Lifetime Estimation Models Research Articles

Combined effect of random porosity and surface defect on fatigue lifetime of additively manufactured micro-sized Ti6Al4V components: An investigation based on numerical analysis and machine learning approach

Surface defects and internal porosities resulting from the additive manufacturing process contribute to a scatter in fatigue lifetime, increasing uncertainty in applications such as aerospace engineering. This study proposes a combined approach of machine learning and finite element modelling to explore the interaction between random porosity distribution and high surface roughness on the fatigue lifetime of micro-sized additively manufactured parts. To achieve this, a high-fidelity finite element model is constructed with randomly distributed porosities and surface defects. A fatigue lifetime estimation model, developed using a combination of continuum damage mechanics and the theory of critical distance, is then applied to predict lifetime using effective stress extracted from simulations. A total of 1200 simulations are conducted using these models to examine the interaction effects of subsurface porosity and surface defects on localized stress distribution and fatigue lifetime. Subsequently, two machine learning algorithms, Support Vector Regression and Kernel Ridge Regression, are employed to estimate fatigue lifetime, accounting for the effects of randomly distributed subsurface porosities and surface defects. Eighty percent of the developed finite element models are employed to construct an input dataset, incorporating geometrical features of pores, and to train the algorithms, while the remaining 20% are reserved for verification purposes. The observed results demonstrate that the combined effect of random porosity and surface defects increases fatigue scatter behaviour, leading to greater uncertainty in lifetime prediction. Furthermore, the machine learning algorithms exhibit promising prediction performance.

Energy consumption analytical modeling of NB-IoT devices for diverse IoT applications

Internet of things (IoT) has been employed in recent years across multiple disciplines in the Fifth Generation (5G) era. The low power consumption of the devices allows long battery lifetimes with increasing wireless coverage ranges. This paper presents a comprehensive power consumption model for battery lifetime estimation in narrowband IoT (NB-IoT), which is based on the user equipment (UE) state diagram and considers the extended discontinuous reception (eDRX) and power saving mode (PSM) mechanisms. This model has been used to simulate the effect of varying NB-IoT link parameters, covering a range of values defined in the specification, corresponding to a wide range of applications. Indeed, this study focuses on mathematical analysis of UE power consumption, mainly for NB-IoT communication applications. Repetitions, as defined in the standard, have also been considered in the analysis. Extensive simulations have been carried out to show the power of the proposed model, which provides accurate results for a wide variety of network parameters and let the network designer to select the most appropriated setup. They also show that the value of link parameters must be carefully selected to achieve a battery lifetime of more than a decade with a standard battery of 5 Wh capacity.

Modeling and Experimental Validation for Battery Lifetime Estimation in NB-IoT and LTE-M

Internet of Things (IoT) is one of the main features in 5G. Low-power wide-area networking (LPWAN) has attracted enormous research interests to enable large scale deployment of IoT, with the design objectives of low cost, wide coverage area, as well as low power consumption. In particular, long battery lifetime is essential since many of the IoT devices will be deployed in hard-to-access locations. Prediction of the battery lifetime depends on the accurate modelling of energy consumption. This paper presents a comprehensive power consumption model for battery lifetime estimation, which is based on User Equipment(UE) states and procedures, for two cellular IoT technologies: Narrowband Internet of Things (NB-IoT) and Long Term Evolution for Machines (LTE-M). A measurement testbed has been setup and the proposed model has been tested and validated via extensive measurements under various traffic patterns and network scenarios, achieving the modelling inaccuracy within5%. The measurement results show that the battery lifetime of an IoT device can reach up to 10 years as required by 3GPP, with proper configuration of the traffic profile, the coverage scenario, as well as the network configuration parameters.

