Experimental Combined Numerical Approach for Evaluation of Battery Capacity Based on the Initial Applied Stress, the Real-Time Stress, Charging Open Circuit Voltage, and Discharging Open Circuit Voltage
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{Yun:2018:MPE,
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author = "Liu Yun and Biranchi Panda and Liang Gao and
Akhil Garg and Xu Meijuan and Dezhi Chen and Chin-Tsan Wang",
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title = "Experimental Combined Numerical Approach for
Evaluation of Battery Capacity Based on the Initial
Applied Stress, the Real-Time Stress, Charging Open
Circuit Voltage, and Discharging Open Circuit Voltage",
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journal = "Mathematical Problems in Engineering",
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year = "2018",
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volume = "2018",
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number = "1",
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pages = "Article ID 8165164",
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keywords = "genetic algorithms, genetic programming, Li",
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ISSN = "1024-123X",
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bibsource = "OAI-PMH server at oai.repec.org",
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identifier = "RePEc:hin:jnlmpe:8165164",
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oai = "oai:RePEc:hin:jnlmpe:8165164",
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URL = "https://downloads.hindawi.com/journals/mpe/2018/8165164.pdf",
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DOI = "doi:10.1155/2018/8165164",
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size = "16 pages",
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abstract = "With the intensification of energy crisis,
considerable attention has been paid to the application
and research of lithium-ion batteries. A significant
progress has also been made in the research of
lithium-ion battery capacity evaluation using
electrochemical and electrical parameters. In this
study, the effect of mechanical characteristic
parameter (i.e., stack stress) on battery capacity is
investigated using the experimental combined numerical
approach. The objective of the proposed approach is to
evaluate the capacity based on the initial applied
stress, the real-time stress, charging open circuit
voltage, and discharging open circuit voltage.
Experiments were designed and the data is fed into
evolutionary approach of genetic programming. Based on
analysis, the accuracy of the proposed GP model is
fairly high while the maximum percentage of error is
about 5percent. In addition, a negative correlation
exists between the initial stress and battery capacity
while the capacity increases with real-time stress.",
- }
Genetic Programming entries for
Liu Yun
Biranchi Narayan Panda
Liang Gao
Akhil Garg
Xu Meijuan
Dezhi Chen
Chin-Tsan Wang
Citations