Skip to main content

Finite Volume Method Used for Numerical Investigations of Electrochemical Devices

  • Chapter
  • First Online:
Numerical Methods for Energy Applications

Part of the book series: Power Systems ((POWSYS))

Abstract

The chapter provides a general overview on the Finite Volume Method (FVM) and on Computational Fluid Dynamic (CFD). It introduces the FVM by using a general scalar transport equation and it describes the main steps of a CFD investigation. All these are applied to the mass, momentum, species, energy and potential conservation equations, equations that govern the operation of Proton Exchange Membrane (PEM) fuel cells. The importance of spatial discretization and of interpolation schemes used in CFD investigations is point out by analysing few parameters with impact on the fuel cell operation. Two cases have been considered. First case based on a fuel cell with a simplified configuration, namely a single serpentine channel, revealed the influence of spatial discretization on the accuracy of the simulation results with regards to current density, pressure and temperature. The second case based on a lab-scale fuel cell with two configurations for channels (7 serpentine and 7 parallel) have been used to analyse the effect of three interpolation schemes (first order, second order, QUICK) on the PEM fuel cell operation; therefore, pressure, hydrogen and water mass fraction profiles were considered for comparison. It was found out that besides the differences in the results accuracy due to spatial discretization and interpolation schemes, the design/geometry used in the CFD investigation may or may not emphasize these differences. If for the 7-serpentine channels fuel cell the interpolation scheme did not show much changes in the accuracy of the results not the same conclusion was drawn for the 7-parallel channels fuel cell where the accuracy of the results improved with increasing the order of the interpolation scheme. A mesh-independent solution on a well-posed problem will provide valuable and accurate results only if the numerical methods are appropriate and the interpolation schemes are of high order. The modeling of fuel cells using CFD techniques, as of any other device, can be an important alternative to the experiment, providing information that is critical to design, operation and optimization, the requirement being to use appropriate model, assumptions and boundary conditions and, of course, an adequate numerical method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

\(c\) :

Concentration, mol/m3

\(D\) :

Diffusivity, m2/s

\(F\) :

Faraday’s constant, C/mol

\(i\) :

Current, A

\(j\) :

Current, density, A/m2

\(j_{0}^{ref}\) :

Reference current density, A/m2

\(k\) :

Thermal conductivity, W/(m K)

\(K\) :

Absolute permeability, m2

\(M\) :

Molecular weight, g/mol

\(R\) :

Universal gas constant, J/(mol K)

\(S\) :

Source term

\(p\) :

Pressure, Pa

\(T\) :

Temperature, K

\(Y\) :

Mass fraction

\(v\) :

Velocity, m/s

\(V_{OC}\) :

Open circuit voltage, V

\(\alpha\) :

Charge transfer coefficient

\(\varepsilon\) :

Porosity

\(\zeta\) :

Specific active surface area, 1/m

\(\eta\) :

Overpotential, V

\(\mu\) :

Dynamic viscosity, Pa s

\(\varphi\) :

Potential, V

\(\rho\) :

Density, kg/m3

\(\sigma_{sol/mem}\) :

Electric/membrane conductivity, S/m

a :

Anode

c :

Cathode

sol :

Solid

mem :

Membrane

References

  1. Barbir F (2012) PEM fuel cell: theory and practice, 2nd edn. Elsevier Academic Press, Amsterdam, Boston. ISBN: 9780123877109. https://doi.org/10.1016/B978-0-12-078142-3.X5000-9

  2. Berning T, Djilali N (2003) A 3D, multiphase, multicomponent model of the cathode and anode of a PEM fuel cell. J Electrochem Soc 150:A1589–A1598

    Article  Google Scholar 

  3. Springer TE, Zawodzinski TA, Gottesfeld S (1991) Polymer electrolyte fuel cell model. J Electrochem Soc 138:2334–2342

    Article  Google Scholar 

  4. Gurau V, Barbir F, Liu H (2000) An analytical solution of a half-cell model for PEM fuel cells. J Electrochem Soc 147(7):2468–2477. https://doi.org/10.1149/1.1393555

    Article  Google Scholar 

  5. Chevalier S, Josset C, Auvity B (2018) Analytical solutions and dimensional analysis of pseudo 2D current density distribution model in PEM fuel cells. Renew Energy 125:738–746. https://doi.org/10.1016/j.renene.2018.02.120

    Article  Google Scholar 

  6. Kulikovsky AA (2017) Approximate analytical solution to MHM equations for PEM fuel cell cathode performance. Electrochem Comm 77:36–39. https://doi.org/10.1016/j.elecom.2017.09.018