Lifetime estimation model of vapor cells in atomic magnetometers

A lifetime estimation model is proposed by characterizing the consumption of the components inside the atomic vapor cells in this work. The buffer gas leakage and alkali metal consumption in vapor cells will significantly destroy the performance of atomic magnetometers. Combining the light absorption method and aging experiments, the deterioration of helium pressure, rubidium vapor density, and cell wall transmittance were obtained to construct the lifetime estimation model that depends on time, working temperature, and initial contents. Then, the causes and consequences of these deteriorations were analyzed, and the combination of theoretical analysis and experimental data showed that the vapor cell invalidation caused by these factors conforms to the Weibull distribution. In order to establish the relationship between the component consumption and the performance of the magnetometer constituted by this cell, a single-beam magnetometer prototype was designed for sensitivity testing. Experiments have shown that the sensitivity of magnetometer is rapidly deteriorating after operating 600 h under 150 °C, which is mainly related to alkali metal consumption. Additionally, 200 °C is a trade-off aging experimental temperature between the aging efficiency and the stability of the cell. The proposed model can be applied to optimize the lifetime of the vapor cells used not only in magnetometers but also in gyroscopes and atomic clocks.

수소연료전지차용 라이너 소재의 기계적 물성을 활용한 열 열화 수명 모델 개발

Purpose: With the development of eco-friendly automobiles, the demand for the reliability of newly applied parts is increasing. An analysis of the lifetime estimation needs to be required because liners made of polymer materials must have heat-resistant properties to withstand high temperatures. Simultaneously, localized products should be evaluated for production performance and reliability.<BR>Methods: The thermal degradation of liner material due to thermal exposure time is investigated by evaluating the tensile strength and Rockwell hardness. Based on the thermal degradation test results, a reliability analysis was conducted and tested specimens were analyzed using optical microscopy and scanning electron microscopy.<BR>Results: With the thermal exposure time prolonged, a slight increase in mechanical properties and afterward, decrease of the properties was observed. The parameters of the Weibull distribution and the activation energies related to the mechanical properties were derived from the established Arrhenius lifetime estimation model. Additionally, the obtained result is higher than the calculated lifetime using the temperature spectrum of FCEV.<BR>Conclusion: In this study, a lifetime estimation model based on the thermal degradation of a liner material was developed. In the case of a localized product, it was confirmed that improvements in the forming process can enhance robustness.

Reliability modeling and assessment of solder joints of electronic assemblies under mixed exposure to mechanical loads

PurposeIn this paper, a lifetime estimation model for the solder joint is proposed which is capable of considering both severe and running mechanical shocks which is the real case in electric converters in the automotive and aerospace applications. This paper aims to asses the reliability of the solder joint under mixed exposure of mechanical loads.Design/methodology/approachMechanical failure process may put at risk the perfect performance of any kinds of electronic systems regardless of the applications they are prepared for. Observation of solder joint health in an electronic assembly under simultaneous exposure of severe and running shocks is an open problem. Three commonly used soldering compositions are considered while the electronic assembly is exposed to three well-known driving cycles.FindingsThe results show that the best performance is achieved using SAC405 soldering alloy in comparison with Sn63Pb37 and SAC387 solder alloy. Consideration of mixed exposure to the mechanical loads leads to much more accurate lifetime estimation of the solder joint in the electronic assemblies.Originality/valueThe originality of the paper is confirmed.

자동차 파워트레인 부품용 플라스틱 소재의 내열 열화 수명예측 연구

Purpose: The engine room temperature of automobiles is constantly rising as the turbo system installation rate increases. On the other hand, plastic materials are very sensitive on temperature changes. Therefore, the heat aging characteristics of plastics applied to automobile powertrains and the lifetime estimation of plastic parts were studied.BRMethods: Heat aging test by temperature condition was conducted for plastic materials applied to automobile powertrain parts. Also, field vehicle operating conditions and environmental temperature were measured. Based on heat aging test and field data, reliability analysis was conductedBRResults: The influence on the mechanical properties was identified, and the acceleration evaluation limit temperature was obtained through the analysis of the degradation mechanism of plastics. The activation energies for mechanical properties and composition of plastic materials were derived from established Arrhenius lifetime estimation model. Also, damage prediction in real environmental conditions and limit temperature to resist in life time of several structural powertrain plastic parts were analyzed and safety factor or limit temperature were determined for these plastic parts.BRConclusion: A method for analyzing thermal damage in the actual environment of the plastic powertrain parts was established.

Evaluation of LoRa Technology in Flooding Prevention Scenarios.

