Module Failure Research Articles

Thermal cycling characterization of an integrated low-inductance GaN eHEMT power module

To exploit the potential of wide-bandgap semiconductors in high-frequency applications, innovative packaging designs are developed to minimize the parasitic inductance of power modules. This study presents an integrated power module with a hybrid PCB/DBC structure, which uses top-side cooling prepackaged GaN enhancement-mode high-electron-mobility transistors. The module achieves a remarkably low parasitic inductance of 2.65 nH. However, there is relatively scarce research on the reliability of this heterostructure, particularly its sensitivity to thermomechanical stress due to the coefficients of thermal expansion mismatch among material interfaces. In this work, the thermal cycling characteristics of the integrated power module are comprehensively investigated. Electrical and thermal parameters were periodically and separately measured offline on a simplified package to monitor the health conditions and decouple possible synergy and competition effects among the failure modes from all packaging components. A thorough failure analysis was conducted using nondestructive visual inspections and scanning acoustic microscopy, complemented by destructive cross-sectional examination and scanning electron microscopy. The findings identified the delamination of the DBC upper copper layer, which exhibited a conchoidal fracture interface, as the primary factor that contributed to the failure of the power module with increased thermal resistance. Furthermore, the study dissected its initiation and propagation mechanisms. This investigation provides valuable insights for the development of more reliable low-inductance power module designs.

Analysis of False Alarms on DVOR Equipment at I Gusti Ngurah Rai International Airport

According to the Government Regulation of the Republic of Indonesia No.71 of 1996 concerning Airports article 9 Paragraph (1) it is explained that flight navigation facilities can include Non Directional Beacons (NDB), Doppler VHF Omni Range (DVOR), Instrument Landing System (ILS), Radio Detection and Ranging (RADAR). Airports must provide navigation facilities, especially the Doppler VHF Omni Range (DVOR), which is a flight aid that has unlimited (continuous) capabilities, and transmits combined radio signals, including Morse code and data that can enable receiver equipment on aircraft to acquire magnetic bearings. from the station to the airplane using the frequency due to the doppler effect, not the actual azimuth direction to the aircraft but information about the Doppler VHF Omni Range (DVOR) ground station point at I Gusti Ngurah Rai Airport. This study used a qualitative descriptive method with physical checking at the Denpasar Branch of Perum LPPNPI, there was an alarm on the Doppler VHF Omni Range (DVOR) equipment caused by a lightning strike which could not be controlled using LMMS due to failure in several modules. So researchers need to replace several modules affected by the Alarm, namely the LCU (Local Control Unit), CSU (Control Sector Unit), and ASU (Air STARTER UNIT) and do the finishing by checking the power and settings on the monitor, resulting in a Doppler VHF Omni Range (DVOR) adjustment. back to normal.

Parameter Estimation and Preliminary Fault Diagnosis for Photovoltaic Modules Using a Three-Diode Model

Accurate estimation of photovoltaic (PV) power generation can ensure the stability of regional voltage control, provide a smooth PV output voltage and reduce the impact on power systems with many PV units. The internal parameters of solar cells that affect their PV power output may change over a period of operation and must be re-estimated to produce a power output close to the actual value. To accurately estimate the power output for PV modules, a three-diode model is used to simulate the PV power generation. The three-diode model is more accurate but more complex than single-diode and two-diode models. Different from the traditional methods, the 9 parameters of the three-diode model are transformed into 16 parameters to further provide more refined estimates. To accurately estimate the 16 parameters in the model, an optimization tool that combines enhanced swarm intelligence (ESI) algorithms and the dynamic crowing distance (DCD) index is used based on actual historical PV power data and the associated weather information. When the 16 parameters for a three-diode model are accurately estimated, the I–V (current-voltage) curves for different solar irradiances are plotted, and the possible failures of PV modules can be predicted at an early stage. The proposed method is verified using a 200 kWp PV power generation system. Three different diode models that are optimized using different ESI algorithms are compared for different weather conditions. The results affirm the reliability of the proposed ESI algorithms and the value of creating more refined estimation models with more parameters. Preliminary fault diagnosis results based on the differences between the actual and estimated I–V curves are provided to operators for early maintenance reference.

