion and abrasion. Our approach integrates accelerated aging data using a Taber test which provides abrasion wear coefficients for the cable materials. The models have been embedded into a software tool that predicts the life expectancy of the cable and demonstrated for narrow conditions, where the tidal flow is unidirectional and perpendicular to the power cable. The paper also provides discussion on how the developed models can be used with other condition monitoring data sets in a prognostics framework.
This paper presents mean fatigue lifetime prediction of a wire-bond structure model in power electronic module using a failure physics approach that integrates high fidelity modelling and reduced order modelling. Loading current with variable amplitudes is applied to a finite element model of simplified wirebond structures. The resulting accumulated fatigue damage due to random loads is predicted by using reduced order modelling based on failure physics, a cycle counting algorithm, and various nonlinear fatigue damage models widely used in the literature. The reduced order modelling approach based on failure physics uses prediction data for the electro-thermo-mechanical behaviour of the wire-bond design of a power module obtained through non-linear transient finite element simulations, in particular for the fatigue lifetime of the aluminium wire attached to the silicon chip of the wire in the module. The reduced order models that capture the black box function of the accumulated plastic strain are used in predicting the mean fatigue life time of the wire bond structure under random loads. One of the widely used cycle counting algorithms, rainflow counting algorithm, is used to count cycles of the temperature profile at the specific point of the wire bond structure in a power electronic module. The cycle data from the rainflow algorithm mean life time of the wire bond structure are predicted with various cumulative fatigue models. Non-linear cumulative fatigue models such as damage curve approach (DCA), double linear damage rule (DLDR), and double damage curve approach (DDCA), and linear cumulative fatigue damage model such as Palmgren-Miner rule are used to predict the mean fatigue life of the wire bond structure, and the results are compared.
Modelling and analysis of vibration of an IGBT power electronic module (PEM) structure were undertaken. PEM structure considered in this study was without molding compound and wirebonds. The most critical resonant frequency was identified by modal analysis. At the critical frequency of 1345Hz, for the vertical displacement of the base excitation, subsequent stress distribution on the PEM structure was analysed. Concurrent vibration and thermo-mechanical fatigue loads on the reliability of PEM structure solder interconnects were also estimated by widely used linear damage superposition approach. It was concluded that the at critical resonant frequency the vibration induced damage is more severe than the thermo-mechanical fatigue loading. In addition, a quarter car model (QCM) was used to mimic the dynamic interaction between the rough road surface and an electric vehicle (EV) in order to analyse the road surface roughness induced excitation on the PEM structure in the engine compartment. Stress and strain distribution on the PEM structure due to road surface roughness were analysed. Furthermore, three Krylov subspace based model order reduction (MOR) techniques were applied to the resulting dynamic system in vibration analysis. Due to the limits on computing resources, a submodel was utilized for MOR analysis. Within the three MOR techniques, Passive Reduced order Interconnect Macromodeling Algorithm (PRIMA) MOR technique performs better than the other techniques. Computational time ratio between reduced system iteration and the full system iteration is 1:53.
This paper discusses the design for reliability of a sintered silver structure in a power electronic module based on the computational approach that composed of high fidelity analysis, reduced order modelling, numerical risk analysis, and optimisation. The methodology was demonstrated on sintered silver interconnect sandwiched between silicon carbide chip and copper substrate in a power electronic module. In particular, sintered silver reliability due to thermal fatigue material degradation is one of the main concerns. Thermomechanical behaviour of the power module sintered silver joint structure is simulated by finite element analysis for cyclic temperature loading profile in order to capture the strain distribution. The discussion was on methods for approximate reduced order modelling based on interpolation techniques using Kriging and radial basis functions. The reduced order modelling approach uses prediction data for the thermo-mechanical behaviour. The fatigue lifetime of the sintered silver interconnect and the warpage of the interconnect layer was particular interest in this study. The reduced order models were used for the analysis of the effect of design uncertainties on the reliability of the sintered silver layer. To assess the effect of uncertain design data, a method for estimating the variation of reliability related metrics namely Latin Hypercube sampling was utilised. The product capability indices are evaluated from the distributions fitted to the histogram resulting from Latin Hypercube sampling technique. A reliability based design optimisation was demonstrated using Particle Swarm Optimisation algorithm for constraint optimisation task consists of optimising two different characteristic performance metrics such as the thermo-mechanical plastic strain accumulation per cycle on the sintered layer and the thermally induced warpage.
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