Preliminary design review analysis of a 250-volt-ampere static inverter
Component reliability analysis for 250 volt-ampere static inverter
SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Component reliability analysis for 250 volt-ampere static inverter
The high-reliability operation of three-level inverters is crucial to prevent equipment damage, process downtime, and economic losses. This article investigates a three-level neutral-point-clamped inverter under all possible combinations of open-circuit and short-circuit faults and proposes a new postfault operation method without adding extra hardware. This method provides comprehensive solution for operations after single and multiple-device failures, increasing the inverter reliability by 24%. This article classified postfault modulations and uncovered previously unknown fault scenarios that can be addressed using the proposed control method. A new postfault modulation based on space vector modulation with virtual vectors is proposed. The feasibility of the proposed control method is verified by simulation and an experiment for one fault scenario in a three-level neutral-point-clamped inverter with a 3.73 kW motor load. Furthermore, this article contributes to improving the reliability of three-level inverters.
Timing channel circuit reliability in static inverter
Physics-of-Failure (PoF) based reliability assessment for photovoltaic (PV) inverters requires long-duration electrical and electrothermal stress histories, yet generating such stress histories with high-fidelity switching models over year long mission profiles is computationally prohibitive. Conventional methods either sacrifice modeling fidelity for speed or require runtimes that are impractical for design iteration and uncertainty studies. To address this bottleneck, this paper presents a High-Performance Computing (HPC) based simulation frame work for faster-than-real-time reliability-oriented simulation. The proposed framework integrates the Average-to-Switching (A2S) method with parallel computing techniques to accelerate switching-level waveform reconstruction. We further introduce optimization strategies, including cluster merging and sensitivity based mission profile screening, to reduce the computational burden. Evaluated using real-world mission profile inputs and a MATLAB/Simulink switching-model reference, the framework reduces the simulation time for a one-year mission from an intractable multi-year duration to approximately 7.3 minutes while maintaining low waveform error. This acceleration provides a practical reliability-oriented simulation engine that can be coupled with component-specific aging models for subsequent PV inverter PoF assessment.
Generally, large electrolytic capacitors (E-caps) are required to decouple the double-line frequency power fluctuation inherent in all single-phase dc-ac or ac-dc converters. These E-caps pose the weak link in the photovoltaic (PV) inverter because they have poor reliability as a result of short life expectancy and higher equivalent series resistance (ESR) which leads to lower system efficiency. In this paper, multiport smart dual-inverter modules are proposed for residential PV inverter systems with balanced outputs to eliminate the requirement of large decoupling capacitors, thus leading to more reliable and highly efficient inverter modules. The balanced dual outputs are controlled in phase quadrature such that the double frequency current is completely eliminated. One phase supports the standalone residential loads, and the other phase interfaces with the grid, which is synchronized to the utility grid. Also, the proposed modular configuration is scalable to accommodate higher power rating by stacking and paralleling multiple modules. Simulation results for the dual-inverter modules rated for 1 kW each are presented to validate the proposed concept. Experimental results from a controller hardware-in-the-loop (CHIL) platform also verify its feasibility.
While PV panel reliability continues to increase, PV inverters become the limiting factor for PV system reliability. Consequently, it is critical to have a generic tool from a third party for PV inverter reliability assessment to help 1) utilities/PV farm operators schedule maintenance in advance, and 2) inverter developers improve the next-generation design. However, these two things cannot be accomplished without first understanding the reasons behind inverter failure. Following this idea, as the first step, it is essential to identify and investigate the most failure-prone components within a PV inverter system. After all, any system is only as reliable as the components that are contained within it. This motivates the failure mode and effects analysis (FMEA) work presented for this workshop. The FMEA is conducted as follows: first, the overview of the methodology on the development of the FMEA is presented; then, based on a top-down approach starting from the PV inverter system, critical inverter components with high failure rates are identified and summarized; afterward, a thorough FMEA study at a component-level is performed and its results, including failure modes, failure mechanisms, and critical stressors, are tabulated; finally, according to three rankings (chance of occurrence, severity of occurrence, and ease of detection prior to failure) for each failure mechanism provided by the FMEA, risk priority numbers are calculated and the failure mechanisms along with the critical stressors are ranked in terms of their potentially detrimental effect on the PV inverter.