Global climate change originates frequent floods that may cause severe damage, justifying the need for real-time remote monitoring and alerting systems. Several works deal with LoRa (Long Range) communications over land and in the presence of obstacles, but little is known about LoRa communication reliability over water, as it may happen in real flooding scenarios. One aspect that is known to influence the communication quality is the height at which nodes are placed. However, its impact in water environments is unknown. This is an important aspect that may influence the location of sensor nodes and the network topology. To fill this gap, we conducted several experiments using a real LoRa deployment to evaluate several features related to data communication. We considered two deployment scenarios corresponding to countryside and estuary environments. The nodes were placed at low heights, communicating, respectively, over the ground and over the water. Measurements for packet loss, received signal strength indicator (RSSI), signal-to-noise ratio (SNR) and round-trip time (RTT) were collected during a period of several weeks. Results for both scenarios are presented and compared in this paper. One important conclusion is that the communication distance and reliability are significantly affected by tides when the communication is done over the water and nodes are placed at low heights. Based on the RTT measurements and on the characteristics of the hardware, we also derive a battery lifetime estimation model that may be helpful for the definition of an adequate maintenance plan.

The Modelling of an Energy Efficient Algorithm Considering the Temperature Effect on the Lifetime of a Node in a Wireless Network

In wireless ad-hoc networks the nodes may be placed in a remote area and with no fixed infrastructure. Wireless nodes have limited energy resources which act as a key factor to estimate the node lifetime. Most research is based on the power aware schemes, which takes advantage of the remaining energy of wireless nodes. Existing schemes estimate remaining energy based on only current consumption and voltage, leading to erroneous estimations that result in early power exhaustion of nodes that affects real world deployment, because the residual energy in real batteries is also affected by temperature, charge cycle, aging, self-discharge, and various other factors. A lifetime estimation model examines the battery characteristics to investigate their performance under varying operational conditions more precisely. In this article a lifetime estimation model is proposed, it takes into account the varying environmental temperatures effecting battery performance. An experimental approach is proposed to determine the actual capacity of ad-hoc nodes under varying temperatures.

Design Optimization of a Residential PV-Battery Microgrid With a Detailed Battery Lifetime Estimation Model

The interest in installing photovoltaic (PV)-based microgrids has increased significantly in the last few years due to the urgent need for reducing greenhouse gas emissions and improving the reliability as well as the quality of power supply, particularly in developing countries. The design of a microgrid is challenging since multiple components and complicated operating conditions have to be taken into account. In this article, a comprehensive method for optimal design of a class of residential PV-battery microgrids is proposed to determine the optimal number of lead-acid batteries and PV panels, the optimal battery bank depth of discharge (DOD) value, and the optimal tilt angle of the PV panels. The aim of the optimization is to minimize the levelized cost of energy (LCOE) where the limitation of the annual total loss of the power supply and the operational constraints are considered. In addition, a detailed model for battery lifetime estimation is introduced based on the physico-chemical mechanism of the lead-acid battery. Moreover, the effect of design parameters, e.g., the size and DOD of the battery bank on the battery capacity degradation, the PV-panel number and battery lifetime on LCOE, is investigated. Computation results demonstrate that the proposed method is capable of optimizing the size of the microgrid components and the other design parameters while satisfying all technical and operational constraints.

Comparative Analysis of IGBT Parameters Variation Under Different Accelerated Aging Tests

Power semiconductor devices are vulnerable to thermomechanical fatigue due to temperature cycling caused by system load profile and external climatic conditions. As the reliability performance of power semiconductor devices in power converter systems is determined by this temperature stress, accelerated power or thermal cycling test are used in this article to emulate the temperature stress. The failure mechanisms due to temperature stress can be studied, and it also helps to develop the lifetime estimation model for power semiconductor devices. In the past, active power cycling and passive thermal cycling tests are investigated separately to develop the failure mechanism model based on the device’s electrical parameter changes and scanning electron microscopic (SEM) analysis. However, there is no detailed report on, how different temperature stresses emulated by dc, pulsewidth modulation (PWM) power cycling, and thermal cycling affects the device physically, and how much changes it introduces in the device’s electrical parameters. Therefore, this article presents an experimental investigation of active dc, PWM power cycling and passive thermal cycling approaches on 1.2-kV 50-A fast trench insulated gate bipolar junction transistor (IGBT) devices. The device electrical parameters, such as ON-state voltage, threshold voltage, gate current, gate voltage, and thermal resistance, were monitored during the study to classify the effects of temperature stress produced by dc, PWM power cycling, and thermal cycling on these electrical parameters.

