IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v225y2024ics0960148124003768.html
   My bibliography  Save this article

Enhancing the performance of thermoelectric generators using novel segmental arrangement of multi-functional gradient materials

Author

Listed:
  • Harb, Abd El-Moneim A.
  • Elsayed, Khairy
  • Sedrak, Momtaz
  • Ahmed, Mahmoud
  • Abdo, Ahmed

Abstract

Enhancing the performance of thermoelectric generators at wide range of operating temperatures is of great importance to maximize the output power. Thus, different updated semiconductor materials with different values of figure of merit are used. Accordingly, a modified design of the TEG system based on the multi-functional gradient (MFG) technique is developed. A comprehensive three-dimensional modeling and optimization analysis was developed and numerically simulated. The numerical predicted results were validated using the available measurements and numerical data. The results showed that when compared to low operating temperature semiconductor material of traditional (Bi2Te3) at a hot side temperature equals 227 °C, the updated material improved the output power and efficiency by 18.8% and 58%, respectively. At high operating temperature at Th = 620 °C, the upgraded material outperformed the Silicon–germanium (SiGeT) traditional semiconductor material by about 71% in the output power and 100% in the efficiency. Using the MFG-TEG, the performance improvement over the conventional design at Tc = 27 °C, and Th of 477 °C was around 315% for output power and 503% for efficiency. The current findings introduce a brand-new, innovative technique that allows scientists to create thermoelectric generators that are incredibly efficient.