The reliability of photovoltaic (PV) inverters is critical for long-term solar system performance, with cooling fan failures frequently leading to costly downtime. While much research exists on general cooling fan reliability, little attention has been given to fans operating within PV inverters and their unique environmental challenges. Here, this article proposes a comprehensive methodology to address this gap. First, a failure mode and effects analysis is performed on fans to identify the key failure mechanisms in PV applications, their corresponding stressors, and the models necessary for lifetime prediction. Second, an accelerated life test is designed and conducted to collect valuable experimental data for PV inverter fans in a reasonable amount of time. Third, a mathematical conversion of dynamic mission profiles into effective constant stress levels is derived. Fourth, case studies are given, showcasing lifetime estimates that account for geographic variations in mission profile data. The results demonstrate that this integrated approach leads to an accurate reliability assessment for PV inverter cooling fans.
Design stage reliability analysis application to static inverter
With this final report, the combined team of the University of Arkansas (UA), University of Illinois, Urbana-Champaign (UIUC), Wolfspeed, Caterpillar, and Ampaire have successfully met all of their project objectives. Noteworthy for the heavy equipment portion of the project with Caterpillar is that the team made its project milestones two years into the project by designing a power dense motor drive for a permanent magnet synchronous machine. Upon finding out that Caterpillar had pivoted to switched-reluctance machines (SRMs), the team subsequently redesigned and implemented the SRM drive with a coolant temperature of 105°C! The other major task that the UA, UIUC, and Wolfspeed teams took on was the design of a PMSM drive for a hybrid aircraft that was flown on Feb. 20, 2023 by Ampaire after extensive testing and evaluation. While there were also technical objectives in thermal management, integrated gate drivers, reliability studies, and high temperature capacitors with integrated bussing, each of these have been fully reported on in quarterly reports. In brief, advances in thermal management and high temperature capacitors were utilized in order to achieve a 105°C motor drive. The integrated gate driver work resulted in a higher density drive with no loss of efficiency. Most of the last year, during a no-cost extension, was spent waiting for the Ampaire motor drive to be tested (outside of our project). Many months passed with the device just sitting in California while the company dealt with battery-related issues. This delayed the integration and testing activities until Fall 2022. Once those began, then the process took about 4-5 months to complete culminating in the test flight in Feb. 2023. By providing technical advances and integration into final platforms, the barrier to economic impact has been lowered. This project benefits the public by overcoming key technical barriers to electrified and hybrid electric heavy equipment and aircraft. This, in turn, leads to lower greenhouse gas emissions and a cleaner environment. This final report summarizes the integrated gate driver work and the Ampaire hybrid electric aircraft integration and test flight efforts. All other information has been previously reported in quarterly reports. A summary of the motor drives created during this project is provided along with a listing of publications.
This article introduces a data-driven approach to assessing failure mechanisms and reliability degradation in outdoor photovoltaic (PV) string inverters. The manufacturer's stated PV inverter lifetime can vary due to the impact of operating site conditions. To address limitations in degradation estimation through accelerated testing, condition monitoring, or degradation modeling, we propose a machine learning (ML) oriented approach. Utilizing data from a 1.4 MW PV power plant operational since 2016, with 46 string PV inverters tied to the grid, we employ the unsupervised one-class support vector machine ML technique to analyze inverter and sensor data, capable of classifying humidity cycling and temperature fluctuations as dominant failure mechanisms. Utilizing the anomaly alert relationship and alert details specific to the inverter, the level of PV inverter output is considered as its availability or available reliability. Subsequently, a continuous Markov model is applied to six-month alert data, revealing an average stated reliability of 20% after 20 years of continuous operation. These results support recommendations for time-bound preventive measures to enhance PV inverter reliability under diverse outdoor conditions. Furthermore, the approach provides a nondestructive, top–down, and generalized method for analyzing any commercial PV inverter exposed to outdoor conditions, contingent on the availability of relevant data.
Double-side cooled power modules are being developed for next-generation traction inverters due to their better heat extraction, lower profile, and lower parasitic inductances. However, due to their rigid structure, they cause reliability concerns arising from high thermo-mechanical stresses at the interconnection joints in the module. In this work, a materials-based approach using rigid encapsulants is presented for reducing thermo-mechanical fatigue. Finite-element thermo- mechanical simulations were performed to examine the effects of the elastic modulus and coefficient of thermal expansion of epoxy- based encapsulants on the bond deformation inside a double-side cooled power module. It was found that a rigid encapsulant with a high modulus of 6.0 GPa or above and a coefficient of thermal expansion around 20 ppm/oC would improve the thermo- mechanical reliability of double-side cooled power modules by decreasing the permanent bond deformation inside the modules by 50-60%.
