Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/13542
Title: A high fuel consumption efficiency management scheme for PHEVs using an adaptive genetic algorithm
Authors: Lee, WC 
Tsang, KF
Chi, HR
Hung, FH
Wu, CK
Chui, KT
Lau, WH
Leung, YW
Keywords: Adaptive genetic algorithm
Fuel efficiency management
PHEV
Issue Date: 2015
Publisher: Molecular Diversity Preservation International (MDPI)
Source: Sensors, 2015, v. 15, no. 1, p. 1245-1251 How to cite?
Journal: Sensors 
Abstract: A high fuel efficiency management scheme for plug-in hybrid electric vehicles (PHEVs) has been developed. In order to achieve fuel consumption reduction, an adaptive genetic algorithm scheme has been designed to adaptively manage the energy resource usage. The objective function of the genetic algorithm is implemented by designing a fuzzy logic controller which closely monitors and resembles the driving conditions and environment of PHEVs, thus trading off between petrol versus electricity for optimal driving efficiency. Comparison between calculated results and publicized data shows that the achieved efficiency of the fuzzified genetic algorithm is better by 10% than existing schemes. The developed scheme, if fully adopted, would help reduce over 600 tons of CO2 emissions worldwide every day.
URI: http://hdl.handle.net/10397/13542
EISSN: 1424-8220
DOI: 10.3390/s150101245
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