Cause Analysis on the Abnormal Failure of SiC Power Modules During the HV-H3TRB Tests

Cause Analysis on the Abnormal Failure of SiC Power Modules During the HV-H³TRB Tests

In Situ Monitoring Chip Failure in Multichip IGBT Modules Using Turn-On Delay Time Extracted From Auxiliary Emitter Voltage

In Situ Monitoring Chip Failure in Multichip IGBT Modules Using Turn-On Delay Time Extracted From Auxiliary Emitter Voltage

Fault-Tolerant Phototaxis of a Modular System Inspired by Gonium pectorale Using Phase-Based Control

In this study, we proposed a model for modular robots in which autonomous decentralized modules adaptively organize their behavior. The phototaxis of Gonium pectorale, a species of volvocine algae, was modeled as a modular system, and a fault-tolerant modular control method of phototaxis was proposed for it. The proposed method was based on the rotation phase of the colony and adaptively adjusted an internal response-related parameter to enhance the fault tolerance of the system. Compared to a constant parameter approach, the simulation results demonstrated a significant improvement in the phototaxis time for positive and negative phototaxis during module failures. This method contributes to achieving autonomous, decentralized, and purposeful mediation of the modules necessary for controlling modular robots.

Faulty cell prediction accuracy comparison of machine learning algorithms using temperature sensor placement optimization approach in immersion cooled Li-ion battery modules

Immersion cooling is a promising thermal management system for LiBs where the cells are submerged in a thermally conductive coolant, thus improving heat dissipation and prolonging battery life. The present study investigates an aligned arranged 4S4P immersion-cooled LiB module to develop a best-fit machine learning (ML) model that could predict the fault position in the module depending on the inputs from the temperature sensors that are optimized under different operating and fault conditions. The Pearson Correlation Coefficient (PCC) feature selection approach is used to optimize the sensors, while the data is generated from numerical simulations on a 4S4P immersion-cooled LiB module. The model validation through internal experimental trials is performed on a 2S2P battery module. The four ML classification algorithms, which include the K Nearest Neighbors, Random Forest (RF), Extreme Gradient, and Long Short Term Memory (LSTM), are trained on the optimized sensors data and are further tested internally and externally to assess their performance on unseen data within and outside the training range. A 5-fold cross-validation process is also implemented, and following a comprehensive comparison of the predictions based on the accuracies and model elapsed time, the best-fit model is identified. The results conclude that while the LSTM model slightly outweighs the other models with an accuracy of 98.18% for the specific external test cases, the RF model is chosen as the best-fit model with a prediction accuracy of 99.7% based on the error metrics and low training time for the internal testing. The outcomes of this present work contribute to the early identification of battery module failures, enhancing safety and reducing costs.

Experimental investigation of nonuniform PV soiling

Photovoltaic (PV) module soiling, i.e., the accumulation of dust on PV module surfaces, poses several challenges to PV system performance. Among these challenges, the nonuniform deposition of soiling across the module surface has received scarce attention. Soiling is directly associated with an overall performance loss, but can also potentially give rise to localised hotspots that can lead to long-term PV module failure. Therefore, addressing the issues arising from this nonuniformity is not only important for optimising energy production, but also for enhancing system reliability, and ensuring the long-term operation of relevant power generation systems. In this study, the impact of nonuniform soiling on PV performance is investigated experimentally by examining soil deposition on the upper surfaces of low-iron glass samples. Samples positioned at four different tilt angles were collected on a monthly basis over a one-year study period. Since the horizontal samples were found to represent the worst-case conditions, the most soiled sample at horizontal tilt was divided into four zones, each housing a single monocrystalline solar cell and examined further. The findings reveal that the soiled sample experiences an average transmittance deterioration of 13% relative to a clean sample, and a maximum (relative) spatial variation of 4% between the four zones. These optical losses affect the amount of sunlight received by the cells, resulting in a power deterioration of ∼6–7% per 5% drop in transmittance. The soiled sample experienced an average temperature rise of 2 °C, and an average power output (and efficiency) reduction of 30% relative to the clean sample, and a maximum (relative) spatial variation of 7% between the zones. The 30% average power loss measured in this nonuniform soiling case is more than double that which would be expected theoretically for a transmittance loss of 13% but from uniform soiling, so these results highlight the importance of addressing PV soiling for optimal PV performance, and of accounting for spatial soiling nonuniformity.

