Fault Detection for Power Batteries Using a Generative Adversarial Network with a Convolutional Long Short-Term Memory (GAN-CNN-LSTM) Hybrid Model

Fault Detection for Power Batteries Using a Generative Adversarial Network with a Convolutional Long Short-Term Memory (GAN-CNN-LSTM) Hybrid Model

With the rapid proliferation of new energy vehicles, the safety of power batteries has attracted increasing attention. As a crucial approach to ensuring system stability, fault detection has become a research focus. However, strong temporal dependencies in battery operation data and the scarcity of...

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Bibliographic Details
Main Authors: Shaofan Liu, Tianbao Xie, Yanxin Li, Siyu Liu
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
Subjects:
power battery
fault detection
imbalanced dataset
machine learning
deep learning
generative model
Online Access:https://www.mdpi.com/2076-3417/15/11/5795
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