Building equivalent circuit models of lithium-ion battery by means of genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Zhao:2014:IJWMC,

• author = "Li Zhao and Wan-Ke Cao and Yu-Tao He",
• title = "Building equivalent circuit models of lithium-ion battery by means of genetic programming",
• journal = "International Journal of Wireless and Mobile Computing",
• year = "2014",
• month = oct # "~31",
• volume = "7",
• number = "3",
• pages = "275--281",
• keywords = "genetic algorithms, genetic programming, equivalent circuit models, SOC, state of charge, lithium-ion batteries, battery system design, battery modelling, electric vehicles, model-based state estimation",
• ISSN = "1741-1092",
• bibsource = "OAI-PMH server at www.inderscience.com",
• language = "eng",
• publisher = "Inderscience Publishers",
• URL = "http://www.inderscience.com/link.php?id=62005",
• DOI = "DOI:10.1504/IJWMC.2014.062005",
• abstract = "In the process of battery system design and operation, accurate battery modeling is a key factor. Generally speaking, the electric characteristics of a given battery cell are necessary for a designer to build an equivalent circuit model. The equivalent circuit design entails the creation of both the sizing of components used in the circuit and the topology. So, it is very hard to build an accurate battery model for electric vehicles. This paper presents a single method to design an accurate equivalent circuit by computer automatically. The obtained model enables the assessment of the cells state of charge (SOC) precisely using model-based state estimation approaches.",
• notes = "National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 10081, China Shijiazhuang Vocational Technology Institute Shijiazhuang 050081, China",

}

Genetic Programming entries for Li Zhao Wan-Ke Cao Yu-Tao He

Citations