Developing Prognostic Models Using Duality Principles for DC-to-DC Converters

Abstract

Abstract-Within the field of Integrated SystemHealth management, there is still a lack of technological approaches suitable for the creation of adequate prognostic model for large applications whereby a number of similar or even identical subsystems and components are used. Existing similarity among a number of different systems, which are comprised of similar components but with different topologies, can be employed to assign the prognostics of one system to other systems using an inference engine. In the process of developing prognostics, this approach will thereby save resources and time. This paper presents a radically novel approach for building prognostic models based on system similarity in cases where duality principle in electrical systems is utilized. In this regard, unified damage model is created based on standard Tee/Pi models, prognostics model based on transfer functions, and RUL estimator based on how energy relaxation time of system is changed due to degradation. An advantage is; the prognostic model can be generalized such that a new system could be developed on the basis and principles of the prognostic model of other systems. Simple electronic circuits, DC-to-DC converters, are to be used as an experiment to exemplify the potential success of the proposed technique validated with prognostics models from particle filter.

Stochastic RUL Calculation Enhanced With TDNN-Based IGBT Failure Modeling

“…In a normal distribution, mean and variance parameters [cf. (3)] are estimated in order to obtain the best fit probability distribution function for each degradation phase.…”

“…On the other hand, data-driven approaches start with accelerating aging tests followed with pre-processing (filtering) and classification for eliminating noise from collected data, and damage model formulation followed by RUL estimation. There is also an important initial step (known as feature extraction step) to investigate what signals should be monitored that would allow prognostics to be successfully developed based on features extracted from those signals [3], [4].…”

“…Maximum likelihood estimation (MLE) is used as an objective function to maximize the density probability function (i.e., normal distribution function). A Normal distribution as shown in (3) is the probability distribution of the IGBT estimated degradation phase…”

Physics-based prognostic modelling of filter clogging phenomena

“…Particle filters, also called as 'Sequential Monte Carlo Estimators', have been used widely in prognostics, peculiarly integrated in physics-based models. Some of the examples found in the literature are; fatigue crack propagation modelling for various engineering structures [28], [29], [30], [31], [32] and [33], battery capacity modelling [29], [34] and [35], centrifugal pump degradation modelling [36], thermal processing unit degradation [37], pneumatic valve modelling [38], DC-DC converter system level degradation modelling [39], Isolated Gate Bipolar Transistor (IGBT) degradation modelling [40], Proton Exchange Membrane Fuel Cells (PEMFC) life modelling [41], Lumen degradation modelling for LED light sources [42]. The list can be expanded to various engineering prognostic applications.…”

DC current bus distributed power system and its stability analysis

“…Thus, current type DC/DC converters are required to drive them efficiently. Some literature focuses on the derivation and modelling of current type converters [14, 19, 20].…”