Voltage and Current Characteristics of Schottky Barrier Diodes and Rectifier Diodes Exposed to Standard Lightning Impulse Voltage

Lightning surges are one of the major reasons of bypass diode (BPD) failure in photovoltaic modules. In this study, standard lightning impulse voltages (SLIVs) were directly applied to Schottky barrier diodes (SKB diodes) and rectifier diodes (PNJ diodes) with different electrical specifications. The critical voltages Vc of SLIV at which the diodes were damaged and the temporal variations of diode current (iD) and voltage (vD) were measured. It was found the iD‐vD characteristics can be categorized into a total of eight patterns: four patterns for the forward SLIV application and the four for the reverse SLIV application, regardless of diode types. The measured results imply that the irreversible voltage dip that occurs before the termination of the reverse breakdown contributes significantly to diode damage in the both forward and reverse SLIV applications. SKB diodes exposed to the reverse SLIV are easily damaged at the lowest magnitude of SLIV among all combinations of diode types and SLIV directions. Once a diode has been damaged due to the first SLIV application, the second application of SLIV to the same diode causes remarkable change in the iD‐vD characteristic even if the magnitude of the second SLIV is smaller than Vc. © 2024 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Predictive Maintenance Framework for Fault Detection in Remote Terminal Units

The scheduled maintenance of industrial equipment is usually performed with a low frequency, as it usually leads to unpredicted downtime in business operations. Nevertheless, this confers a risk of failure in individual modules of the equipment, which may diminish its performance or even lead to its breakdown, rendering it non-operational. Lately, predictive maintenance methods have been considered for industrial systems, such as power generation stations, as a proactive measure for preventing failures. Such methods use data gathered from industrial equipment and Machine Learning (ML) algorithms to identify data patterns that indicate anomalies and may lead to potential failures. However, industrial equipment exhibits specific behavior and interactions that originate from its configuration from the manufacturer and the system that is installed, which constitutes a great challenge for the effectiveness of ML model maintenance and failure predictions. In this article, we propose a novel method for tackling this challenge based on the development of a digital twin for industrial equipment known as a Remote Terminal Unit (RTU). RTUs are used in electrical systems to provide the remote monitoring and control of critical equipment, such as power generators. The method is applied in an RTU that is connected to a real power generator within a Public Power Corporation (PPC) facility, where operational anomalies are forecasted based on measurements of its processing power, operating temperature, voltage, and storage memory.

Early degradation factors of solar 33 kV grid connected power plant, a comparative study

This paper identifies and analyses early degradation mechanisms observed in photovoltaic (PV) modules of power plants over 7 years of operation on the coast power grid in Mauritania. Performance degradation takes place due to several reasons such as material degradation following dust accumulation, high temperature, and humidity. Also, mismatch of electric power parameters such as increasing loads above projected values of the plant. Therefore, this paper analyses and studies the degradation in four phases. First, the visual inspection detects the degradation of materials and defects such as the presence of dust, cracks, browning (discoloration), and connection corrosion. The second phase proposes a mathematical model to calculate the early degradation rate (DR) of different components, such as short circuit current (Isc), open circuit voltage (VOC), the maximum yield power (Pmax), and the fill factor (FF) of the PV module. The third phase is a MATLAB modeling of the measured real-time data of the operating PV system to test Power versus voltage curves (with and without degradation) to examine the presence of failure of PV modules. Finally, compare the evolution of real-time production data for three measured years (2015, 2016, and 2017) with the simulation curves of this study.

Application of indoor and outdoor integrated collaborative positioning technology in power transportation detection

With the continuous acceleration of the construction of electric power Internet of Things, the structure and scale of electric power system is more massive, the complexity and danger coefficient of field operation is enhanced, and the risk of causing safety accidents is further increased. Therefore, based on wireless sensor network, collecting and transmitting information of personnel and site operation environment, establishing power operation tracking system is of great significance to improve the safety and efficiency of operation and inspection personnel. At present, most of the electric power operation and maintenance personnel are positioned by satellite or wireless WIFI, which has a large error or even cannot be positioned, so this paper proposes a 5G+Beidou fusion indoor-outdoor cooperative positioning technology for electric power operation and inspection service. The fusion model of Beidou carrier phase differential positioning and 5G cellular network positioning is established by using the improved Federal Kalman filter algorithm, which can avoid data pollution caused by Beidou receiver failure or 5G communication module failure in a complex environment, and avoid the inability to locate compared with the common Federal Kalman filter. phenomenon.

Control of PV power plants with quasi-Z-source cascaded H-bridge multilevel inverters under failure

