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System-Independent Irradiance Sensorless ANN-Based MPPT for Photovoltaic Systems in Electric Vehicles

Author

Listed:
  • Baldwin Cortés

    (Facultad de Ingeniería Eléctrica, Universidad Michocana de San Nicolás de Hidalgo, Morelia 58030, Mexico)

  • Roberto Tapia

    (Facultad de Ingeniería Eléctrica, Universidad Michocana de San Nicolás de Hidalgo, Morelia 58030, Mexico)

  • Juan J. Flores

    (Facultad de Ingeniería Eléctrica, Universidad Michocana de San Nicolás de Hidalgo, Morelia 58030, Mexico)

Abstract

The integration of photovoltaic systems (PVS) in electric vehicles (EV) increases the vehicle’s autonomy by providing an additional energy source other than the battery. However, current solar cell technology generates around 200 W for a 1.4 m 2 panel (to be installed on the roof of the EV) at stable irradiance conditions. This limitation in production and the sudden changes in irradiance produced by shadows of clouds, buildings, and other structures make developing a fast and efficient maximum power point tracking (MPPT) technique in this area necessary. This article proposes an artificial neural network (ANN)-based MPPT, called DS-ANN, that uses manufacturer datasheet parameters as inputs to the network to address this problem. The Bayesian backpropagation-regularization performs the training, ensuring that the MPPT technique operates satisfactorily on different PVS without retraining. We simulated the response of 20 commercial modules against actual irradiance data to validate the proposed method. The results show that our method achieves an average tracking efficiency of 99.66%, improving by 1.21% over an enhanced P&O method.

Suggested Citation

  • Baldwin Cortés & Roberto Tapia & Juan J. Flores, 2021. "System-Independent Irradiance Sensorless ANN-Based MPPT for Photovoltaic Systems in Electric Vehicles," Energies, MDPI, vol. 14(16), pages 1-18, August.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:4820-:d:610242
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    References listed on IDEAS

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    1. Wang, Dawei & Zamel, Nada & Jiao, Kui & Zhou, Yibo & Yu, Shuhai & Du, Qing & Yin, Yan, 2013. "Life cycle analysis of internal combustion engine, electric and fuel cell vehicles for China," Energy, Elsevier, vol. 59(C), pages 402-412.
    2. Bahrami, Milad & Gavagsaz-Ghoachani, Roghayeh & Zandi, Majid & Phattanasak, Matheepot & Maranzanaa, Gaël & Nahid-Mobarakeh, Babak & Pierfederici, Serge & Meibody-Tabar, Farid, 2019. "Hybrid maximum power point tracking algorithm with improved dynamic performance," Renewable Energy, Elsevier, vol. 130(C), pages 982-991.
    3. Peng, Lele & Zheng, Shubin & Chai, Xiaodong & Li, Liming, 2018. "A novel tangent error maximum power point tracking algorithm for photovoltaic system under fast multi-changing solar irradiances," Applied Energy, Elsevier, vol. 210(C), pages 303-316.
    4. Li, Xingshuo & Wen, Huiqing & Hu, Yihua & Jiang, Lin, 2019. "A novel beta parameter based fuzzy-logic controller for photovoltaic MPPT application," Renewable Energy, Elsevier, vol. 130(C), pages 416-427.
    5. Ahmed, Jubaer & Salam, Zainal, 2015. "An improved perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for higher efficiency," Applied Energy, Elsevier, vol. 150(C), pages 97-108.
    6. Chenni, R. & Makhlouf, M. & Kerbache, T. & Bouzid, A., 2007. "A detailed modeling method for photovoltaic cells," Energy, Elsevier, vol. 32(9), pages 1724-1730.
    7. Ahmad, Riaz & Murtaza, Ali F. & Sher, Hadeed Ahmed, 2019. "Power tracking techniques for efficient operation of photovoltaic array in solar applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 82-102.
    8. Ishaque, Kashif & Salam, Zainal & Lauss, George, 2014. "The performance of perturb and observe and incremental conductance maximum power point tracking method under dynamic weather conditions," Applied Energy, Elsevier, vol. 119(C), pages 228-236.
    9. Bendib, Boualem & Belmili, Hocine & Krim, Fateh, 2015. "A survey of the most used MPPT methods: Conventional and advanced algorithms applied for photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 637-648.
    10. Łukasz Kidziński & Scott Delp & Michael Schwartz, 2019. "Automatic real-time gait event detection in children using deep neural networks," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-11, January.
    11. Farhat, Maissa & Barambones, Oscar & Sbita, Lassaad, 2017. "A new maximum power point method based on a sliding mode approach for solar energy harvesting," Applied Energy, Elsevier, vol. 185(P2), pages 1185-1198.
    12. Karami, Nabil & Moubayed, Nazih & Outbib, Rachid, 2017. "General review and classification of different MPPT Techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 1-18.
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    Cited by:

    1. Ali M. Eltamaly & Zeyad A. Almutairi & Mohamed A. Abdelhamid, 2023. "Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV Systems," Energies, MDPI, vol. 16(13), pages 1-22, July.
    2. Bryam Paúl Lojano-Riera & Carlos Flores-Vázquez & Juan-Carlos Cobos-Torres & David Vallejo-Ramírez & Daniel Icaza, 2023. "Electromobility with Photovoltaic Generation in an Andean City," Energies, MDPI, vol. 16(15), pages 1-16, July.

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