Open AccessData Analysis and Research of Lithium-Ion Battery Based on Data Mining Technology
Author(s) -
Zhi Yang,
Jianhua Wu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1631/1/012144
Subject(s) - battery (electricity) , lithium ion battery , computer science , electronics , lithium (medication) , automotive engineering , electrical engineering , engineering , medicine , power (physics) , physics , quantum mechanics , endocrinology
With the development of consumer electronics and energy storage systems, the market demand of lithium-ion batteries is rapidly increasing. To improve the application efficiency of lithium-ion battery, it is necessary to investigate the influence of battery parameters on the available capacity of the battery. In this paper, the data mining technology is used to study and analyze the parameter data of lithium-ion battery, aiming at exploring relationships among multi-parameters and capacity in battery charge and discharge processes, and Python language is applied to realize this end. The proposed data mining technology for lithium-ion battery includes the cleaning and discretization of lithium-ion battery data, the correlation analysis of lithium battery parameters using association rule Apriori algorithm, and the visual processing of the relationship between charge and discharge time and battery capacity.