Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/13542
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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
Issue Date: 2015
Source: Sensors, Jan. 2015, v. 15, no. 1, p. 1245-1251
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.
Keywords: Adaptive genetic algorithm
Fuel efficiency management
PHEV
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Sensors 
EISSN: 1424-8220
DOI: 10.3390/s150101245
Rights: © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
The following publication Lee, W.C.; Tsang, K.F.; Chi, H.R.; Hung, F.H.; Wu, C.K.; Chui, K.T.; Lau, W.H.; Leung, Y.W. A High Fuel Consumption Efficiency Management Scheme for PHEVs Using an Adaptive Genetic Algorithm. Sensors 2015, 15, 1245-1251 is available at https://dx.doi.org/10.3390/s150101245
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