基于具有自注意机制的卷积门控递归神经网络的锂离子电池健康状态估计

IF 3.1 4区工程技术 Q3 ENERGY & FUELS

International Journal of Green Energy Pub Date : 2024-04-03 DOI:10.1080/15435075.2024.2335510

Zewang Chen, Zhaofan Xu, Hanrui Wang, Na Shi, Lin Yang

引用次数: 0

摘要

锂离子电池的健康状况（SOH）是电池管理系统的一个关键参数。对其进行准确估算可以提高电池的整体寿命。以数据为驱动的测量方法可用于测量...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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State-of-health estimation of lithium-ion battery based on convolutional-gated recurrent neural network with self-attention mechanism

The state of health (SOH) of lithium-ion batteries is a critical parameter of the battery management system. An accurate estimation of it can improve the battery’s overall life. The data-driven met...

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来源期刊

International Journal of Green Energy 工程技术-能源与燃料

CiteScore

6.60

自引率

9.10%

发文量

112

审稿时长

3.7 months

期刊介绍： International Journal of Green Energy shares multidisciplinary research results in the fields of energy research, energy conversion, energy management, and energy conservation, with a particular interest in advanced, environmentally friendly energy technologies. We publish research that focuses on the forms and utilizations of energy that have no, minimal, or reduced impact on environment, economy and society.