    Article  Google Scholar 

  7. Um S, Wang CY, Chen KS (2000) Computational fluid dynamics modeling of proton exchange membrane fuel cells. J Electrochem Soc 147(12):4485–4493

    Article  Google Scholar 

  8. Blazek J (2015) Computational fluid dynamics: principles and applications, 3rd edn. Butterworth-Heinemann Imprint, pp 73–120. ISBN 978–0–08–099995–1. https://doi.org/10.1016/C2013-0-19038-1

  9. Ma L, Ingham DB, Pourkashanian MC (2005) Application of fluid flows through porous media in fuel cells. In: Transport phenomena in porous media III, 1st edn. Elsevier Science, pp 418–440. https://doi.org/10.1016/B978-0-08-044490-1.X5003-0

  10. Heister T, Rebholz LG, Xue F (2019) Numerical analysis—an introduction. De Gruyter Textbook, pp 121–140. ISBN 978-3-11-057330-5

    Google Scholar 

  11. Walter E (2014) Numerical methods and optimization. Springer International Publishing, pp 17–57. ISBN 978-3-319-07670-6. https://doi.org/10.1007/978-3-319-07671-3

  12. Moukalled F, Mangani L, Darwish M (2016) The finite volume method. In: Computational fluid dynamics, an advanced introduction with OpenFOAM® and Matlab®. Fluid mechanics and its applications, vol 113. Springer International Publishing, pp 103–135. ISSN 0926-5112. https://doi.org/10.1007/978-3-319-16874-6

  13. Versteeg HK, Malalasekera W (1995) Computational fluid dynamics (CFD) is the application of algorithm and numerical techniques to solve fluid flow problems. Wiley, pp 85–204 ISBN 0-582-21884-5

    Google Scholar 

  14. Barth T, Ohlberger M (2004) Finite volume methods: foundation and analysis. In: Stein E, de Borst R, Hughes TJR (eds) Encyclopedia of computational mechanics. Part 1 fluids. Wiley. https://doi.org/10.1002/9781119176817.ecm2010

  15. Marinoiu A, Cobzaru C, Carcadea E et al (2015) An experimental approach for finding low cost alternative support material in PEM fuel cells. Rev Roum Chim 61:433–440

    Google Scholar 

  16. Bizon N (2019) Sensitivity analysis of the fuel economy strategy based on load-following control of the fuel cell hybrid power system. Energy Convers Manag 199:111946. https://doi.org/10.1016/j.enconman.2019.111946

    Article  Google Scholar 

  17. Karimi G, Baschuk JJ, Li X (2005) Performance analysis and optimization of PEM fuel cell stacks using flow network approach. J Power Sources 147(1–2):162–177. https://doi.org/10.1016/j.jpowsour.2005.01.023

    Article  Google Scholar 

  18. Russel J, Cohn R (2012) Gaussian elimination. ISBN 9-785510890709

    Google Scholar 

  19. Mittal RC, Al-Kurdi A (2002) LU-decomposition and numerical structure for solving large sparse nonsymmetric linear systems. Comput Math Appl 43(1–2):131–155. https://doi.org/10.1016/S0898-1221(01)00279-6

    Article  MathSciNet  MATH  Google Scholar 

  20. Mazumder S (2016) Numerical methods for partial differential equations. In: Finite difference and finite volume methods, pp 1–49. ISBN 978-0-12-849894-1

    Google Scholar 

  21. Ferziger JH, Peric M (1997) Computational Methods for Fluid Dynamics, Springer-Verlag Berlin Heidelberg, pp 21–37, 71–89, doi: https://doi.org/10.1007/978-3-642-56026-2

  22. Anderson J (1995) Computational fluid dynamics—the basics with applications. McGraw-Hill, pp 216–278. ISBN 0-07–001685-2

    Google Scholar 

  23. Zawawi MH, Saleha A, Salwa A et al (2018) A review: fundamentals of computational fluid dynamics (CFD). AIP Conf Proc 2030:020252. https://doi.org/10.1063/1.5066893

    Article  Google Scholar 

  24. Carcadea E, Varlam M, Marinoiu A et al (2019) Influence of catalyst structure on PEM fuel cell performance—a numerical investigation. Int J Hydrogen Energy 44:12829–12841. https://doi.org/10.1016/j.ijhydene.2018.12.155

    Article  Google Scholar 

  25. Carcadea E, Varlam M, Ismail M et al (2019) PEM fuel cell performance improvement through numerical optimization of the parameters of the porous layers. Int J Hydrogen Energy 45(14):7968–7980