Suggested Citation

  • Harb, Abd El-Moneim A. & Elsayed, Khairy & Sedrak, Momtaz & Ahmed, Mahmoud & Abdo, Ahmed, 2024. "Enhancing the performance of thermoelectric generators using novel segmental arrangement of multi-functional gradient materials," Renewable Energy, Elsevier, vol. 225(C).
  • Handle: RePEc:eee:renene:v:225:y:2024:i:c:s0960148124003768
    DOI: 10.1016/j.renene.2024.120311
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124003768
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2024.120311?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Li, Siyang & Pei, Jun & Liu, Dawei & Bao, Liangliang & Li, Jing-Feng & Wu, Huaqiang & Li, Liangliang, 2016. "Fabrication and characterization of thermoelectric power generators with segmented legs synthesized by one-step spark plasma sintering," Energy, Elsevier, vol. 113(C), pages 35-43.
    2. Zhu, Lei & Li, Huaqi & Chen, Sen & Tian, Xiaoyan & Kang, Xiaoya & Jiang, Xinbiao & Qiu, Suizheng, 2020. "Optimization analysis of a segmented thermoelectric generator based on genetic algorithm," Renewable Energy, Elsevier, vol. 156(C), pages 710-718.
    3. Sun, Henan & Ge, Ya & Liu, Wei & Liu, Zhichun, 2019. "Geometric optimization of two-stage thermoelectric generator using genetic algorithms and thermodynamic analysis," Energy, Elsevier, vol. 171(C), pages 37-48.
    4. Yamashita, Osamu, 2009. "Effect of linear and non-linear components in the temperature dependences of thermoelectric properties on the cooling performance," Applied Energy, Elsevier, vol. 86(9), pages 1746-1756, September.
    5. Chen, Wei-Hsin & Wu, Po-Hua & Lin, Yu-Li, 2018. "Performance optimization of thermoelectric generators designed by multi-objective genetic algorithm," Applied Energy, Elsevier, vol. 209(C), pages 211-223.
    6. Ge, Ya & Lin, Yousheng & He, Qing & Wang, Wenhao & Chen, Jiechao & Huang, Si-Min, 2021. "Geometric optimization of segmented thermoelectric generators for waste heat recovery systems using genetic algorithm," Energy, Elsevier, vol. 233(C).
    7. Ouyang, Zhongliang & Li, Dawen, 2018. "Design of segmented high-performance thermoelectric generators with cost in consideration," Applied Energy, Elsevier, vol. 221(C), pages 112-121.
    8. Sahoo, Rashmi Rekha & Karana, Dhruv Raj, 2020. "Effect of design shape factor on exergonic performance of a new modified extended-tapering segmented thermoelectric generator system," Energy, Elsevier, vol. 200(C).
    9. Shu, Gequn & Zhao, Jian & Tian, Hua & Liang, Xingyu & Wei, Haiqiao, 2012. "Parametric and exergetic analysis of waste heat recovery system based on thermoelectric generator and organic rankine cycle utilizing R123," Energy, Elsevier, vol. 45(1), pages 806-816.
    10. Feng, Mengqi & Lv, Song & Deng, Jingcai & Guo, Ying & Wu, Yangyang & Shi, Guoqing & Zhang, Mingming, 2023. "An overview of environmental energy harvesting by thermoelectric generators," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    11. Siddique, Abu Raihan Mohammad & Mahmud, Shohel & Heyst, Bill Van, 2017. "A review of the state of the science on wearable thermoelectric power generators (TEGs) and their existing challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 730-744.
    12. Shen, Zu-Guo & Wu, Shuang-Ying & Xiao, Lan & Yin, Gang, 2016. "Theoretical modeling of thermoelectric generator with particular emphasis on the effect of side surface heat transfer," Energy, Elsevier, vol. 95(C), pages 367-379.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhu, Yuxiao & Newbrook, Daniel W. & Dai, Peng & de Groot, C.H. Kees & Huang, Ruomeng, 2022. "Artificial neural network enabled accurate geometrical design and optimisation of thermoelectric generator," Applied Energy, Elsevier, vol. 305(C).
    2. He, Zhi-Zhu, 2020. "A coupled electrical-thermal impedance matching model for design optimization of thermoelectric generator," Applied Energy, Elsevier, vol. 269(C).
    3. Alghamdi, Hisham & Maduabuchi, Chika & Okoli, Kingsley & Albaker, Abdullah & Makki, Emad & Alghassab, Mohammed & Alobaid, Mohammad & Alkhedher, Mohammad, 2023. "Pioneering sustainable power: Harnessing material innovations in double stage segmented thermoelectric generators for optimal 4E performance," Applied Energy, Elsevier, vol. 352(C).
    4. Shittu, Samson & Li, Guiqiang & Zhao, Xudong & Ma, Xiaoli, 2020. "Review of thermoelectric geometry and structure optimization for performance enhancement," Applied Energy, Elsevier, vol. 268(C).
    5. Ju, Chengjian & Dui, Guansuo & Zheng, Helen Hao & Xin, Libiao, 2017. "Revisiting the temperature dependence in material properties and performance of thermoelectric materials," Energy, Elsevier, vol. 124(C), pages 249-257.
    6. Chen, Wei-Hsin & Chiou, Yi-Bin, 2020. "Geometry design for maximizing output power of segmented skutterudite thermoelectric generator by evolutionary computation," Applied Energy, Elsevier, vol. 274(C).
    7. Maduabuchi, Chika & Eneh, Chibuoke & Alrobaian, Abdulrahman Abdullah & Alkhedher, Mohammad, 2023. "Deep neural networks for quick and precise geometry optimization of segmented thermoelectric generators," Energy, Elsevier, vol. 263(PC).
    8. Chen, Wei-Hsin & Wang, Chi-Ming & Lee, Da-Sheng & Kwon, Eilhann E. & Ashokkumar, Veeramuthu & Culaba, Alvin B., 2022. "Optimization design by evolutionary computation for minimizing thermal stress of a thermoelectric generator with varied numbers of square pin fins," Applied Energy, Elsevier, vol. 314(C).
    9. Ge, Ya & Lin, Yousheng & He, Qing & Wang, Wenhao & Chen, Jiechao & Huang, Si-Min, 2021. "Geometric optimization of segmented thermoelectric generators for waste heat recovery systems using genetic algorithm," Energy, Elsevier, vol. 233(C).
    10. Su, Shanhe & Liu, Tie & Wang, Junyi & Chen, Jincan, 2014. "Evaluation of temperature-dependent thermoelectric performances based on PbTe1−yIy and PbTe: Na/Ag2Te materials," Energy, Elsevier, vol. 70(C), pages 79-85.
    11. Yusuf, Aminu & Ballikaya, Sedat, 2022. "Electrical, thermomechanical and cost analyses of a low-cost thermoelectric generator," Energy, Elsevier, vol. 241(C).
    12. Shittu, Samson & Li, Guiqiang & Xuan, Qindong & Zhao, Xudong & Ma, Xiaoli & Cui, Yu, 2020. "Electrical and mechanical analysis of a segmented solar thermoelectric generator under non-uniform heat flux," Energy, Elsevier, vol. 199(C).
    13. Weng, Zebin & Liu, Furong & Zhu, Wenchao & Li, Yang & Xie, Changjun & Deng, Jian & Huang, Liang, 2022. "Performance improvement of variable-angle annular thermoelectric generators considering different boundary conditions," Applied Energy, Elsevier, vol. 306(PA).
    14. Lan, Yuncheng & Lu, Junhui & Li, Junming & Wang, Suilin, 2022. "Effects of temperature-dependent thermal properties and the side leg heat dissipation on the performance of the thermoelectric generator," Energy, Elsevier, vol. 243(C).
    15. Lan, Song & Li, Qingshan & Guo, Xin & Wang, Shukun & Chen, Rui, 2023. "Fuel saving potential analysis of bifunctional vehicular waste heat recovery system using thermoelectric generator and organic Rankine cycle," Energy, Elsevier, vol. 263(PB).
    16. Chen, Wei-Hsin & Lin, Yi-Xian & Wang, Xiao-Dong & Lin, Yu-Li, 2019. "A comprehensive analysis of the performance of thermoelectric generators with constant and variable properties," Applied Energy, Elsevier, vol. 241(C), pages 11-24.
    17. Liu, Shuang & Hu, Bingkun & Liu, Dawei & Li, Fu & Li, Jing-Feng & Li, Bo & Li, Liangliang & Lin, Yuan-Hua & Nan, Ce-Wen, 2018. "Micro-thermoelectric generators based on through glass pillars with high output voltage enabled by large temperature difference," Applied Energy, Elsevier, vol. 225(C), pages 600-610.
    18. Ge, Ya & He, Kui & Xiao, Liehui & Yuan, Wuzhi & Huang, Si-Min, 2022. "Geometric optimization for the thermoelectric generator with variable cross-section legs by coupling finite element method and optimization algorithm," Renewable Energy, Elsevier, vol. 183(C), pages 294-303.
    19. Yang, Huizhu & Li, Mingxuan & Wang, Zehui & Ren, Fengsheng & Yang, Yue & Ma, Bijian & Zhu, Yonggang, 2023. "Performance optimization for a novel two-stage thermoelectric generator with different PCMs embedding modes," Energy, Elsevier, vol. 281(C).
    20. Song Lv & Zuoqin Qian & Dengyun Hu & Xiaoyuan Li & Wei He, 2020. "A Comprehensive Review of Strategies and Approaches for Enhancing the Performance of Thermoelectric Module," Energies, MDPI, vol. 13(12), pages 1-24, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:225:y:2024:i:c:s0960148124003768. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.