Title :
Applying Management Methodology to Electric Vehicles with Multiple Energy Storage Systems
Author :
Rosario, Leon ; Luk, Patrick Chi Kwong
Author_Institution :
Cranfield Univ., Shrivenham
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;
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
DOI :
10.1109/ICMLC.2007.4370888