Investigation of the trade‐off between switching losses and EMI generation in Gaussian S‐shaping for high‐power IGBT switching transients by active voltage control

Yang, Xin; Li, Zhiqiang; Wen, Yanhui; Huang, Hao; Palmer, P.R.

doi:10.1049/iet-pel.2015.1035

Cited by 21 publications

(11 citation statements)

References 24 publications

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“…The input of the output layer is given by Equation (10). As shown in equations (11), the identity function was selected as an activation function of neurons in the output layer.…”

Section: B Test Data Preprocessing and Normalizationmentioning

confidence: 99%

Prediction Method of Driving Strategy of High-Power IGBT Module Based on MEA-BP Neural Network

et al. 2020

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An insulated gate bipolar transistor (IGBT) driver is crucial for improving the reliability of a power electronics system. This paper proposes a method for predicting the optimal driving strategy of high-power IGBT module based on backpropagation neural network optimized by the mind evolutionary algorithm in order to solve the problem of compromise among switching loss, switching time and overshoot and achieve a good driving effect. The three regions of switching transitions are analyzed based on the switching characteristics of the IGBT module. Neural networks are established to predict turn-on and turn-off driving strategies for variable gate resistance active gate driver of the IGBT module. The mind evolutionary algorithm is used to optimize the weights and biases of the neural networks so that the optimal weights and biases can be obtained. In order to verify the effectiveness of the driving strategy prediction method proposed in this paper, experiments are carried out for 4500V/900A the IGBT module. Compared to the conventional gate driver, the predicted driving strategies reduce the turn-on energy loss, turn-on time, overcurrent, comprehensive evaluation method, turn-on delay time and tail voltage duration by 59.31%, 46.38%, 36.99%, 65.65%, 1.9 µs, 2.9 µs, respectively. It was also found that the Planar-IGBT turn-off process was rarely affected by the gate resistance. The proposed method in this paper can be used not only for the guidance of the driving strategy determination of high-power the IGBT module driver, but also for the driver circuit improvement in the design process. INDEX TERMS IGBT module, active gate driver, MEA-BP neural network, driving strategy optimization, data-driven method.

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“…The input of the output layer is given by Equation (10). As shown in equations (11), the identity function was selected as an activation function of neurons in the output layer.…”

Section: B Test Data Preprocessing and Normalizationmentioning

confidence: 99%

Prediction Method of Driving Strategy of High-Power IGBT Module Based on MEA-BP Neural Network

et al. 2020

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“…The device simulator such as Atlas cannot implement closed-loop control simulations such as the AVC technique. To exam the controlled series-connected IGBTs' switching under temporary clamp, a clamped inductive load test is built in Matlab/Simulink [20][21].…”

Section: Circuit and Device Modelingmentioning

confidence: 99%

Physical Investigation Into Effective Voltage Balancing by Temporary Clamp Technique for the Series Connection of IGBTs

Yang

Zhang

He³

et al. 2018

IEEE Trans. Power Electron.

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The series connection of IGBTs is essential for high voltage applications where fast switching performances need to be maintained. However, unbalanced voltage sharing is a major resistance to the converter application of this structure. There are a number of causes leading to voltage unbalance, such as different signal delays, parasitic parameters, and tail currents and so on. A temporary clamp scheme performed by Active Voltage Control (AVC) has been proven to be effective in solving the unbalanced voltage-sharing issue. However, the basic physics has not been investigated. In this paper, the physical principle of voltage unbalance within IGBTs series operation is discussed. The carrier storage region differences are concluded to be the intrinsic cause of unbalanced voltage sharing. By using an accurate Fourier-series-based IGBT simulation model with appropriate assumptions, a physical explanation for temporary clamp is provided in detail. At the end of the tail current period when the excess carrier concentration becomes close to the intrinsic doping density, the temporary clamp is able to achieve satisfactory equal voltage sharing.

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“…EMI filtering and shielding volume and cost are challenging to predict without subjecting the design to full EMC qualification, and hence this element has been neglected in this comparison. The impact of EMI qualification on the cost of the SiC 2-level converter seems likely to be significant [33], and may well lead to an increased cost in the SiC converter compared with the Si MMC converter. However, even with EMC qualification the SiC 2-level converter may remain physically smaller than the 7-level Si MMC converter, although the difference will become less significant, however this disadvantage must be weighed against the higher efficiency offered by the 7-level Si MMC converter.…”

Section: )mentioning

confidence: 99%

LV Converters: Improving Efficiency and EMI Using Si MOSFET MMC and Experimentally Exploring Slowed Switching

Roscoe

Holliday

McNeill

et al. 2018

IEEE J. Emerg. Sel. Topics Power Electron.

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Abstract-Widespread adoption of electric vehicles will require AC power distribution systems to accommodate high penetrations of power electronic loads, placing increasing demands on the power quality of gridconnected converters. Recent developments in devices and circuit topologies have potential to improve the intrinsic power quality of these grid interface inverters, reducing the need for passive filters and associated reactive power consumption. Wide bandgap devices, such as SiC, have recently gained much attention due to their low switching losses facilitating raised PWM frequencies. However the high cost of SiC together with electromagnetic interference (EMI) resulting from very rapid switching transitions necessary to realize low switching losses cause concern. Previous research in Si MOSFET modular multilevel converters (MMC) suggests a high efficiency alternative with potential for lower EMI. Si MOSFET MMC benefits are enhanced with parallel-connected devices and slowed switching, made possible by low effective switching frequency. This paper uses experimental results to explore the impact of parallel connection and slowed switching on Si MOSFET MMC losses, and presents improved Si MOSFET switching loss models to resolve inaccuracies observed with conventional Si MOSFET models. EMI is then compared between SiC and Si MMC using carefully controlled relative measurements of radiated EMI.

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Investigation of the trade‐off between switching losses and EMI generation in Gaussian S‐shaping for high‐power IGBT switching transients by active voltage control

Cited by 21 publications

References 24 publications

Prediction Method of Driving Strategy of High-Power IGBT Module Based on MEA-BP Neural Network

Prediction Method of Driving Strategy of High-Power IGBT Module Based on MEA-BP Neural Network

Physical Investigation Into Effective Voltage Balancing by Temporary Clamp Technique for the Series Connection of IGBTs

LV Converters: Improving Efficiency and EMI Using Si MOSFET MMC and Experimentally Exploring Slowed Switching

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