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Emerging Technologies for Electric and Hybrid Vehicles
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Energies 2016,9, 270 examinetherationalityandstabilityof theproposedframeworkandanalysis results, thesensitivity analysisofνvalueandsub-criteriaweightsarepresented. Table6showsthat thesub-criteriaC9andC10affiliatedwith theenvironmentalaspectobtain muchmore attention from the expert group, which reflects the strategy and energy saving and environmentprotectiongoalsof theChinesegovernment.Meanwhile, thesub-criteriaaffiliatedwith economicdevelopment are not so important as before,which is consistentwith thedevelopment goalsofChina.Asweallknow, inrecentyears, transportationandelectricity industryhassuffered pressuresandchallenges fromthe“twelfthfive-year”planandtheenvironmentalprotection lawof China,which indicates theresponsibilityandtargetof these industries forenvironmentprotection. Moreover, thesevereenvironmentandresource issueshaveposedundesirableconditions tohumans for living. Therefore, theenvironmentalaspecthasbeengivenmoreconsiderationbyexperts for the optimalsitingforEVCSs inChina. Asmentionedabove, this studyuses thevariationofvvalues todemonstrate thatallof themdo notaffect theanalysis results (Figure4). Thevvaluesarepostulatedtochangefrom0.1 to0.9,while therankingordersoffiveEVCSsaresame,namelyA3>A5>A2>A1>A4.Andthus, this studycan confirmthat theresultsobtainedbyusingtheproposedmodelarereliableandeffective. Figure4.Sensitivityanalysisofvvalue foreachalternative. Next, a sensitivity analysis on the impacts of sub-criteriaweights for optimal EVCS siting is presented, soas toobtainbetter insightofevaluationresultsandverify therobustnessofevaluation results.Accordingto thecriteria, thirteensub-criteriaaredividedinto fouranalysisaspects,namely economy,society,environmentandtechnology.All sub-criteriahave10%,20%and30%lessweight thanthebaseweightand10%,20%and30%moreweight thanthebaseweight (allbaseweightsare showninTable6). It canbeseenthat inFigure5, theQiofA5andA1decreasewhenthesub-criterionC1becomes less important. TheQiofA2increaseswhentheweightofC1becomesmore important,andit ranks fourth, surpassedbyA1.However,nomatterhowtheC1weightchanges, theQiofA3alwayshas the lowest score, indicating thebestalternative.AsC2 isgivenmore importance,only theQiofA2shows asmall rising tendency,while the scoresofotheralternatives remain relatively stablealthoughC2 carries largeweight in theoptimalEVCSsiting. In thecaseofC3, theQiofA1andA5dramaticallyrise alongwithweight increase,whichgetscloser to thatofA4andA2, respectively.A3andA4arestill the optimalandworst sites thesameas in thebasecase.Apparently,C1andC3aresensiblesub-criteria whichdramaticallyaffect theoptimalEVCSsitingresults.However,nomatterhowtheweights in the economygroupchange,A3 isalways thebestchoice in theoptimalsitingofEVCSinTianjin. 195
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Emerging Technologies for Electric and Hybrid Vehicles
Title
Emerging Technologies for Electric and Hybrid Vehicles
Editor
MDPI
Location
Basel
Date
2017
Language
English
License
CC BY-NC-ND 4.0
ISBN
978-3-03897-191-7
Size
17.0 x 24.4 cm
Pages
376
Keywords
electric vehicle, plug-in hybrid electric vehicle (PHEV), energy sources, energy management strategy, energy-storage system, charging technologies, control algorithms, battery, operating scenario, wireless power transfer (WPT)
Category
Technik
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Emerging Technologies for Electric and Hybrid Vehicles