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With the aim of moderating the consumption of traditional fuels and carbon

Zhen Zhang, Hongrui Sun

2022Englishbatteriesenergy storageelectrochemistrylithium-ion batteriesbattery agingcapacity estimation

Abstract

Language:

Capacity attenuation is one of the most intractable issues in the current application of the cells. The disintegration mechanism is known to be very complex across the system, making it a significant challenge to fully comprehend and accurately predict the process. This study employs machine learning (ML) technology to predict the specific capacity change of the cell throughout the cycle and grasps this intricate procedure. Unlike previous works, the proposed WOA-ELM model (R2 = 0.9999871) identifies the key factors affecting the specific capacity of the battery while overcoming defects in the machine learning black box through an interpretable model. The study also explains comprehensively their connection with the structural damage of electrode materials and battery failure during cycling, revealing their essentiality to battery performance. This research paves the way for superior studies on contemporary batteries and their modifications.

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Cite This Work

@article{3bbf0b28-fb3e-431f-9efc-83538dbf0dce,
  title={With the aim of moderating the consumption of traditional fuels and carbon},
  author={Zhen Zhang and Hongrui Sun},
  year={2022},
  language={English}
}
TY  - JOUR
TI  - With the aim of moderating the consumption of traditional fuels and carbon
AU  - Zhen Zhang
AU  - Hongrui Sun
PY  - 2022
LA  - English
ER  -

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