A Model to Estimate the Lifetime of BESS for the Prosumer Community of Manufacturers with OGS

Abstract Onsite generation system (OGS) with renewable sources for modern manufacturing plant is considered as a critical alternative energy source for the manufacturers. Prosumer community can be formed by aggregating such manufacturers to achieve a mutual goal of sustainable and resilient power system. As the sustainability of the network depends on the reliable operations of each component in the network, it is required to monitor the performance and lifetime of the components existed in the network. One of the critical as well as costly components used to enhance the reliability and performance of the network is the battery energy storage system (BESS). The paper proposes a lifetime estimation model for the BESS using an integrated approach of cellular automata and system dynamic (SD) to prevent any sudden power outage and build a reliable energy management framework for the community. The major factors such as energy demand of the manufacturing plant, intermittent generation from the OGS, energy sharing capability of the prosumers etc. are considered to simulate the model and determine the amount of battery degradation. Based on the estimated lifetime of the battery, the manufacturers further can control the energy management plan (charging/discharging scheme) to prolong the battery lifetime and ensure a reliable operation for the community. A numerical case study is simulated to illustrate the effectiveness of the model.

Stress-Based Model for Lifetime Estimation of Bond Wire Contacts Using Power Cycling Tests and Finite-Element Modeling

In this paper, a lifetime model for bond wire contacts of insulated gate bipolar transistors (IGBT) power modules is reported. This model is based on power cycling tests obtained under accelerated conditions, and a finite-element model taking into account the electrical, thermal, and mechanical coupling. It allows us to estimate the bond wire lifetime for a large scale of junction temperature swing amplitudes (ΔT <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</sub> ) and stress durations (t <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ON</sub> ). To build it, a numerical design of experiment was performed in both high and low stress values (ΔT <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</sub> ). Then, a strain-life curve has been constructed where the average strain values on a defined volume around the contact areas between top-metallization and the most exposed bond wires to fatigue and liftoff have been used. As a result, it has been shown that the total strain is linearly dependent with ΔT <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</sub> and power law dependent with t <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ON</sub> . The combination of the strain-life relation and the strain dependency with stress parameters leads to the lifetime relationship. The obtained lifetime model has been satisfactorily validated with some additional experimental points obtained from literature and with a large range of values for t <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ON</sub> . This methodology can be easily replicated to other structures and is quite generic.

The Influence of Path Dependence on the Degradation of Lithium-Ion Batteries in Electric Vehicles

