Predicting the Temperature of the Electrolytic Capacitor Based on Neural Network Algorithm-Reference-Cited by-同舟云学术

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Predicting the Temperature of the Electrolytic Capacitor Based on Neural Network Algorithm

Published:2023-12 Issue:6 Volume:11 Page:6068-6078
ISSN:2168-6777
Container-title:IEEE Journal of Emerging and Selected Topics in Power Electronics
language:
Short-container-title:IEEE J. Emerg. Sel. Topics Power Electron.

Author:

Huang Yajie¹,Zhang Donglai¹^ORCID,Wang Tao²,Li Anshou³

Affiliation:

1. Power Electronics and Motion Control Research Center, Harbin Institute of Technology (Shenzhen), Shenzhen, China

2. Shenzhen Aerospace New Power Technology Ltd, Shenzhen, China

3. Department of Mathematics and Theories, Peng Cheng Laboratory, Shenzhen, China

Funder

National Natural Science Foundation of China

Shenzhen Municipal Commission of Basic Research Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Link

http://xplorestaging.ieee.org/ielx7/6245517/10336248/10298204.pdf?arnumber=10298204

Reference32 articles.

1. A Thermal Modeling Method Considering Ambient Temperature Dynamics

2. A VEN Condition Monitoring Method of DC-Link Capacitors for Power Converters

3. Temperature Estimation of Aluminum Electrolytic Capacitor under Actual Circuit Operation

4. Electrothermal Stress Analysis and Lifetime Evaluation of DC-Link Capacitor Banks in the Railway Traction Drive System

5. Prediction of Capacitor’s Accelerated Aging Based on Advanced Measurements and Deep Neural Network Techniques

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1. Converter Capacitor Temperature Estimation Based on Continued Training LSTM under Variable Load Conditions;Sensors;2024-07-02

2. Data-Driven Modeling and Compensation Strategy of PMSM Considering Core Loss and Saturation;IEEE Journal of Emerging and Selected Topics in Power Electronics;2024-04

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