    Article  Google Scholar 

  26. Tu J, Yeoh GH, Liu C (2019) Computational fluid dynamics—a practical approach. Elsevier Ltd. ISBN 978-0-08-101127-0. https://doi.org/10.1016/C2015-0-06135-4

  27. Barbir F. PEM fuel cells. In: Sammes N (ed) Fuel cell technology: reaching towards commercialization. Springer International Publishing, pp 27–51. ISBN: 978-1-84628–207-2. https://doi.org/10.1007/1-84628-207-1

  28. OpenFoam Software. https://openfoam.org/

  29. HELYX Sotware. https://engys.com/products/helyx

  30. ANSYS. Multiphysics help. www.ansys.com

  31. COMSOL Multiphysics. https://www.comsol.com/cfd-module

  32. Inoue G, Matsukuma Y, Minemoto M (2006) Effect of gas channel depth on current density distribution of polymer electrolyte fuel cell by numerical analysis including gas flow through gas diffusion layer. J Power Sources 157:36–152

    Google Scholar 

  33. Carcadea E, Ingham DB, Stefanescu I et al (2011) The influence of permeability changes for a 7-serpentine channel PEM fuel cell performance. Int J Hydrogen Energy 36:10376–10383

    Article  Google Scholar 

  34. Ismail MS, Hughes KJ, Ingham DB et al (2013) Effect of PTFE loading of gas diffusion layers on the performance of proton exchange membrane fuel cells running at high-efficiency operating conditions. Int J Energy Res 37:1592–1599

    Article  Google Scholar 

  35. Jang WK, Choi J, Seo YH et al (2015) Effect of cathode flow field configuration on air-breathing proton exchange membrane fuel cell. Int J Precis Eng Man 16:1129–1134

    Article  Google Scholar 

  36. Khakaz-Baboli M, Harvey DA, Pharoah JG (2013) Investigating the performance of catalyst layer micro-structure with different platinum loadings. ECS Trans 50(2):765–772

    Article  Google Scholar 

  37. Raceanu M, Marinoiu A, Culcer M et al (2014) Preventing reactant starvation of a 5 kW PEM fuel cell stack during sudden load change. In: Proceedings of 6th international conference on electronics, computers and artificial intelligence, pp 55–60. https://doi.org/10.1109/ECAI.2014.7090147

  38. Sanchez DG, Ruiu T, Friedrich KA et al (2016) Analysis of the influence of temperature and gas humidity on the performance stability of polymer electrolyte membrane fuel cells. J Electrochem Soc 163:F150–F159

    Article  Google Scholar 

  39. Obut S, Alper E (2011) Numerical assessment of dependence of polymer electrolyte membrane fuel cell performance on cathode catalyst layer parameters. J Power Sources 196:1920–1931

    Article  Google Scholar 

  40. Antunes RA, de Oliveira MCL, Ett G et al (2011) Carbon materials in composite bipolar plates for polymer electrolyte membrane fuel cells: a review of the main challenges to improve electrical performance. J Power Sources 196(6):2945–2961

    Article  Google Scholar 

  41. Carcadea E, Varlam M, Stefanescu I et al (2014) (2014) Effects of flow fields on PEM fuel cell performance. Prog Cryog Isot Sep 17:81–88

    Google Scholar 

  42. Guilin HU, Xu Y, Zhang Z (2014) Numerical simulation of heat/mass transfer in a single proton exchange membrane fuel cell with serpentine fluid channels. Int J Electrochem Sci 9:1902–1910

    Google Scholar 

  43. Yuan XZR, Song C, Wang H et al (2010) PEM fuel cells and their related electrochemical fundamentals. In: Electrochemical impedance spectroscopy in PEM fuel cells. Springer, London, pp 1–37. https://doi.org/10.1007/978-1-84882-846-9_1

  44. Kazemi Esfeh H, Azarafza A, Hamis MKA (2017) On the computational fluid dynamics of PEM fuel cells (PEMFCs): an investigation on mesh independence analysis. RSC Adv 7:32893–32902

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by a grant of the Romanian Ministry of Research and Innovation, CCCDI - UEFISCDI, project number PN-III-P1-1.2-PCCDI-2017-0194/25 PCCDI within PNCDI III and contract 117/2016, RESTORE project.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Elena Carcadea .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Carcadea, E., Varlam, M. (2021). Finite Volume Method Used for Numerical Investigations of Electrochemical Devices. In: Mahdavi Tabatabaei, N., Bizon, N. (eds) Numerical Methods for Energy Applications. Power Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-62191-9_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-62191-9_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62190-2

  • Online ISBN: 978-3-030-62191-9

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics