DocumentCode
1939425
Title
Applying Management Methodology to Electric Vehicles with Multiple Energy Storage Systems
Author
Rosario, Leon ; Luk, Patrick Chi Kwong
Author_Institution
Cranfield Univ., Shrivenham
Volume
7
fYear
2007
fDate
19-22 Aug. 2007
Firstpage
4223
Lastpage
4230
Abstract
Research in power and energy management of multiple energy systems within electric vehicle (EV) architectures has been undertaken exclusively with scientific methodologies, with varying focuses and degree of success. However, the narrowing vision of scientific quest means other bodies of knowledge like management and economics are being largely ignored in this intriguing multi-discipline of power and energy management. Whilst current research endeavours embracing intelligent control strategies seem to offer some promising results, remarkably no effort is made to exploit well-known management concepts into this field of power management. This paper reports our work as the first to revisit the fundamentals of management concepts, with a view to formulating a novel modular power management framework that is readily implementable to a multi-sourced electric vehicle. Practical results are included to support the validity of the framework.
Keywords
cells (electric); electric vehicles; energy management systems; intelligent control; electric vehicles; energy management; intelligent control; multiple energy storage systems; multiple energy systems; multisourced electric vehicle; power management; Batteries; Conference management; Cybernetics; Electric vehicles; Energy management; Energy storage; Intelligent control; Machine learning; Power system management; Technology management; Batteries; Dual-sourced ultracapacitors; Electric vehicles; Power and energy management;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-0973-0
Electronic_ISBN
978-1-4244-0973-0
Type
conf
DOI
10.1109/ICMLC.2007.4370888
Filename
4370888
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