鋰電池模組故障排除系統暨衰退評估模型建置研究( II );Study on the Development and Implementation of Fault Trouble Shooting System and Degradation Assessment Model for Li-Ion Battery Packs( II )

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题名:	鋰電池模組故障排除系統暨衰退評估模型建置研究( II );Study on the Development and Implementation of Fault Trouble Shooting System and Degradation Assessment Model for Li-Ion Battery Packs( II )
作者:	潘敏俊
贡献者:	國立中央大學機械工程學系
关键词:	鋰電池組;故障排除;知識庫系統;衰退模型;殘餘壽命評估;;Li-ion Battery Pack;Fault Trouble Shooting;Knowledge System;Degradation Model;Prediction of Remaining Useful Life.
日期:	2020-01-13
上传时间:	2020-01-13 14:56:44 (UTC+8)
出版者:	科技部
摘要:	新普科技集團為當前世界上消費型電池設計製造商領導品牌，旗下嘉普科技(股)公司提供各類動力系統鋰電池模組研發製造及服務，客戶多分散國外、尤其以歐洲為主；經多年營運而有鋰電池故障排除系統開發、老化衰退評估模型建置的需求。相關技術發展，前者可降低技術人員往返提供工程服務的營運成本；而後者可因老化衰退模型獲得可靠的殘餘壽命評估，分別達到避免客戶臨時停機的損失、或能降低電池消費成本雙重目的。本產學計畫將由執行單位與配合企業嘉普科技共同開發上述技術，透過鋰電池領域專家技術人員經驗，彙整故障排除及失效應對經驗法則，建立知識庫系統；在老化衰退模型建立方面，將發展基於模型及資料的混成技術，適當結合卡曼濾波、經驗模型分解、及型態識別演算法等，達到能夠對所探討鋰電池組進行可靠的殘餘壽命評估目標，以提升配合企業的先導技術能力。 ;The SMP Group has become a leading brand of a design and manufacturing company for consumer electronics battery packs in the world. In the group Trend Power Technology Co. studies and supplies varied li-ion battery packs of power systems worldwide, especially for European countries. For years of operation their unmet needs include the development and implementation of both fault trouble shooting system and degradation evaluation model. The benefits brought by the techniques to be developed are two-folds. One is it enables to save the cost of engineering support. The other is the estimated remaining useful life obtained from the degradation model may achieve preventing the power system from unexpected shutdown and saving the cost of using battery packs. This industry-academic bilateral project aims to investigate the above techniques cooperatively. To construct the knowledge system for the fault trouble shooting of li-ion battery packs, the experience and rules of failure modes to fault detection will be searched and collected. As to the degradation model for an individual battery pack, in the project a data-driven and model-based hybrid technique will be investigated to effectively predict remaining useful life through combining Kalman filtering, empirical model decomposition and pattern recognition algorithm. The studies through performing this project expect to enhance the leading technologies of the enterprise.
關聯:	財團法人國家實驗研究院科技政策研究與資訊中心
显示于类别:	[機械工程學系] 研究計畫

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