Uncertainty quantification plays a pivotal role in improving the accuracy and reliability of inverter operation within modern power systems that are increasingly dominated by inverter-based resources (IBRs). IBRs, especially those operating under grid forming (GFM) control, rely heavily on a complex set of control parameters and system measurements to maintain voltage, frequency, and power balance. Traditional deterministic modeling approaches often fail to capture these parameter deviations, potentially resulting in suboptimal control actions, reduced system stability, or even instability under high penetration of IBRs. In this paper, we demonstrate the application of model calibration and uncertainty quantification (UQ) principles to an integrated transmission and distribution (T&D) model involving a GFM converter and provide a framework for prioritizing control improvements, guiding robust design, and informing adaptive strategies that can accommodate real-time variability in system conditions. The proposed approach could be valuable in enhancing the robustness of current and future power systems under increased IBR penetrations.
Breadboard models and interface requirements for optimum performance and reliability of inverter motor system
To achieve useful, fair, and cost-effective design qualification and type approval testing for PV inverters, two procedures were developed and demonstrated to evaluate the bus link capacitors and power transistor—and where applicable, its module—for long-term reliability. We evaluate the inverter under simulated use conditions with heat run tests to find the highest operating temperatures reached by these components. The procedures are demonstrated in this study with a 4-kVA class string inverter. The maximum temperature of the DC bus link capacitors was determined to be 76.4°C when the ambient temperature was at the inverter's maximum rated temperature of 60°C with derating occurring. On the other hand, the power transistor module's maximum temperature using the heat sink temperature as the index, 92.6°C, occurred in an ambient of 40.8°C when derating was not occurring. The conditions found for upper temperatures exhibited by these components are, respectively, proposed for implementation in the dry heat and thermal cycling tests in the IEC 62093 “Power conversion equipment for photovoltaic systems – Design qualification testing” international standard draft so that the levels applied in the tests are in proportion to those experienced in the field. Finally as a result, fairer evaluation of inverter reliability is realized.
Here, this study presents a novel approach for the precise monitoring and prognosis of photovoltaic (PV) inverter status, which is crucial for the proactive maintenance of PV systems. It addresses the gaps in traditional model-based methods, which tend to neglect the overall reliability of inverters, and the limitations of data-driven approaches that largely depend on simulated data. This research presents a robust solution applicable to real-world scenarios. The proposed data-driven model for PV inverter failure prognosis employs actual inverter measurements, integrating various operational and weather-related factors based on domain knowledge. This approach effectively represents inverter stressors and operational status. Utilizing an Enhanced Siamese Convolutional Neural Network (ESCNN), the model merges operational data with domain knowledge features, redefining the prognosis challenge as a classification task. Furthermore, the paper discusses an ESCNN-based real-time inverter failure monitoring method developed on the well-trained model. The proposed models are rigorously trained and tested with real inverter data and a novel filtering method is included to address accidental failures in practical scenarios. The results validate the model's efficacy, and the directions for future research are also outlined.
As many island power systems seek to integrate high levels of renewable energy, they face new challenges on top of the existing difficulties of operating an isolated grid. With their drastically declining cost, variable renewables, such as wind and photovoltaics (PVs), are increasingly being integrated into island grids to reduce the use of imported fuels. These deployments of renewable energy are dominated by PV and wind generators, which bring unique challenges of their own.
The project aimed to address the challenges posed by the rapid growth of inverter-based resources (IBR) such as solar, wind, and battery storage, which have fundamentally changed fault behavior, system strength, and protection performance in bulk power systems. Traditional protection schemes, designed for synchronous generator-dominated grids, are inadequate under high IBR penetration. Overall, the project materially advances protection modeling and simulation capabilities needed to maintain reliable grid protection under high IBR penetration. The results build utility confidence in operating power systems safely and reliably across a wide range of generation mixes, supporting grid modernization goals.
This paper presents a small-signal stability analysis of grid-forming (GFM) inverters under current-limiting conditions. It examines how adjustments in virtual impedance angles, implemented through advanced current-limiting and frequency stabilization techniques, influence small-signal stability. This paper studies a GFM inverter control integrating a fictitious power technique stabilizing primary control by adding a virtual power term and a hybrid current limiter integrating virtual impedance in the anti-wind-up feedback with current reference saturation limiting. A small-signal model is developed to assess the impact of virtual impedance angles on GFM inverter dynamics during grid disturbances, such as voltage drops. The findings indicate that although increasing the virtual impedance angle (to make it more inductive) enhances large-signal stability and voltage support during faults, it can induce oscillations and lead to instability if the angle exceeds certain thresholds. Based on the small-signal models, this paper provides design considerations for the current-limiter impedances to ensure reliable GFM inverter behavior under grid disturbances while maintaining small-signal stability.