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State of health prediction model based on internal resistance
Author(s) -
Ji Hao,
Zhang Wei,
Pan XuHai,
Hua Min,
Chung YiHong,
Shu ChiMin,
Zhang LiJing
Publication year - 2020
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.5383
Subject(s) - internal resistance , state of health , battery (electricity) , ternary operation , lithium ion battery , state of charge , electric vehicle , ion , materials science , automotive engineering , nuclear engineering , engineering , computer science , chemistry , thermodynamics , physics , power (physics) , organic chemistry , programming language
Summary The state of health (SOH) is a crucial indicator of lithium‐ion batteries. A battery cycle and calendar life are critical for electric vehicle batteries. Complex interactions occur between the SOH and internal resistance of a battery. In this study, several ternary lithium‐ion battery charge discharge experiments were performed to investigate the effects of the ambient temperature, discharge rate, and depth of discharge on a battery's internal resistance. An SOH prediction model was then constructed and used to evaluate the remaining capacity of the electric vehicle battery. The model was verified through various experiments, and a comparison of experimental and model‐derived data revealed a favorable agreement. Thus, the model accurately predicted the SOH of a ternary lithium‐ion battery.
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