At the present time, quasi-Z-source cascaded H-bridge multilevel inverters (qZS-CHBMLI) have gained attention in photovoltaic (PV) applications, due to their advantages over traditional multilevel inverters. They allow single-stage power conversion of a PV power plant by independently adjusting the DC voltage in each module; thus, each PV array operates at the maximum power. This advantage permits dispensing with a DC/DC boost converter and reduces the number of modules required. This paper develops a novel control strategy for a qZS-CHBMLI connected to a single-phase system that guarantees proper operation when a fault occurs in a quasi-impedance source inverter (qZSI). The control strategy is employed in a grid-connected qZS-CHBMLI with three modules, each one with a quasi-impedance network, a 4.8 kW PV array and a voltage source inverter (VSI), with H-bridge topology. The purpose of the control system is to deliver a suitable DC voltage at the input of the VSI and ensure the grid power requirements after a fault in a module. The proposed control system is evaluated through a 40 s simulation in MATLAB/Simulink® in two cases: A) analysis of the system behaviour when there is a variation in the operation limit equation; and B) evaluation of the control strategy under dissimilar operating conditions. In addition, an experimental setup based on an OPAL RT-4510 unit and a dSPACE MicroLabBox prototyping unit is employed to validate the results. The results confirmed the correct response of the applied strategy with the failure of a single module.

A Deep-Sea Environment Simulated Test System for Subsea Control Modules, Part A: Prototype and Test

This paper proposes a version of the deep-sea environment simulated test system for subsea control modules to solve the problem of incomplete testing systems for electro-hydraulic subsea control modules. Based on the subsea control module test requirements specified in APISTD17F, the test system in this paper is a highly integrated system, including a test hydraulic power unit, a control module test bench, a signal simulator, an electronic test unit, an umbilical simulator, a high-pressure chamber, and an incubator. Firstly, the design indicators of the test system were determined by analyzing the various functions of the subsea control module and its working environment. Secondly, the design scheme for the test system was proposed, and a detailed design was carried out. Finally, a hydro-electrical subsea control module for the Bohai Sea was fully tested with this system, with tests including the qualification test and the factory acceptance test. The test results show that all parts of the test system coordinated well and have achieved the design indicators, and the test system can simulate the working environment and complete a land test. The effectiveness and feasibility of the test system have been verified through the test. By adopting this system, the risk of subsea control module failure can be minimized, laying the foundations for future research and improvement of subsea control module testing equipment.

Repairing ribbon bus bar interruptions in photovoltaic modules using non-intrusive interruption location

Ribbon bus bar interruptions in photovoltaic modules represent approximately a 10 % of photovoltaic module failures. The purpose of the present work is to repair this failures using the simplest, fastest and cheapest techniques. Twin and single intercell interruptions are defined. The first one, twin intercell interruptions, cut off electrical current flow between two cells while the second one permits current flow between cells through just one ribbon bus bar at the cost of module efficiency reduction. We propose non-intrusive methods to find precise location of single and twin intercell interruptions. A simple technique for intercell interruption repairing is described. Three modules were repaired, multiplying its power production in two cases by 4, when comparing with its non-repaired power production. The third module did not produce any electricity before repairing, and after being repaired produced a power similar to its nominal value. The proposal of repairing can be put into practice in modestly equipped factories and laboratories, without using expensive and time consuming techniques.

A Review of Photovoltaic Module Failure and Degradation Mechanisms: Causes and Detection Techniques

With the global increase in the deployment of photovoltaic (PV) modules in recent years, the need to explore and understand their reported failure mechanisms has become crucial. Despite PV modules being considered reliable devices, failures and extreme degradations often occur. Some degradations and failures within the normal range may be minor and not cause significant harm. Others may initially be mild but can rapidly deteriorate, leading to catastrophic accidents, particularly in harsh environments. This paper conducts a state-of-the-art literature review to examine PV failures, their types, and their root causes based on the components of PV modules (from protective glass to junction box). It outlines the hazardous consequences arising from PV module failures and describes the potential damage they can bring to the PV system. The literature reveals that each component is susceptible to specific types of failure, with some components deteriorating on their own and others impacting additional PV components, leading to more severe failures. Finally, this review briefly summarises PV failure detection techniques, emphasising the significance of electrical characterisation techniques and underlining the importance of considering more electrical parameters. Most importantly, this review identifies the most prevalent degradation processes, laying the foundation for further investigation by the PV research community through modelling and experimental studies. This allows for early detection by comparing PV performance when failures or degradation occur to prevent serious progression. It is worth noting that most of the studies included in this review primarily focus on detailing failures and degradation observed in PV operations, which can be attributed to various factors, including the manufacturing process and other external influences. Hence, they provide explanations of these failure mechanisms and causes but do not extensively explore corrective actions or propose solutions based on either laboratory experiments or real-world experience. Although, within this field of study, there are corresponding studies that have designed experiments to suggest preventive measures and potential solutions, an in-depth review of those studies is beyond the scope of this paper. However, this paper, in turn, serves as a valuable resource for scholars by confining PV failures to critically evaluate available studies for preventative measures and corrective actions.

