期刊
ENERGIES
卷 6, 期 6, 页码 3082-3096出版社
MDPI
DOI: 10.3390/en6063082
关键词
remaining useful life; battery capacity; lithium-ion batteries; adaptive bathtub-shaped function; mean average precision; mean standard deviation; swarm fish algorithm
资金
- National Natural Science Foundation of China [61179059, 51105061, 50905028]
- Scientific Research Foundation for the Returned Overseas Chinese Scholars
- State Education Ministry [201294001]
- Program for New Century Excellent Talents in University [NCET-11-0063]
- Div Of Civil, Mechanical, & Manufact Inn
- Directorate For Engineering [1234451] Funding Source: National Science Foundation
Batteries are one of the most important components in many mechatronics systems, as they supply power to the systems and their failures may lead to reduced performance or even catastrophic results. Therefore, the prediction analysis of remaining useful life (RUL) of batteries is very important. This paper develops a quantitative approach for battery RUL prediction using an adaptive bathtub-shaped function (ABF). ABF has been utilised to model the normalised battery cycle capacity prognostic curves, which attempt to predict the remaining battery capacity with given historical test data. An artificial fish swarm algorithm method with a variable population size (AFSAVP) is employed as the optimiser for the parameter determination of the ABF curves, in which the fitness function is defined in the form of a coefficient of determination (R-2). A 4 x 2 cross-validation (CV) has been devised, and the results show that the method can work valuably for battery health management and battery life prediction.
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