End of performance prediction of lithium-ion batteries
Journal article, Peer reviewed
Accepted version
Åpne
Permanent lenke
http://hdl.handle.net/11250/2593314Utgivelsesdato
2019Metadata
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- Institutt for matematiske fag [2533]
- Publikasjoner fra CRIStin - NTNU [38576]
Originalversjon
10.1080/00224065.2018.1541388Sammendrag
Rechargeable batteries are critical components for the performance of portable electronics and electric vehicles. The long-term health performance of rechargeable batteries is characterized by state of health, which can be quantified by end of performance (EOP) and remaining useful performance. Focusing on EOP prediction, this article first proposes an accelerated testing version of the trend-renewal process model to address this decision problem. The proposed model is also applied to a real case study. Finally, a NASA dataset is used to address the prediction performance of the proposed model. Comparing with the existing prediction methods and time series models, our proposed procedure has better performance in the EOP prediction.