Driver Optimization Method Based on GeneticAlgorithm for IGBT

Chengyang Lin; Mingcheng Ma; Tianlin Sun; Dianguo Xu

doi:10.30420/566131013

Driver Optimization Method Based on GeneticAlgorithm for IGBT

Chengyang Lin
, Mingcheng Ma
, Tianlin Sun
, Dianguo Xu^*

^*Corresponding author for this work

School of Electrical Engineering and Automation

Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This article proposes a technique called Genetic Algorithm Gate Driver (GAGD) that utilizes genetic algorithms to optimize the gate driving characteristics. To achieve this, a gate characteristic testing platform with high bandwidth, high voltage swing, and high output speed is designed. This platform uses genetic algorithms to generate gate voltage waveforms, drive insulated gate bipolar transistors (IGBTs), and optimize the output voltage waveform. The gate driving method of the IGBT is iteratively optimized under the constraints of turn-on losses and turn-on stress. Finally, experimental comparisons are conducted with traditional gate driving techniques during the turn-on process. The experimental results demonstrate that the optimized drive mode using genetic algorithms exhibits good transient characteristics.

Original language	English
Title of host publication	PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings
Publisher	VDE Verlag GmbH
Pages	78-83
Number of pages	6
ISBN (Electronic)	9783800761326
DOIs	https://doi.org/10.30420/566131013
State	Published - 2023
Event	2023 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Asia 2023 - Shanghai, China Duration: 29 Aug 2023 → 31 Aug 2023

Publication series

Name	PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings

Conference

Conference	2023 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Asia 2023
Country/Territory	China
City	Shanghai
Period	29/08/23 → 31/08/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Access to Document

10.30420/566131013

Cite this

Lin, C., Ma, M., Sun, T., & Xu, D. (2023). Driver Optimization Method Based on GeneticAlgorithm for IGBT. In PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings (pp. 78-83). (PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings). VDE Verlag GmbH. https://doi.org/10.30420/566131013

Lin, Chengyang ; Ma, Mingcheng ; Sun, Tianlin et al. / Driver Optimization Method Based on GeneticAlgorithm for IGBT. PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings. VDE Verlag GmbH, 2023. pp. 78-83 (PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings).

@inproceedings{23ec4958580240bcb2b39148a4899e0f,

title = "Driver Optimization Method Based on GeneticAlgorithm for IGBT",

abstract = "This article proposes a technique called Genetic Algorithm Gate Driver (GAGD) that utilizes genetic algorithms to optimize the gate driving characteristics. To achieve this, a gate characteristic testing platform with high bandwidth, high voltage swing, and high output speed is designed. This platform uses genetic algorithms to generate gate voltage waveforms, drive insulated gate bipolar transistors (IGBTs), and optimize the output voltage waveform. The gate driving method of the IGBT is iteratively optimized under the constraints of turn-on losses and turn-on stress. Finally, experimental comparisons are conducted with traditional gate driving techniques during the turn-on process. The experimental results demonstrate that the optimized drive mode using genetic algorithms exhibits good transient characteristics.",

author = "Chengyang Lin and Mingcheng Ma and Tianlin Sun and Dianguo Xu",

note = "Publisher Copyright: {\textcopyright} VDE VERLAG GMBH - Berlin - Offenbach.; 2023 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Asia 2023 ; Conference date: 29-08-2023 Through 31-08-2023",

year = "2023",

doi = "10.30420/566131013",

language = "英语",

series = "PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings",

publisher = "VDE Verlag GmbH",

pages = "78--83",

booktitle = "PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings",

}

Lin, C, Ma, M, Sun, T & Xu, D 2023, Driver Optimization Method Based on GeneticAlgorithm for IGBT. in PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings. PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings, VDE Verlag GmbH, pp. 78-83, 2023 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Asia 2023, Shanghai, China, 29/08/23. https://doi.org/10.30420/566131013

Driver Optimization Method Based on GeneticAlgorithm for IGBT. / Lin, Chengyang; Ma, Mingcheng; Sun, Tianlin et al.
PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings. VDE Verlag GmbH, 2023. p. 78-83 (PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Driver Optimization Method Based on GeneticAlgorithm for IGBT

AU - Lin, Chengyang

AU - Ma, Mingcheng

AU - Sun, Tianlin

AU - Xu, Dianguo

PY - 2023

Y1 - 2023

N2 - This article proposes a technique called Genetic Algorithm Gate Driver (GAGD) that utilizes genetic algorithms to optimize the gate driving characteristics. To achieve this, a gate characteristic testing platform with high bandwidth, high voltage swing, and high output speed is designed. This platform uses genetic algorithms to generate gate voltage waveforms, drive insulated gate bipolar transistors (IGBTs), and optimize the output voltage waveform. The gate driving method of the IGBT is iteratively optimized under the constraints of turn-on losses and turn-on stress. Finally, experimental comparisons are conducted with traditional gate driving techniques during the turn-on process. The experimental results demonstrate that the optimized drive mode using genetic algorithms exhibits good transient characteristics.

AB - This article proposes a technique called Genetic Algorithm Gate Driver (GAGD) that utilizes genetic algorithms to optimize the gate driving characteristics. To achieve this, a gate characteristic testing platform with high bandwidth, high voltage swing, and high output speed is designed. This platform uses genetic algorithms to generate gate voltage waveforms, drive insulated gate bipolar transistors (IGBTs), and optimize the output voltage waveform. The gate driving method of the IGBT is iteratively optimized under the constraints of turn-on losses and turn-on stress. Finally, experimental comparisons are conducted with traditional gate driving techniques during the turn-on process. The experimental results demonstrate that the optimized drive mode using genetic algorithms exhibits good transient characteristics.

UR - https://www.scopus.com/pages/publications/85183465597

U2 - 10.30420/566131013

DO - 10.30420/566131013

M3 - 会议稿件

AN - SCOPUS:85183465597

T3 - PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings

SP - 78

EP - 83

BT - PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings

PB - VDE Verlag GmbH

T2 - 2023 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Asia 2023

Y2 - 29 August 2023 through 31 August 2023

ER -

Lin C, Ma M, Sun T, Xu D. Driver Optimization Method Based on GeneticAlgorithm for IGBT. In PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings. VDE Verlag GmbH. 2023. p. 78-83. (PCIM Asia 2023 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Conference Proceedings). doi: 10.30420/566131013

Driver Optimization Method Based on GeneticAlgorithm for IGBT

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