This paper proposes the experiments and setups for studying diagnosis and prognosis of electrolytic capacitors in DC-DC power converters. Electrolytic capacitors and power MOSFET’s have higher failure rates than other components in DC-DC converter systems. Currently, our work focuses on experimental analysis and modeling electrolytic capacitors degradation and its effects on the output of DC-DC converter systems. The output degradation is typically measured by the increase in Equivalent series resistance and decrease in capacitance leading to output ripple currents.Typically, the ripple current effects dominate, and they can have adverse effects on downstream components. A model based approach to studying degradation phenomena enables us to combine the physics based modeling of the DC-DC converter with physics of failure models of capacitor degradation, and predict using stochastic simulation methods how system performance deteriorates with time. Degradation experiments were conducted where electrolytic capacitors were subjected to electrical and thermal stress to accelerate the aging of the system. This more systematic analysis may provide a more general and accurate method for computing the remaining useful life (RUL) of the component and the converter system.

Electrolytic capacitors are used in several applications rang- ing from power supplies on safety critical avionics equipment to power drivers for electro-mechanical actuators. This makes them good candidates for prognostics and health management research. Prognostics provides a way to assess remaining use- ful life of components or systems based on their current state of health and their anticipated future use and operational con- ditions. Past experiences show that capacitors tend to degrade and fail faster under high electrical and thermal stress condi- tions that they are often subjected to during operations. In this work, we study the effects of accelerated aging due to thermal stress on different sets of capacitors under different conditions. Our focus is on deriving first principles degra- dation models for thermal stress conditions. Data collected from simultaneous experiments are used to validate the de- sired models. Our overall goal is to derive accurate models of capacitor degradation, and use them to predict performance changes in DC-DC converters.

This paper discusses our initial efforts in constructing physics of failure models for electrolytic capacitors subjected to electrical stressors in DC-DC power converters. Electrolytic capacitors and MOSFET’s are known to be the primary causes for degradation and failure in DC-DC converter systems. We have employed a topological energy based modeling scheme based on the bond graph (BG) modeling language for building parametric models of multi-domain systems, such as motors and pumps. In previous work, we have conducted experimental studies to validate an empirical physics of failure model based on Arrhenius Law for equivalent series resistance (ESR) increase in electrolytic capacitors operating under nominal conditions. In this paper, our focus shifts to deriving first principle models of capacitor degradation that explain both the ESR increase and the decrease in capacitance over time when the capacitor is operated under electrical stress conditions. Experimental studies are run in parallel, and data collected from these studies are used to validate the generated models. In the future, they will also be used to compute model parameters, so that the overall goal of deriving accurate models of capacitor degradation, and using them to predict performance changes in DC-DC converters is realized.

Electrolytic capacitors are used in several applications rang- ing from power supplies for safety critical avionics equipment to power drivers for electro-mechanical actuators. Past expe- riences show that capacitors tend to degrade and fail faster when subjected to high electrical or thermal stress condi- tions during operations. This makes them good candidates for prognostics and health management. Model-based prognos- tics captures system knowledge in the form of physics-based models of components in order to obtain accurate predictions of end of life based on their current state of health and their anticipated future use and operational conditions. The focus of this paper is on deriving first principles degradation mod- els for thermal stress conditions and implementing Bayesian framework for making remaining useful life predictions. Data collected from simultaneous experiments are used to validate the models. Our overall goal is to derive accurate models of capacitor degradation, and use them to remaining useful life in DC-DC converters.

Studying and analyzing the ageing mechanisms of electronic components avionics in systems such as the GPS and INAV are of critical importance. In DC-DC power converter systems electrolytic capacitors and MOSFET’s have higher failure rates among the components. Degradation in the capacitors under varying operating conditions leads to high ripples output voltages and currents affecting downstream components leading to cascading faults. For example, in avionics systems where the power supply drives a GPS unit, ripple currents can cause glitches in the GPS position and velocity output, and this may cause errors in the Inertial Navigation (INAV) system, causing the aircraft to fly off course The work in this paper proposes a detail experimental and systematic study on analyzing the degradation phenomenon is electrolytic capacitors under high stress operating conditions. The output degradation is typically measured by an increase in ESR (Equivalent Series Resistance) and decrease in the capacitance value. We present the details of our accelerated ageing methodology along with analysis and comparison of the results.

