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Supervisory Power Management Control Algorithms for Hybrid Electric Vehicles: A Survey

contributor authorMalikopoulos, Andreas /A/.
date accessioned2020-03-12T23:55:23Z
date available2020-03-12T23:55:23Z
date issued2014
identifier issn1524-9050
identifier other6781036.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1128186?show=full
formatgeneral
languageEnglish
publisherIEEE
titleSupervisory Power Management Control Algorithms for Hybrid Electric Vehicles: A Survey
typeJournal Paper
contenttypeMetadata Only
identifier padid8308280
subject keywordselectric propulsion
subject keywordsfuel economy
subject keywordshybrid electric vehicles
subject keywordspower control
subject keywordsenvironmentally benign hybrid propulsion systems
subject keywordsfuel economy
subject keywordshybrid electric vehicles
subject keywordsparallel PHEVs
subject keywordsplug-in HEVs
subject keywordspollutant emissions
subject keywordspower split PHEVs
subject keywordsseries PHEVs
subject keywordssupervisory power management control algorithms
subject keywordsBatteries
subject keywordsEngines
subject keywordsFuels
subject keywordsHybrid electric vehicles
subject keywordsMechanical power transmission
subject keywordsOptimization
subject keywordsHybrid electric vehicles (HEVs)
subject keywordsplug-in HEVs (PHEVs)
subject keywordssupervisory power management control algorithms
identifier doi10.1109/TITS.2014.2309674
journal titleIntelligent Transportation Systems, IEEE Transactions on
journal volume15
journal issue5
filesize846510
citations0


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