A density-based topology optimization methodology for thermoelectric energy conversion problems

RESEARCH PAPER
  • 33 Downloads

Abstract

A density-based topology optimization approach for thermoelectric (TE) energy conversion problems is proposed. The approach concerns the optimization of thermoelectric generators (TEGs) and thermoelectric coolers (TECs). The framework supports convective heat transfer boundary conditions, temperature dependent material parameters and relevant objective functions. Comprehensive implementation details of the methodology are provided, and seven different design problems are solved and discussed to demonstrate that the approach is well-suited for optimizing TEGs and TECs. The study reveals new insight in TE energy conversion, and the study provides guidance for future research, which pursuits the development of high performing and industrially profitable TEGs and TECs.

Keywords

Topology optimization Thermoelectric energy conversion Electric power output Conversion efficiency Thermoelectricity Renewable energy Thermoelectric cooling Thermoelectric coolers 

Notes

Acknowledgements

The authors acknowledge the financial support received from the TopTen project sponsored by the Danish Council for Independent Research (DFF-4005-00320).

References

  1. Angst S (2016) Complex dynamics and performance of inhomogeneous thermoelectrics. PhD thesis, Von der Fakultt fr Physik der Universitt Duisburg-EssenGoogle Scholar
  2. Antonova E E, Looman D C (2000) Finite elements for thermoelectric device analysis in ANSYS. In: International conference on thermoelectrics, pp 1–4Google Scholar
  3. Bendsøe M, Sigmund O (2003) Topology optimization - theory methods and applications. Springer, BerlinMATHGoogle Scholar
  4. Bendsøe MP, Kikuchi N (1988) Generating optimal topologies in structural design using a homogenization method. Comput Methods Appl Mech Eng 71(2):197–224MathSciNetCrossRefMATHGoogle Scholar
  5. Champier D (2017) Thermoelectric generators: a review of present and future applications. Springer International Publishing, Cham, pp 203–212Google Scholar
  6. Cook R D, Malkus D S, Plesha M E, Witt R J (2007) Concepts and applications of finite element analysis, 4th edn. Wiley, New YorkGoogle Scholar
  7. Deuflhard P (2014) Newton methods for nonlinear problems. Springer, BerlinMATHGoogle Scholar
  8. Goldsmid H J (2009) Introduction to thermoelectricity, vol 121. Springer Science & Business Media, BerlinGoogle Scholar
  9. Heghmanns A, Beitelschmidt M (2015) Parameter optimization of thermoelectric modules using a genetic algorithm. Appl Energy 155:447–454CrossRefGoogle Scholar
  10. Rowe D M (2005) Thermoelectrics handbook: macro to nano. CRC Press, Boca RatonCrossRefGoogle Scholar
  11. Sakai A, Kanno T, Takahashi K, Tamaki H, Kusada H, Yamada Y, Abe H (2014) Breaking the trade-off between thermal and electrical conductivities in the thermoelectric material of an artificially tilted multilayer. Sci Rep 4:6089CrossRefGoogle Scholar
  12. Sigmund O (1998) Systematic design of electrothermomechanical microactuators using topology optimization. In: Modelling and simulation of microsystems, semiconductors, sensors and actuators, pp 1492–1500Google Scholar
  13. Sigmund O (2009) Manufacturing tolerant topology optimization. Acta Mechanica Sinica/Lixue Xuebao 25 (2):227–239CrossRefMATHGoogle Scholar
  14. Sigmund O (2011) On the usefulness of non-gradient approaches in topology optimization. Struct Multidiscip Optim 43(5):589–596MathSciNetCrossRefMATHGoogle Scholar
  15. Sigmund O, Maute K (2013) Topology optimization approaches. Struct Multidiscip Optim 48(6):1031–1055MathSciNetCrossRefGoogle Scholar
  16. Svanberg K (1987) The method of moving asymptotes—a new method for structural optimization. Int J Numer Methods Eng 24(2):359–373MathSciNetCrossRefMATHGoogle Scholar
  17. Takezawa A, Kitamura M (2012) Geometrical design of thermoelectric generators based ontopology optimization. Int J Numer Methods Eng 90:1885–1891CrossRefMATHGoogle Scholar
  18. Tian Z, Lee S, Chen G (2014) A comprehensive review of heat transfer in thermoelectric materials and devices. Ann Rev Heat Transfer 17:425–483CrossRefGoogle Scholar
  19. Tritt T M, Ma Subramanian (2006) Thermoelectric materials, phenomena, and applications: a bird’s eye view. MRS Bull 31(March):188–198CrossRefGoogle Scholar
  20. Ursell T S, Snyder G J (2002) Compatibility of segmented thermoelectric generators. In: Twenty-first international conference on thermoelectrics, 2002. Proceedings ICT’02. IEEE, pp 412–417Google Scholar
  21. Vining C B (2009) An inconvenient truth about thermoelectrics. Nat Mater 8(2):83–85CrossRefGoogle Scholar
  22. Wang F, Lazarov B S, Sigmund O (2011) On projection methods, convergence and robust formulations in topology optimization. Struct Multidiscip Optim 43(6):767–784CrossRefMATHGoogle Scholar
  23. Yamashita O, Tomiyoshi S, Makita K (2003) Bismuth telluride compounds with high thermoelectric figures of merit. J Appl Phys 93(1):368–374CrossRefGoogle Scholar
  24. Yang Y, Xie S H, Ma F, Lei C H (2012) On the effective thermoelectric properties of layered heterogeneous medium. J Appl Phys 111(1):3510Google Scholar
  25. Yang Y, Ma F, Lei C H, YY L, Li J (2013) Is thermoelectric conversion efficiency of a composite bounded by its constituents? Appl Phys Lett 102(5):53905CrossRefGoogle Scholar
  26. Yushanov S, Gritter L, Crompton J, Koppenhoefer K (2011) Multiphysics analysis of thermoelectric phenomena. In: Seventh annual conference on multiphysics modeling and simulation, proceedings of the 2011 COMSOL conference, Boston, USAGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringTechinical University of DenmarkKgs. LyngbyDenmark

Personalised recommendations