Data redundancy reduction using sensitivity analysis method for machine-learning-based battery management system

Data redundancy reduction using sensitivity analysis method for machine-learning-based battery management system

This thesis proposes a sensitivity analysis method to reduce the computational effort of machine-learning (ML) techniques in the battery management system (BMS). The novel approach analyzes the sensitivity of lithium-ion battery model parameters towards their discharge performances. The sensitivity...

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書目詳細資料
主要作者:	Mustaza, Muhammad Syafiq Anwar
格式:	Thesis
語言:	English English English
出版:	2021
主題:	TA1501-1820 Applied optics Photonics
在線閱讀:	http://eprints.uthm.edu.my/987/1/24p%20MUHAMMAD%20SYAFIQ%20ANWAR%20BIN%20MUSTAZA.pdf http://eprints.uthm.edu.my/987/4/MUHAMMAD%20SYAFIQ%20ANWAR%20BIN%20MUSTAZA%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/987/5/MUHAMMAD%20SYAFIQ%20ANWAR%20BIN%20MUSTAZA%20WATERMARK.pdf
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