on-field eis-based diagnostic tool for pemfc · on-field eis-based diagnostic tool for pemfc c....
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Diagnosis-aidedcontrolforSOFCpowersystems
FCH-JU-2013-1 GRANT AGREEMENT NUMBER: 621208
On-field EIS-based diagnostic tool for PEMFC
C. Pianese, P. Polverino, M. Sorrentino, G. Spagnuolo
University of Salerno
Workshop on Monitoring, Diagnostics and Control for SOFC systems
Improving SOFC-based CHP performance through innovative diagnosis and control
Naples (I) – December 16th, 2015
Project Mid-term Exploitation Workshop
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§ Motivations & Objectives, Targets and Challenges
§ Background, Concept and Commitment
§ EIS-based diagnosis
§ Conclusions
2 DIAMOND – Mid-Term Workshop
Outlines
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MOTIVATION & OBJECTIVES, TARGETS & CHALLENGES
DIAMOND – Mid-Term Workshop 3
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Motivations & Objectives
DIAMOND – Mid-Term Workshop 4
• Needforadvanceddiagnos,ctoolstoimprovePEMFCslife,me.• Givesignificantinsightsintothestate-of-health(SOH)forbothstackandBalanceOf
Plant(BOP).• Reducetheempiricismofdiagnos,csandimprovecontrolviaquan,ta,ve
feedback.• SupporteffecJvecontroltomi,gatetheconsequencesofdegrada,on.• Faultdetec,onandisola,onmayalertoperatorstoreducetheriskoffailures.
MOTIVATIONS
• TransposeElectrochemical ImpedanceSpectroscopy(EIS)from lab-scaleto real-lifeon-fieldapplica,ons.
• Design a diagnosis-oriented DC/DC converter to obtain the stack impedancespectrumon-board.
• Derivea setof indicators fromthe spectrum toevaluateadifferencebetween theactualstatusandthenominalone.
OBJECTIVES
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Targets & Challenges
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TARGETS
• DeriveFCdegradaJon/diagnosJcinformaJonthroughon-boardEISwhilethesystemisrunningorisinstand-by;
• Impactofstack,BoPandconverterinteracJonsontheEIS;• LowfrequencyEISmaybeaffectedbybothloaddriPorcontrolstrategy;• HVapplicaJonsmaybecriJcalduetothenoisecomingfromtheload,whichmight
worsenthesignal-to-noisera,oduringtheEISanalysis;• Systemcharacteriza,onmethodologiesforon-boardimplementaJon.
CHALLENGES
• DiagnosetheFCSforaquan,ta,veassessmentofStack&BoPstatus;• ExpectaJonsfromimprovedsystemmanagement:
- Monitoringandfaultdiagnosis;- ForecastlifeJme;- ControlstrategyadaptaJon;
- Dynamicresponseimprovement;- Maintenanceplanning;- Ensuresystemreadiness;- Improvesystemreliability.
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BACKGROUND, CONCEPT AND COMMITMENT
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Technical background
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ElectrochemicalImpedanceSpectroscopy(EIS)collects
significantinformaJoninasinglerepresentaJon(i.e.theimpedancespectrum)guaranteeingaholis,c
analysisofthecell/stackbehavior.
On-boardEISandavailableBOPmeasurementsguaranteea
completeanalysisoftheFCstatewhilerunningon-field.
ThediagnosJcsystemwilldetectthefaultsandidenJfythemainsourcesforcriJcaloperaJonswithadeepercomprehensionofrela,onshipsamongcausesandeffects.
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D-CODE & HEALTH-CODE Concept
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FCSTACK
GRID/LOAD
DC/DCCONVERTER
SYSTEMCONTROLUNIT
BOP
EISBOARD
DIAGNOSIS
CONTROL*
FCSYSTEM
SYSTEMMANAGEMENTANDCONTROL
UNIT
*Controldesignandimplementa1onnotaccountedintheprojectproposals
DC/DCCOnverter-basedDiagnosticsforPEMsystems
www.d-code-jJ.eu
www.pemfc.health-code.eu(underconstrucJon)
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D-CODE & HEALTH-CODE Commitment
DIAMOND – Mid-Term Workshop 9
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7-0.05
0
0.05
0.1
0.15
0.2I = 08 [A]
Re(Z) [Ohm]
-Im(Z
) [Oh
m]
Exp. DataID Model
Fromlab-scale… …toon-board*!
d-code.eifer.kit.edu
*Furtherdetailson:www.d-code-jJ.eu
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EIS-BASED DIAGNOSIS
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Analysed faults & Proposed Algorithms
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• Floodinganddrying(i.e.watermanagement)• AirstarvaJon• FuelstarvaJon• Sulphurpoisoning• ChangeinfuelcomposiJon(contaminants)
FAULTS
DC/DCCOnverter-basedDiagnosticsforPEMsystems
DIAGNOSTICALGORITHMS*
• Model-basedthroughEquivalentCircuitModeling
• Knowledge-basedviaFuzzy-Clustering
• Signal-basedbymeansofANFISmodeling
*Furtherdetailson:www.d-code-jJ.eu
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Example of EIS-based diagnosis
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Model-based approach: Equivalent Circuit Modeling
DIAMOND – Mid-Term Workshop 13
*ItalianPatentApplica1on,No.RM2014A000641;Authors:PetroneR.,PolverinoP.,PianeseC.,Sorren1noM.;Title:MethodForMonitoringAndDiagnosingElectrochemicalDevicesBasedOnAutoma1cElectrochemicalImpedanceIden1fica1on.
0.1 0.15 0.2 0.25 0.3 0.35
0
0.05
0.1
0.15
Re(Z) [Ohm]
-Im(Z
) [O
hm]
Exp. DataFITGFG
25 A *
0.1 0.15 0.2 0.25 0.3-0.05
0
0.05
0.1
0.15
Re(Z) [Ohm]
-Im(Z
) [O
hm]
Exp. DataFITGFG
40 A *
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Diagnosis through ECM parameters
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0.1 0.2 0.3 0.40.1
0.15
0.2
0.25
Current density [A cm-2]
Membrane Resistance RΩ,eq [Ω cm2]
0.1 0.2 0.3 0.40.1
0.15
0.2
0.25
Current density [A cm-2]
Membrane Resistance RΩ,eq [Ω cm2]
λ < 14
λ > 14
NORMAL FAULTY
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On-line application example
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UNISA Diagnostic algorithm Interface
Residuals calculation for monitoring and classification
System variables and ECM
parameters plots
Spectrum plot Diagnostic result
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CONCLUSIONS
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Conclusions
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EISboardable to performon-line measurements for on-board systemmonitoring anddiagnos,cs, with accuracycomparable with convenJonallaboratorydevices.
Diagnos,c algorithms forrelevant faults detec,on andisola,on, oriented towardsinterac,on with controlstrategiesforsystemreliabilityandlifeJmeimprovement;0.1 0.2 0.3 0.4
0.1
0.15
0.2
0.25
Current density [A cm-2]
Membrane Resistance RΩ,eq [Ω cm2]
0.1 0.2 0.3 0.40.1
0.15
0.2
0.25
Current density [A cm-2]
Membrane Resistance RΩ,eq [Ω cm2]
λ < 14
λ > 14
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Thank you for your kind attention
Contacts www.eprolab.unisa.it
University of Salerno (Italy)
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