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Multi-objective optimization in battery selection for hybrid electric vehicle applications
Joint Authors
Panday, Aishwarya
Bansal, Hari Om
Source
Issue
Vol. 12, Issue 2 (30 Jun. 2016), pp.325-343, 19 p.
Publisher
Publication Date
2016-06-30
Country of Publication
Algeria
No. of Pages
19
Main Subjects
Abstract EN
This paper proclaims the battery selection for hybrid electric vehicle applications using multiobjective optimization techniques.
Ashby's methodology, Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) and VIse Kriterijum-ska Optimizacija Komprominsno Resenje (VIKOR) methods are employed here for the assessment.
Various attributes considered for analysis are specific energy, energy density, electrical efficiency, self-discharge rate, nominal cell voltage, energy, cost and durability.
The batteries considered for analysis are Liion, Ni-MH, Ni-Cd and Pb-acid.
Based on the performance indices and battery attributes, selection charts and tables are presented here.
It is observed that Li-ion batteries are most suitable for hybrid electric vehicle applications followed by Ni-MH batteries.
The outcomes of all methods considered are uniform and promising.
The results obtained are also matched up with actual practices in automotive industries.
Alike results confirm the validity of this study.
American Psychological Association (APA)
Panday, Aishwarya& Bansal, Hari Om. 2016. Multi-objective optimization in battery selection for hybrid electric vehicle applications. Journal of Electrical Systems،Vol. 12, no. 2, pp.325-343.
https://search.emarefa.net/detail/BIM-689844
Modern Language Association (MLA)
Panday, Aishwarya& Bansal, Hari Om. Multi-objective optimization in battery selection for hybrid electric vehicle applications. Journal of Electrical Systems Vol. 12, no. 2 (2016), pp.325-343.
https://search.emarefa.net/detail/BIM-689844
American Medical Association (AMA)
Panday, Aishwarya& Bansal, Hari Om. Multi-objective optimization in battery selection for hybrid electric vehicle applications. Journal of Electrical Systems. 2016. Vol. 12, no. 2, pp.325-343.
https://search.emarefa.net/detail/BIM-689844
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 341-343
Record ID
BIM-689844