A Web Based Clustering Analysis Toolbox WBCA design Using MATLAB.docx

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A Web Based Clustering Analysis Toolbox WBCA design Using MATLAB.docx

AWebBasedClusteringAnalysisToolboxWBCAdesignUsingMATLAB

Inthissystemtwopermanent-magnet-brushlessdcmotors(PMBDCMs)areconnecteddirectlyinserial,inordertocutdownthedifferentialalgorithmthoroughlyinvelocitycontrolstrategy.ThisstructurecanrealizethedifferentialautomaticallywhentheEVrunsonthesmoothroadatlowspeed.Butthisstructureconsidersthecharactersofthemotoronly,whichisanidealsystem.EVisacomplexelectromechanicalsystem,anditsworkconditionisalsocomplex.Thevariationoftheexternalconditionandtheworkconditionofoperationcanaffecttheoperationofmotor,sothestateoftheEVwillchange.Inthispaper,accordingtothechangeoftheworkconditionandroadcondition,combinedwiththedynamicsofEV,thisproblemwaswellstudied.TheneuralnetworkPIDcontrolmodewasusedinthispaper,andbymeansoftheMatlab/Simulinkandtheexperimentalverification,itrevealsthatthismethodcanenhancethesafetyandstabilityofthissystem.

ArticleOutline

1.Introduction

2.PMBDCM’scharacter

3.Serial-typemotorselectricvehicledrivingsystem

4.DynamicmodelofthewholeEV

5.Forcediagramofthetyre(Konghui,1991)

6.NeuralnetworkPIDcontrolmode

7.Simulationandexperimentalresults

8.Conclusion

References

104

Multi-objectivemodel-basedcontrolforanautomotivecatalyst  OriginalResearchArticle

JournalofProcessControl,Volume16,Issue1,January2006,Pages27-35

KennethR.Muske,JamesC.PeytonJones

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AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences

Abstract

Amodel-basedfeedforward/feedbackairfuelratiocontrollerthatoptimizestheoxygenstoragecapacityofthethree-waycatalystinautomotiveemissioncontrolsystemsispresented.Thisworkincorporatesasimplifieddynamiccatalystmodelthatdescribesthephysicalbehaviorofoxygenchemisorptionandreversibledeactivationinthecatalystsystem.Anovelaspectofthisworkistheuseoftheoxygenstoragecapabilityofthecatalystnotonlytominimizevehicleemissionsbutalsotooptimizeengineperformanceandfueleconomyduringtransientenginedemand.Thefeedback/feedforwardcontrollerisanonlinearmodelpredictivecontrollerthatincorporatescatalyst,engineairfuelratiocontroller,andfuelsystemmodelstodeterminetheoptimalairfuelratiotargettrajectory.Feedbackisprovidedbyanonlinearmovinghorizonestimationstrategyforthedeterminationoftheoxygenstoragelevelofthecatalystbasedonairfuelratiosensors.

ArticleOutline

1.Introduction

2.Catalystoperation

3.Catalystsystemmodel

3.1.Catalystoxygenstoragemodel

3.2.Post-catalystUEGOsensordistortion

3.3.Pre-catalystairfuelratioandfuelsystemmodels

3.4.Discrete-timesystemmodel

4.Oxygenstoragestateestimation

5.Model-basedcatalystcontrolstrategy

5.1.Model-basedcontrolalgorithm

5.2.Airfuelratiotargetreference

6.Example

7.Conclusions

Acknowledgements

References

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105

Simulationofairflowandpollutionlevelscausedbyseveretrafficjaminaroadtunnel  OriginalResearchArticle

TunnellingandUndergroundSpaceTechnology,Volume25,Issue1,January2010,Pages70-77

S.Bari,J.Naser

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AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences

Abstract

ComputersimulationswerecarriedouttostudyairflowpatternsandpollutionlevelsduetoemissionsfromvehiclesforthewestboundMelbourneCityLinktunnelunderseverelycongestedtrafficjamconditions.Thetimeaveragedequationsforvelocity,pressure,temperatureandmassfractionofemissionsweresolvedusingCFDsoftwareFLUENT6.0.ThemaximummassfractionsofO2,CO2andCOwerefoundtobe0.16,0.14and0.002,respectively.Thesehighlevelsofpollutantsweredetecteddespitethefactthatroof-mountedfanspushedexhaustfumesouttheexitandsuckedfreshairinfromtheinletofthetunnel.Duringanotherconditionofpowerfailure,whenthefanswerenotinoperation,theflowinsidethetunnelwasmainlydrivenbybuoyancyandtheconcentrationlevelsofO2,CO2andCOwerethenfoundtobe0.05,0.18and0.0028,respectively.Thesesemissionsfromthevehiclesforbothcasesposedathreattohumanhealth.Toavoidthisdangeroussituationamulti-prongedapproachisneededthatincludeshavingalternativesourcesofpowerforthefans,ensuringfasterevacuationofpassengersanddrivers,aswellasswitching-offenginesduringprolongedtrafficstandstill.

