Entropy coefficient and thermal time constant estimation from dynamic thermal cycling of a cylindrical LiFePO4 battery cell

Sergio Mendoza, Hosam Kadry Fathy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a method for estimating (i) the reciprocal of the thermal time constant of a lithium-ion battery cell and (ii) the cell's entropy coefficients for different states of charge. The method utilizes dynamic battery temperature cycling for parameter estimation. The paper demonstrates this method specifically for a cylindrical lithium iron phosphate (LiFePO4) cell. Identifying battery thermal parameters is important for accurate thermo-electrochemical modeling and model-based battery management. Entropy coefficients have been identified in previous research for various battery chemistries using calorimetric and potentiometric measurements requiring quasi-equilibrium conditions. This work, in contrast, fits the entropy coefficients and the reciprocal of the thermal time constant of a first-order thermal model to datasets collected in a noninvasive, dynamic experiment. This reduces the time required for parameter identification by a factor of 3 compared to traditional quasi-equilibrium experiments.

Original languageEnglish (US)
Title of host publicationDynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing
PublisherAmerican Society of Mechanical Engineers
Volume2
ISBN (Electronic)9780791846193
DOIs
StatePublished - Jan 1 2014
EventASME 2014 Dynamic Systems and Control Conference, DSCC 2014 - San Antonio, United States
Duration: Oct 22 2014Oct 24 2014

Other

OtherASME 2014 Dynamic Systems and Control Conference, DSCC 2014
CountryUnited States
CitySan Antonio
Period10/22/1410/24/14

Fingerprint

Thermal cycling
Entropy
Parameter estimation
Identification (control systems)
Phosphates
Lithium
Experiments
Iron
Hot Temperature
Temperature

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

Cite this

Mendoza, S., & Fathy, H. K. (2014). Entropy coefficient and thermal time constant estimation from dynamic thermal cycling of a cylindrical LiFePO4 battery cell. In Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing (Vol. 2). [6176] American Society of Mechanical Engineers. https://doi.org/10.1115/DSCC2014-6176
Mendoza, Sergio ; Fathy, Hosam Kadry. / Entropy coefficient and thermal time constant estimation from dynamic thermal cycling of a cylindrical LiFePO4 battery cell. Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing. Vol. 2 American Society of Mechanical Engineers, 2014.
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Mendoza, S & Fathy, HK 2014, Entropy coefficient and thermal time constant estimation from dynamic thermal cycling of a cylindrical LiFePO4 battery cell. in Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing. vol. 2, 6176, American Society of Mechanical Engineers, ASME 2014 Dynamic Systems and Control Conference, DSCC 2014, San Antonio, United States, 10/22/14. https://doi.org/10.1115/DSCC2014-6176

Entropy coefficient and thermal time constant estimation from dynamic thermal cycling of a cylindrical LiFePO4 battery cell. / Mendoza, Sergio; Fathy, Hosam Kadry.

Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing. Vol. 2 American Society of Mechanical Engineers, 2014. 6176.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - This paper presents a method for estimating (i) the reciprocal of the thermal time constant of a lithium-ion battery cell and (ii) the cell's entropy coefficients for different states of charge. The method utilizes dynamic battery temperature cycling for parameter estimation. The paper demonstrates this method specifically for a cylindrical lithium iron phosphate (LiFePO4) cell. Identifying battery thermal parameters is important for accurate thermo-electrochemical modeling and model-based battery management. Entropy coefficients have been identified in previous research for various battery chemistries using calorimetric and potentiometric measurements requiring quasi-equilibrium conditions. This work, in contrast, fits the entropy coefficients and the reciprocal of the thermal time constant of a first-order thermal model to datasets collected in a noninvasive, dynamic experiment. This reduces the time required for parameter identification by a factor of 3 compared to traditional quasi-equilibrium experiments.

AB - This paper presents a method for estimating (i) the reciprocal of the thermal time constant of a lithium-ion battery cell and (ii) the cell's entropy coefficients for different states of charge. The method utilizes dynamic battery temperature cycling for parameter estimation. The paper demonstrates this method specifically for a cylindrical lithium iron phosphate (LiFePO4) cell. Identifying battery thermal parameters is important for accurate thermo-electrochemical modeling and model-based battery management. Entropy coefficients have been identified in previous research for various battery chemistries using calorimetric and potentiometric measurements requiring quasi-equilibrium conditions. This work, in contrast, fits the entropy coefficients and the reciprocal of the thermal time constant of a first-order thermal model to datasets collected in a noninvasive, dynamic experiment. This reduces the time required for parameter identification by a factor of 3 compared to traditional quasi-equilibrium experiments.

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Mendoza S, Fathy HK. Entropy coefficient and thermal time constant estimation from dynamic thermal cycling of a cylindrical LiFePO4 battery cell. In Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing. Vol. 2. American Society of Mechanical Engineers. 2014. 6176 https://doi.org/10.1115/DSCC2014-6176