AI for Status Monitoring of Utility Scale Batteries - Wang, Shunli; Liu, Kailong; Wang, Yujie
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Utility-scale Li-ion batteries are poised to play key roles for the clean energy system, but their failure has severe effects. AI can help with their monitoring and management. This work covers machine learning, neural networks, and deep learning, for battery modeling.

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Produktbeschreibung
Utility-scale Li-ion batteries are poised to play key roles for the clean energy system, but their failure has severe effects. AI can help with their monitoring and management. This work covers machine learning, neural networks, and deep learning, for battery modeling.
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Autorenporträt
Shunli Wang is a professor at Southwest University of Science and Technology, Sichuan, China. He is an expert in the field of new energy research. He is the head of NELab, conducting modeling and state estimation strategy research for lithium-ion batteries. He has undertaken over 40 projects and 30 patents, published over 100 research papers, and won 20 awards such as the Young Scholar, and Science & Technology Progress Awards.