Building equivalent circuit models of lithium-ion battery by means of genetic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @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