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讲准字【2021】第390号:Machine learning for electrochemical energy storage

发布时间:2021-12-08|浏览次数:

讲座报告主题:Machine learning for electrochemical energy storage
专家姓名:Akeel Abbas Shah
日期:2021-12-15 时间:10:00
地点:能源研究院1501会议室
主办单位:能源研究院

主讲概况:Professor Akeel A. Shah graduated with a first-class honours degree in Mathematical Physics in 1995 and a PhD in Applied Mathematics (both from University of Manchester Institute of Science and Technology) in 2001. He is currently a Professor in University of Warwick, UK and a specially appointed Professor in Chongqing University, China, with expertise in electrochemical energy conversion, computational engineering and applied machine learning. He previously held position at University of Southampton. His work is primarily focused on the modelling and simulation of energy-conversion devices, including computational modelling, and the development of fast algorithms for computer codes in science and engineering based on machine learning and computational statistics. Between 2004 and 2006, he held a joint Pacific Institute of Mathematics Sciences (PIMS) and Mathematics of Information Technology and Complex Systems (MITACS) Fellowship. He is the author of over 85 publications in leading, international peer-reviewed journals. Professor Shah has worked closely with the fuel cell and battery industry (Ballard Power Systems, Johnson Matthey Corp., Sharp Laboratories, ACAL Energy Ltd) to develop models/numerical codes for design purposes. He has received funding from the TSB, FP7, dstl and directly from industry. 研究专长:燃料电池数值模拟,先进液流电池设计与优化。

主讲内容概况:储能电池相关信息进行大数据Machine Learning分析和模型构建,形成储能电池寿命管理系统,可以推荐符合预期经营运行的储能微网运行策略。根据算法模型和分析目标,人工智能技术可以对模型算法进行数据喂养和训练,提高算法精度,并对算法和模型进行验证和误差分析,校验模型的适用性和准确性。结合电化学和海量电池数据,评估引起电池析锂和热失控等故障的关键因素;对电芯和模组失效进行主动异常监测;通过AI实现电池故障预警,故障追踪,故障原因分析。


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