利用联合电池诊断和预测催化深度脱碳,改善储能系统的数据管理

IF 7.9 2区 综合性期刊 Q1 CHEMISTRY, MULTIDISCIPLINARY Cell Reports Physical Science Pub Date : 2024-09-19 DOI:10.1016/j.xcrp.2024.102215
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引用次数: 0

摘要

工业数据分析方法在提高储能性能和效率方面发挥着核心作用,影响着电气化交通的未来。
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Catalyzing deep decarbonization with federated battery diagnosis and prognosis for better data management in energy storage systems
Industrial data analytics methods play a central role in improving energy storage performance and efficiency, impacting the future of electrified tran…
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来源期刊
Cell Reports Physical Science
Cell Reports Physical Science Energy-Energy (all)
CiteScore
11.40
自引率
2.20%
发文量
388
审稿时长
62 days
期刊介绍: Cell Reports Physical Science, a premium open-access journal from Cell Press, features high-quality, cutting-edge research spanning the physical sciences. It serves as an open forum fostering collaboration among physical scientists while championing open science principles. Published works must signify significant advancements in fundamental insight or technological applications within fields such as chemistry, physics, materials science, energy science, engineering, and related interdisciplinary studies. In addition to longer articles, the journal considers impactful short-form reports and short reviews covering recent literature in emerging fields. Continually adapting to the evolving open science landscape, the journal reviews its policies to align with community consensus and best practices.
期刊最新文献
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