Gaining understanding into battery ageing is essential, especially for electric vehicles (EVs) where the reliability of the vehicle is dependent on battery performance, capacity and lifetime. Studying the causes of degradation, the conditions that accelerate degradation and the end of life criteria of batteries under realistic EV conditions enables us to make accurate predictions of the lifetime of a cell. During usage, the battery will experience ageing caused by multiple factors, but broadly, these can be grouped into two ageing types: calendar ageing when the cell is at rest and cyclic ageing when it is in use. Degradation path dependency is the impact on degradation caused by the order in which a cell is exposed to different ageing conditions. The order in which the cell experiences each type of ageing can affect the ageing of a cell by influencing the interactions between degradation mechanisms. Studying path dependency allows us to determine how the interactions between these degradation mechanisms impacts state of health [1]. An experimental study is being conducted which exposes groups of lithium-ion NCA 18650 cells to various blended load profiles consisting of calendar and cyclic ageing in various orders. The ratio of calendar and cyclic ageing in the profiles is constant through the tests to allow comparability between the degradation data collected. The profiles for groups 1 and 3 are designed to expose the cells to 1 day of cyclic ageing followed by 5 days of calendar ageing at C/2 and C/4 respectively. The cells in groups 2 and 4 experience 2 days of cyclic ageing and 10 days of calendar ageing at C/2 and C/4 respectively. The cyclic ageing portion of the profile is conducted using constant current charge/discharge and the calendar ageing portion is conducted at 90% state of charge (SoC). The stress factors that the cell is exposed to are controlled in terms of environmental temperature, depth of discharge, SoC and C-rate. This aims to ensure that the data obtained from this study are an accurate representation of the degradation effects due to path dependency only. Specifically, two groups of cells that are exposed to the same calendar/cyclic ageing in different orders are shown in the supporting image. Although group 1 and group 3 experience the same amount of ageing, the order in which the cell experiences the ageing leads to a difference in state of health in terms of capacity and resistance. The current lifetime estimation models superimpose calendar and cyclic aging however the early indications from the results obtained suggests that path dependency does exist, meaning that existing empirical ageing models may need to be reconsidered or modified in order to account for coupling between different ageing mechanisms [2]. Image Caption: Normalised capacity graphs highlighting the impact of path dependency on capacity fade rate between two groups of cells that are exposed to the same aging conditions in different orders. [1] M. Dubarry, A. Devie, and K. McKenzie, “Durability and reliability of electric vehicle batteries under electric utility grid operations: Bidirectional charging impact analysis,” J. Power Sources, vol. 358, pp. 39–49, 2017. [2] M. Schimpe, M. E. von Kuepach, M. Naumann, H. C. Hesse, K. Smith, and A. Jossen, “Comprehensive Modeling of Temperature-Dependent Degradation Mechanisms in Lithium Iron Phosphate Batteries,” ECS Trans., vol. 80, no. 13, pp. 147–170, 2017. Figure 1

Charging Automation for Electric Vehicles: Is a Smaller Battery Good for the Wireless Charging Electric Vehicles?

Dynamic wireless charging (DWC) is an emerging technology that enables the batteries of electric vehicles (EVs) to charge automatically while the vehicles are in motion. The DWC-EV system addresses the challenges inherent in battery technology, such as the short driving range, long recharging time, and high price. Compared with conventional plug-in EVs, the DWC-EV can charge a battery more frequently because it can be done while the EV is in motion from the charging infrastructure installed on the road. In this paper, we analyze how this frequent-charging characteristic of DWC-EV can affect the battery lifetime in the DWC-EV. We first introduce a mathematical model to evaluate the economic cost of the DWC-EV for a given battery size. A battery degradation model is incorporated to account for the quantitative relationship between the installation of the charging infrastructure and battery life extension. We then use the model to analyze how the economic cost varies with the size of the battery. Our preliminary findings provide insight into the relationship between DWC from the charging infrastructure and the battery’s lifetime. Note to Practitioners —There is a tradeoff between power track allocation and battery size in DWC buses. It has been known that DWC buses need not equip a large battery because the battery can be charged frequently from the power track along the route. Also, it has been agreed that frequent shallow charging with DWC can improve the battery’s lifetime compared to infrequent deep charging. We verify these common beliefs and agreement with a mathematical approach with a widely used battery lifetime estimation model. Our quantitative model indicates that the DWC can positively improve battery lifetime, but this positive effect is always true only when the battery is large enough, even if the battery is charged frequently with DWC. The presented optimization model suggests that the lifelong economic benefit of DWC-based bus transit can be realized with optimal allocation of the power track with a sufficiently large battery.

Al-Si piston alloy behavior under combined mechanical and thermal cyclic loading with superimposed high-frequency thermal cycling

Abstract On pistons for diesel direct injection engines, the thermally high loaded bowl rim is exposed to high-cycle mechanical and high-cycle thermal loading during each combustion event in addition to the thermal cycling induced by variable engine loading, e. g. between idle and full load. This combined loading at various overall temperatures during engine operation contributes to material damage and finally to a limited service life. In the past, the high-cycle thermal loading has neither been experimentally investigated nor incorporated into a numerical model for lifetime estimation. The work described in this paper deals with the setup of an experimental test procedure on samples taken from components for which the effects of slow temperature cycling, fast temperature cycling and mechanical cyclic fatigue loading can be combined in different ratios. The aim of the investigation is to characterize the sample lifetime with respect to varied test conditions in order to differentiate alloy- or process-related material variations in support of process and material development.

