Non-destructive parameter extraction for a reduced order lumped electrochemical-thermal model for simulating Li-ion full-cells
Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Syst...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ng, Benjamin [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Numerical modeling of wave–current forces acting on horizontal cylinder of marine structures by VOF method - Xiao, Hong ELSEVIER, 2013, the international journal on the science and technology of electrochemical energy systems, New York, NY [u.a.] |
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| Übergeordnetes Werk: |
volume:445 ; year:2020 ; day:1 ; month:01 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.jpowsour.2019.227296 |
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ELV048685275 |
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| 245 | 1 | 0 | |a Non-destructive parameter extraction for a reduced order lumped electrochemical-thermal model for simulating Li-ion full-cells |
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| 520 | |a Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). | ||
| 520 | |a Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). | ||
| 650 | 7 | |a Experimental validation |2 Elsevier | |
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| 650 | 7 | |a NMC532 |2 Elsevier | |
| 650 | 7 | |a Lumped model |2 Elsevier | |
| 700 | 1 | |a Coman, Paul T. |4 oth | |
| 700 | 1 | |a Mustain, William E. |4 oth | |
| 700 | 1 | |a White, Ralph E. |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier |a Xiao, Hong ELSEVIER |t Numerical modeling of wave–current forces acting on horizontal cylinder of marine structures by VOF method |d 2013 |d the international journal on the science and technology of electrochemical energy systems |g New York, NY [u.a.] |w (DE-627)ELV00098745X |
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10.1016/j.jpowsour.2019.227296 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000830.pica (DE-627)ELV048685275 (ELSEVIER)S0378-7753(19)31289-3 DE-627 ger DE-627 rakwb eng 690 VZ 50.92 bkl Ng, Benjamin verfasserin aut Non-destructive parameter extraction for a reduced order lumped electrochemical-thermal model for simulating Li-ion full-cells 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). Experimental validation Elsevier GITT Elsevier Full-cell Elsevier NMC532 Elsevier Lumped model Elsevier Coman, Paul T. oth Mustain, William E. oth White, Ralph E. oth Enthalten in Elsevier Xiao, Hong ELSEVIER Numerical modeling of wave–current forces acting on horizontal cylinder of marine structures by VOF method 2013 the international journal on the science and technology of electrochemical energy systems New York, NY [u.a.] (DE-627)ELV00098745X volume:445 year:2020 day:1 month:01 pages:0 https://doi.org/10.1016/j.jpowsour.2019.227296 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 50.92 Meerestechnik VZ AR 445 2020 1 0101 0 |
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10.1016/j.jpowsour.2019.227296 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000830.pica (DE-627)ELV048685275 (ELSEVIER)S0378-7753(19)31289-3 DE-627 ger DE-627 rakwb eng 690 VZ 50.92 bkl Ng, Benjamin verfasserin aut Non-destructive parameter extraction for a reduced order lumped electrochemical-thermal model for simulating Li-ion full-cells 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). Experimental validation Elsevier GITT Elsevier Full-cell Elsevier NMC532 Elsevier Lumped model Elsevier Coman, Paul T. oth Mustain, William E. oth White, Ralph E. oth Enthalten in Elsevier Xiao, Hong ELSEVIER Numerical modeling of wave–current forces acting on horizontal cylinder of marine structures by VOF method 2013 the international journal on the science and technology of electrochemical energy systems New York, NY [u.a.] (DE-627)ELV00098745X volume:445 year:2020 day:1 month:01 pages:0 https://doi.org/10.1016/j.jpowsour.2019.227296 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 50.92 Meerestechnik VZ AR 445 2020 1 0101 0 |
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10.1016/j.jpowsour.2019.227296 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000830.pica (DE-627)ELV048685275 (ELSEVIER)S0378-7753(19)31289-3 DE-627 ger DE-627 rakwb eng 690 VZ 50.92 bkl Ng, Benjamin verfasserin aut Non-destructive parameter extraction for a reduced order lumped electrochemical-thermal model for simulating Li-ion full-cells 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). Experimental validation Elsevier GITT Elsevier Full-cell Elsevier NMC532 Elsevier Lumped model Elsevier Coman, Paul T. oth Mustain, William E. oth White, Ralph E. oth Enthalten in Elsevier Xiao, Hong ELSEVIER Numerical modeling of wave–current forces acting on horizontal cylinder of marine structures by VOF method 2013 the international journal on the science and technology of electrochemical energy systems New York, NY [u.a.] (DE-627)ELV00098745X volume:445 year:2020 day:1 month:01 pages:0 https://doi.org/10.1016/j.jpowsour.2019.227296 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 50.92 Meerestechnik VZ AR 445 2020 1 0101 0 |