Analysis of the structure of an intellectual information system based on the concept of functional stability

The development of modern society requires intensive development of information technologies with a high degree of autonomy. This issue is especially acute for production enterprises that operate under the influence of destabilizing factors. In this work, research on the property of functional stability continues. Functional stability means the property of an information system to maintain its functioning, possibly with a decrease in quality, during the specified time under the influence of external and internal destabilizing factors. External and internal destabilizing factors mean failures, failures of system modules, mechanical damage, thermal effects, errors of service personnel. The main stages of ensuring functional stability are the detection of the module that failed during control, the diagnosis of the module that failed, and the restoration of the functioning of the intelligent information system. A feature of intelligent information systems is that they must function autonomously. With their help, it is possible to ensure an increase in the labor productivity of all production centers while reducing the number of people employed in production. The purpose of the work is to build a mathematical apparatus for quantitative assessment of the functional stability of the data exchange system of the intelligent information system. In addition, this article shows the advantages of using quantitative methods of assessing functional stability based on such indicators as the limit and margin of functional stability. On the basis of these assessments, recommendations can be made for building an intelligent information system. In addition, the evaluation data will help to more clearly formulate the requirements for the structure of the intelligent information system, which will be designed for uninterrupted data transmission.

Scheduling a Single-Arm Two-Cluster Tool With a Process Module Failure Subject to Wafer Residency Time Constraints

Multi-cluster tools are widely adopted in semiconductor manufacturing. When a process module (PM) at a step fails, a multi-cluster tool cannot complete the process recipe of work-in-process wafers and must be forced to enter a closedown process to be empty. To increase the throughput of a wafer fab, it is economically significant to shorten the failure-closedown process. However, due to the wafer residency time constraints, it is highly challenging to respond to a PM failure and find a corresponding optimal schedule. By assuming no parallel PM at a step, this work is the first to study this important issue for scheduling multi-cluster tools. We analyze the task sequences and synchronization conditions for robot activities to avoid deadlock in a shared buffer module. Upon these analyses, for process-dominant multi-cluster tools whose optimal steady-state schedule is known, algorithms are proposed to synthesize the proper sequences for robots in case of PM failures, then, a nonlinear program model is proposed to find an optimal schedule for the corresponding closedown process or decide no feasible solutions. The proposed model can uniformly deal with different scenarios of PM failures. Examples are given to illustrate the application of the proposed method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In a wafer fab, there are hundreds, even thousands, of cluster tools. It is common that a failure of a processing module happens in a cluster tool. How to intelligently respond to such a random failure in a multi-cluster tool is an important issue in real-world production. This paper studies the scheduling problem of a multi-cluster tool in case of a failure at a PM. For a multi-cluster tool in case of a failure module, the proposed method can significantly reduce the loss of work-in-process wafers and shorten the closedown process.

Design and test of rack-integrated cavity combiner for China initiative accelerator driven system project.

The next-generation 650MHz solid state power amplifier designed by the Institute of Modern Physics will utilize 24 modules with an output power of 60 kW. The outputs of each of the 12 modules will be combined using a 12-in-1 rectangular cavity combiner integrated into the rack. This cavity combiner, requiring only a single stage to combine power, is characterized by a minimal power loss and a high combining efficiency. The input couplers of the combiner are adjustable to change the number of combination channels. In the event of one amplifier module failure, the corresponding port can be adjusted to decouple, transforming the combiner to an (N-1)-channel combiner with a combining efficiency decay of 0.2%. The prototype of the combiner has been fabricated and tested with a small signal. The combining efficiency is 98.5%. In this paper, we will validate the feasibility of the combiner from the design, simulation, and experiment.

Analysis of Blocking Capability Failure Mechanism in IGBT Module Under High Salt Spray Environment

High salt spray environment is a threat to the long-term stability and the robustness of an insulated gate bipolar transistor (IGBT) module. Failure mechanisms of IGBTs have been discussed in normal and high humidity environment, which in high salt spray environment is unclear and seldom reported. In this paper, experiments in high salt spray environment are conducted on wire-bonding IGBT modules to reveal failure mechanism. Different degradations of the blocking capability are observed for the same packaged IGBTs in the salt spray environment. Based on experiment results, degradation substances in the internal package are analyzed by means of scanning electron microscope (SEM) and X-ray diffraction (XRD) to reveal the key composition affecting the blocking capability of IGBT switches. Finally, a failure model is used to reveal the mechanism that the insulation strength of the terminal area in the chip edge is reduced by substances, resulting in the blocking failure of IGBT switches. The analysis of IGBT module failure mechanism is of great significance to reliability evaluation and optimal design for package structures of power modules applied in harsh environments.