The analysis of initial probability distribution in Markov Chain model for lifetime estimation

Fatigue crack growth is a stochastic phenomenon due to the uncertainties factors such as material properties, environmental conditions and geometry of the component. These random factors give an appropriate framework for modelling and predicting a lifetime of the structure. In this paper, an approach of calculating the initial probability distribution is introduced based on the statistical distribution of initial crack length. The fatigue crack growth is modelled and predicted by a Markov Chain associated with a classical deterministic crack Paris law. It has been used in calculating the transition probabilities matrix to represent the physical meaning of fatigue crack growth problem. The equation of Paris law provides information regarding the stress intensity factor and material properties in predicting the crack growth rate. The data from the experimental work under constant amplitude loading was analyzed using the Markov Chain model. The results provide a reliable prediction and show excellent agreement between proposed model and experimental result. The reliability of the model can be an effective tool for safety analysis of structure.

A Survey of Network Lifetime Maximization Techniques in Wireless Sensor Networks

Emerging technologies, such as the Internet of Things, smart applications, smart grids, and machine-to-machine networks stimulate the deployment of autonomous, self-configuring, large-scale wireless sensor networks (WSNs). Efficient energy utilization is crucially important in order to maintain a fully operational network for the longest period of time possible. Therefore, network lifetime (NL) maximization techniques have attracted a lot of research attention owing to their importance in terms of extending the flawless operation of battery-constrained WSNs. In this paper, we review the recent developments in WSNs, including their applications, design constraints, and lifetime estimation models. Commencing with the portrayal of rich variety definitions of NL design objective used for WSNs, the family of NL maximization techniques is introduced and some design guidelines with examples are provided to show the potential improvements of the different design criteria.

GELSenVAC: A Novel Sensor Network Framework for WSN Simulation

Nowadays, Wireless Sensor Networks (WSN) are emerging because of the technological developments in wireless communication and the advancements in miniaturization of sensor hardware nodes. WSN is an Adhoc network with more number of nodes densely deployed. The main focus of any WSN is to maximize the lifetime of the network as the sensor nodes are having limited battery energy and the nodes are unattended. Lifetime of the WSN depends on various parameters such as hardware used, number of nodes, deployment strategies, MAC protocol, routing protocol, sampling rate, sampling time, etc. To determine the lifetime of WSN apriori to real time deployment, simulator software is used for evaluating the impact of various parameters influencing the lifetime. Global Mobile Simulator (GloMoSim) is one such text based simulator software used for simulating wireless networks. GloMoSim is not supporting the required features, viz., sensor specific MAC and routing protocols, energy model for lifetime estimation, and charting facility for WSN Simulation. In this paper, the design of novel easy to use GUI with Energy model based Lifetime estimation supported Sensor network framework with Visualization, Application statistics, and Charting facility tools, GELSenVAC, is proposed and implemented. It consists of hardware support for TelosB, MicaZ motes, Sensor MAC (S-MAC) protocol support in data link layer, energy model for lifetime estimation, facility to view application level statistics, and charting facility to generate lifetime charts, on top of GloMoSim environment. By using this framework, designers can easily simulate their own WSN, estimate the lifetime, and select suitable parameters to increase the lifetime of the network. The designed framework is tested by simulating a WSN. The computed lifetime and the results obtained using the tools supported by this framework are presented.

ON-state Reliability of Cu Atom Switch Under Current–Temperature Stress

The dc current-stress tolerance of the ON-state Cu atom switch is evaluated at elevated temperature. It is revealed that the reset-direction current stress causes time-dependent failures, which originate from the $E$ -field-driven diffusion of Cu in the conducting bridge. A new empirical lifetime estimation model, including the Joule heating effect, gives an allowable maximum current per atom switch of $I_{{\textrm {max}}}= 115~\mu \text{A}$ , which is large enough to satisfy the requirements for signal routing under currents that are average (18 $\mu \text{A}$ ) and peak (63 $\mu \text{A}$ ) in the reconfigurable switch block operated at 500 MHz at 125 °C.