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10.1016/j.jpowsour.2019.227296 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000830.pica (DE-627)ELV048685275 (ELSEVIER)S0378-7753(19)31289-3 DE-627 ger DE-627 rakwb eng 690 VZ 50.92 bkl Ng, Benjamin verfasserin aut Non-destructive parameter extraction for a reduced order lumped electrochemical-thermal model for simulating Li-ion full-cells 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). Experimental validation Elsevier GITT Elsevier Full-cell Elsevier NMC532 Elsevier Lumped model Elsevier Coman, Paul T. oth Mustain, William E. oth White, Ralph E. oth Enthalten in Elsevier Xiao, Hong ELSEVIER Numerical modeling of wave–current forces acting on horizontal cylinder of marine structures by VOF method 2013 the international journal on the science and technology of electrochemical energy systems New York, NY [u.a.] (DE-627)ELV00098745X volume:445 year:2020 day:1 month:01 pages:0 https://doi.org/10.1016/j.jpowsour.2019.227296 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 50.92 Meerestechnik VZ AR 445 2020 1 0101 0 |
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10.1016/j.jpowsour.2019.227296 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000830.pica (DE-627)ELV048685275 (ELSEVIER)S0378-7753(19)31289-3 DE-627 ger DE-627 rakwb eng 690 VZ 50.92 bkl Ng, Benjamin verfasserin aut Non-destructive parameter extraction for a reduced order lumped electrochemical-thermal model for simulating Li-ion full-cells 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). Experimental validation Elsevier GITT Elsevier Full-cell Elsevier NMC532 Elsevier Lumped model Elsevier Coman, Paul T. oth Mustain, William E. oth White, Ralph E. oth Enthalten in Elsevier Xiao, Hong ELSEVIER Numerical modeling of wave–current forces acting on horizontal cylinder of marine structures by VOF method 2013 the international journal on the science and technology of electrochemical energy systems New York, NY [u.a.] (DE-627)ELV00098745X volume:445 year:2020 day:1 month:01 pages:0 https://doi.org/10.1016/j.jpowsour.2019.227296 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 50.92 Meerestechnik VZ AR 445 2020 1 0101 0 |
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Enthalten in Numerical modeling of wave–current forces acting on horizontal cylinder of marine structures by VOF method New York, NY [u.a.] volume:445 year:2020 day:1 month:01 pages:0 |
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non-destructive parameter extraction for a reduced order lumped electrochemical-thermal model for simulating li-ion full-cells |
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Non-destructive parameter extraction for a reduced order lumped electrochemical-thermal model for simulating Li-ion full-cells |
| abstract |
Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). |
| abstractGer |
Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). |
| abstract_unstemmed |
Rapid voltage and temperature estimations with a Reduced Order Lumped Electrochemical-Thermal Model (TLM) was developed by applying a State Space Approach to transform partial differential equations (PDEs) into ordinary differential equations (ODEs). The TLM is attractive for Battery Management Systems (BMS) because of model restrictions that result in only four parameters: exchange current (i0S), diffusion time constant (τ), internal resistance (RIR), and the entropic heat coefficient (dUdT−1). The State Space approach is shown to be an effective method for reducing the computational time for the model by greater than 50% (~2s to less than 1s). This study also shows that the required model parameters (i0S, τ, RIR, dUdT−1) can be nondestructively extracted from real cells using the galvanostatic intermittent titration technique (GITT). This allows us to create cell-level temperature and state of charge (SOC) parameter surfaces that would be nearly impossible to develop experimentally. By confirming the extracted parameters with the model predicted parameters, future BMS models can further reduce computational time (approach millisecond predictions) by experimentally constraining the model. This means that the methodology reported in this paper can be ubiquitously implemented for other battery chemistries (e.g. cathodes, anodes), formats (e.g. 18650, pouch, prismatic), and properties (e.g. capacity ratios). |
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Non-destructive parameter extraction for a reduced order lumped electrochemical-thermal model for simulating Li-ion full-cells |
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