In Situ Insulated Gate Bipolar Transistor Junction Temperature Estimation Method via a Bond Wire Degradation Independent Parameter Turn-OFF V
 ce Overshoot

Yang, Yanyong; Zhang, Pinjia

doi:10.1109/tie.2020.3022526

Cited by 35 publications

(5 citation statements)

References 33 publications

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“…The result shows that this method is superior to a single SVM model. However, the original MPA is still prone to fall into local optimization and low global search accuracy [34]. Jia et al [35] proposed that introduce the coevolutionary culture mechanism into the MPA to improve the performance of the original algorithm and have a higher probability of avoiding local optimization.…”

Section: Literature Reviewmentioning

confidence: 99%

Enhanced marine predators algorithm optimized support vector machine for IGBT switching power loss estimation

Liu,

Li,

Liu

2023

Meas. Sci. Technol.

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As the use of renewable energy generation continues to grow, improving power conversion efficiency has become an urgent task. This study aims to propose a high-precision power module loss estimation method, with a focus on predicting the switching losses of Insulated Gate Bipolar Transistor (IGBT) modules, which is crucial for the reliability assessment of IGBT modules. The main objective of this study is to establish a high-precision predictive model for IGBT module switching losses to enhance the reliability and efficiency of these devices. Firstly, a dynamic characteristic test platform was established to acquire relevant data for in-depth analysis of IGBT behavior. Secondly, given the excellent performance of Support Vector Machine (SVM) in handling both strong and small-sized datasets, SVM was chosen as the foundational model for high-precision switching loss estimation. Subsequently, an Enhanced Marine Predatory Algorithm (EMPA), known for its superior convergence precision and speed, was introduced to optimize the random parameters of SVM. Finally, a method based on the Enhanced Marine Predatory Algorithm Optimized Support Vector Machine (EMPA-SVM) was constructed for predicting IGBT switching power losses. The proposed approach was validated using dynamic characteristic test data. And it indicated that the predictive model achieved the value of R2 exceeding 99.8% for switching losses. Additionally, the MAE and RMSE metrics of EMPA-SVM model outperformed other models. Therefore, the research results unambiguously demonstrate the significant benefits of accurately predicting IGBT switching losses in enhancing device performance.

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Section: Literature Reviewmentioning

confidence: 99%

Enhanced marine predators algorithm optimized support vector machine for IGBT switching power loss estimation

Liu,

Li,

Liu

2023

Meas. Sci. Technol.

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“…These are caused by the thermo-mechanical stress induced by the temperature gradients between the components due to the different materials and power losses [34]. In this context, research is focused on online junction temperature estimation methods, so to optimize the power module operation to enhance its reliability [58].…”

Section: B Semiconductor Lifetimementioning

confidence: 99%

Lifetime Estimation of Grid-Connected Battery Storage and Power Electronics Inverter Providing Primary Frequency Regulation

Stecca

Soeiro

Ramírez-Elizondo

et al. 2021

IEEE Open J. Ind. Electron. Soc.

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Battery Energy Storage Systems (BESSs) are a new asset for Primary Frequency Regulation (PFR), an ancillary service for improving the grid stability. The system operators determine the implementation and remuneration of PFR. However, assessing the revenue stream is not enough to define the business case, as also the components' lifetime has to be estimated. Previous studies of lifetime estimation for BESSs performing PFR considered only the electrochemical storage, disregarding the power electronics (PE). Nonetheless, researchers have shown the importance of estimating PE wear due to the operation when applied in renewable energy generation and microgrids. This paper presents a lifetime analysis of BESSs providing PFR considering IGBT modules, electrolytic capacitors and electrochemical storage degradation. The lifetime information is used to estimate BESS's Net-Present-Value (NPV), evaluating the benefits of deploying PE-based BESS in the European grid. A comparison between different countries, Germany, the Netherlands, and the UK, is performed, considering the PFR implementation and remuneration differences. The analysis shows that the BESS management strategy can extend its lifetime and that the component that exhibits the shortest lifetime is the electrochemical storage. The PE components are subject to low wear due to the low power utilization and, therefore, small thermal swings while performing PFR. In conclusion, the provision of PFR by means of BESS has been found to be profitable in all three countries. However, in the Netherlands, the potential NPV has been estimated to be 47% and 76% higher than in Germany and the UK, respectively.

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“…For example, the heat flux density of GaN HEMT is as high as 300 W/cm 2 , about three times that of Si-based IGBTs, as shown in Figure 1 [6]. Since a high heat flux density causes the devices' junction temperature to increase, the junction temperature as a key reliability parameter for Si-based devices is also valuable for the reliability of GaN HEMT [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Steady-State Temperature-Sensitive Electrical Parameters’ Characteristics of GaN HEMT Power Devices

Wang,

Zhu,

Zhao

et al. 2024

Electronics

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Gallium nitride high-electron-mobility transistor (GaN HEMT) power devices are favored in various scenarios due to their high-power density and efficiency. However, with the significant increase in the heat flux density, the junction temperature of GaN HEMT has become a crucial factor in device reliability. Since the junction temperature monitoring technology for GaN HEMT based on temperature-sensitive electrical parameters (TSEPs) is still in the exploratory stage, the TSEPs’ characteristics of GaN HEMT have not been definitively established. In this paper, for the common steady-state TSEPs of GaN HEMT, the variation rules of the saturation voltage with low current injection, threshold voltage, and body-like diode voltage drop with temperature are investigated. The influences on the three TSEPs’ characteristics are considered, and their stability is discussed. Through experimental comparison, it is found that the saturation voltage with low current injection retains favorable temperature-sensitive characteristics, which has potential application value in junction temperature measurement. However, the threshold voltage as a TSEP for certain GaN HEMT is not ideal in terms of linearity and stability.

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In Situ Insulated Gate Bipolar Transistor Junction Temperature Estimation Method via a Bond Wire Degradation Independent Parameter Turn-OFF V _ce Overshoot

Cited by 35 publications

References 33 publications

Enhanced marine predators algorithm optimized support vector machine for IGBT switching power loss estimation

Enhanced marine predators algorithm optimized support vector machine for IGBT switching power loss estimation

Lifetime Estimation of Grid-Connected Battery Storage and Power Electronics Inverter Providing Primary Frequency Regulation

Steady-State Temperature-Sensitive Electrical Parameters’ Characteristics of GaN HEMT Power Devices

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In Situ Insulated Gate Bipolar Transistor Junction Temperature Estimation Method via a Bond Wire Degradation Independent Parameter Turn-OFF V ce Overshoot

Cited by 35 publications

References 33 publications

Enhanced marine predators algorithm optimized support vector machine for IGBT switching power loss estimation

Enhanced marine predators algorithm optimized support vector machine for IGBT switching power loss estimation

Lifetime Estimation of Grid-Connected Battery Storage and Power Electronics Inverter Providing Primary Frequency Regulation

Steady-State Temperature-Sensitive Electrical Parameters’ Characteristics of GaN HEMT Power Devices

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Product

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In Situ Insulated Gate Bipolar Transistor Junction Temperature Estimation Method via a Bond Wire Degradation Independent Parameter Turn-OFF V _ce Overshoot