ArticleOutline

1.Introduction

2.MelbourneCityLinktunnel

3.Solutiondomainandboundaryconditions

4.Mathematicalmodel

5.Resultsanddiscussions

5.1.Bothreversiblejetandaxialfansrunning

5.2.No-fan-running

6.Conclusions

Acknowledgements

References

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106

Optimaltollsformulti-classtraffic:

Analyticalformulationsandpolicyimplications  OriginalResearchArticle

TransportationResearchPartA:

PolicyandPractice,Volume43,Issue4,May2009,Pages445-467

JoséHolguín-Veras,MecitCetin

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Abstract

Thispaperputstogetherananalyticalformulationtocomputeoptimaltollsformulti-classtraffic.Theformulationiscomprisedoftwomajormodules.ThefirstoneisanoptimizationcomponentaimedatcomputingoptimaltollsassumingaStackelberggameinwhichthetollagencysetsthetolls,andtheequilibratingtrafficplaystheroleofthefollowers.Theoptimizationcomponentissupportedbyasetofcostmodelsthatestimatetheexternalitiesasafunctionofamultivariatevectoroftrafficflows.ThesemodelswereestimatedusingTaylorseriesexpansionsoftheoutputobtainedfromtrafficsimulationsofahypotheticaltestcase.Ofimportancetothepaperisthetotaltraveltimefunctionestimatedusingthisapproachthatexpressestotaltraveltimeasamultivariatefunctionofthetrafficvolumes.Theformulationpresentedinthepaperisthenappliedtoavarietyofscenariostogaininsightintotheoptimalityofcurrenttollpolicies.Theoptimaltollsarecomputedfortwodifferentcases:

independenttolls,andtollsproportionaltopassengercarequivalencies(PCE).

ThenumericalresultsclearlyshowthatsettingtollsproportionaltoPCEsleadstolowervaluesofwelfarethatareonaverage15%lowerthanwhenusingindependenttolls,though,insomecasesthetotalwelfarecouldbeupto33%lower.Thisisaconsequenceoftwofactors.First,thecaseofindependenttollshasmoredegreesoffreedomthanthecaseoftollsproportionaltoPCEs.Second,tollsproportionaltoPCEsdonotaccountforexternalitiesotherthancongestion,whichislikelytoleadtolowerwelfarevalues.

Theanalyticalformulationsandnumericalresultsindicatethat,becausethetotaltraveltimeisanon-linearfunctionofthetrafficvolumes,themarginalsocialcostsandthustheoptimalcongestiontollsalsodependonthetrafficvolumesforeachvehicleclass.Asaresultofthis,fortherelativelylowvolumesoftrucktrafficobservedinreallife,theoptimalcongestiontollsfortruckscouldindeedbeeitherloweroraboutthesameasforpassengercars.ThisstandinsharpcontrastwithwhatisimpliedintheuseofPCEs,i.e.,thatthecontributiontocongestionareconstant.ThislatterassumptionleadstooptimaltruckcongestiontollsthatarealwaysproportionaltothePCEvalues.

Thecomparisonofthetollratios(trucktollsdividedbypassengercartolls)forbothobservedandoptimalconditionssuggeststhatthetollsforsmalltrucksareabouttherightlevel,maybeaslightlylowerthanoptimal.However,theanalysisofthetollratioforlargetrucksseemstoindicateasignificantovercharge.Theestimatesshowthattheaverageobservedtollratioforlargetrucksisevenhigherthanthemaximumoptimaltollratiofoundinthenumericalexperiments.Thissuggeststhatthetollsforlargetrucksaresetonthebasisofrevenuegenerationprincipleswhilethepassengercartollsarebeingsetbasedonamildformofwelfaremaximization.Thisleadstoasuboptimalcross-subsidizationofpassengercartrafficindetrimentofanimportantsectoroftheeconomy.

ArticleOutline

1.Introduction

2.Literaturereview

3.Economicmodel

4.Demandfunctions

5.Externalcosts

5.1.Congestioncosts

5.2.Environmentalcosts

5.3.Pavementcosts

5.4.Totalcostmodel

5.5.Estimationofexternalcostmodelsfornumericalexperiments

5.6.Estimationofexternalitycostmodels

6.Optimizationproblems

6.1.Optimizationproblem#1(multipleindependenttolls)

6.2.Optimizationproblem#2(tollsproportionaltopassengercarequivalencies)

7.Selectionofvaluationestimates

8.Numericalresults

8.1.Welfareimplications

8.2.Optimaltolls

9.Conclusions

Acknowledgements

References

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107

Open-architecturesystembasedonareconfigurablehardware–softwaremulti-agentplatformforCNCmachines  OriginalResearchArticle

JournalofSystemsArchitecture,Volume56,Issue9,September2010,Pages407-418

LuisMorales-Velazquez,RenedeJesusRomero-Troncoso,RoqueAlfredoOsornio-Rios,GilbertoHerrera-Ruiz,EduardoCabal-Yepez

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AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences

Abstract

Newgenerationofmanufacturingsystemsendowstheirintelligenceandreconfigurabilitytothecomputerizednumericalcontroll

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