A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.

This paper proposes a physics based degradation modeling and prognostics approach for electrolytic capacitors. Electrolytic capacitors are critical components in electronics systems in aeronautics and other domains. Degradation's in capacitor and MOSFET components are often the cause of failures in DC-DC converters. For example, prevalent fault effects, such as a ripple voltage surge at the power supply output, can damage interconnected critical subsystems leading to cascading fault propagation. Prognostics in general and in this case electronics components in particular is concerned with the prediction of remaining useful life (RUL) of components and systems. It performs a condition-based health assessment by estimating the current state of health. Furthermore, it leverages the knowledge of the device physics and degradation physics to predict remaining useful life as a function of current state of health and anticipated operational and environmental conditions. Physics-based models capture degradation phenomena in terms of component geometry and energy based principles that define the effect of stressors on the component behavior. This is in contrast to the traditional approach for deriving degradation models from empirical data. Implementing the degradation modeling techniques present a general methodology for estimating lifetimes due to specific failure mechanisms. The failure rate models can be tuned to include parameters that relate to the present health of the device/system and the expected conditions under which it will be operated. The models and algorithms are applied to data from degradation experiments of several COTS capacitors. Results show the efficiency of the approach chosen.

A remaining useful life prediction methodology for elec- trolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good can- didate for component level prognostics and health manage- ment. Prognostics provides a way to assess remaining use- ful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated ag- ing test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This prelim- inary remaining life prediction algorithm serves as a demon- stration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation pro- gression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognos- tics methods typically used for remaining useful life predic- tions in other applications.

This paper proposes a combined energy-based model with an empirical physics of failure model for degradation analysis and prognosis of electrolytic capacitors in DC-DC power converters. Electrolytic capacitors and MOSFET’s have higher failure rates than other components in DC-DC converter systems. For example, in avionics systems where the power supply drives a GPS unit, ripple currents can cause glitches in the GPS position and velocity output, and this may cause errors in the Inertial Navigation (INAV) system causing the aircraft to fly off course. We have employed a topological energy based modeling scheme based on the bond graph (BG) modeling language for building parametric models of electrical domain systems. Our current work adopts a physics of failure model (Arrhenius Law) for equivalent series resistance (ESR) increase in electrolytic capacitors subjected to electrical and thermal stresses. Experiments for capacitor degradation were conducted for collecting degradation ESR data. Parameter re-estimation for the failure model is done using the experimental data. The derived degradation model of the capacitor is reintroduced into the DC-DC converter system model to study changes in the system performance using Monte Carlo simulation methods. Stochastic simulation methods applied to the combined model help us predict how system performance deteriorates with time.

This paper proposes first principles based modeling and prognostics approach for electrolytic capacitors. Electrolytic capacitors and MOSFETs are the two major components, which cause degradations and failures in DC-DC converters. This type of capacitors are known for its low reliability and frequent breakdown on critical systems like power supplies of avionics equipment and electrical drivers of electro-mechanical actuators. Some of the more prevalent fault effects, such as a ripple voltage surge at the power supply output can cause glitches in the GPS position and velocity output, and this, in turn, if not corrected will propagate and distort the navigation solution. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. In this paper, we study the effects of accelerated aging due to thermal stress on sets of capacitors. Our focus is on deriving rst principles degradation models for thermal stress conditions. The degradation data form the basis for developing the model based remaining life prediction algorithm. Our overall goal is to derive accurate models of capacitor degradation, and use them to predict performance changes in DC-DC converters.