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Hengsheng SHAN, Chengke LI, Xiaoya LI, et al., “Model Parameter Extraction for InGaN/GaN Multiple Quantum Well-based Solar Cells using Dynamic Programming,” Chinese Journal of Electronics, vol. x, no. x, pp. 1–10, xxxx doi: 10.23919/cje.2023.00.337
Citation: Hengsheng SHAN, Chengke LI, Xiaoya LI, et al., “Model Parameter Extraction for InGaN/GaN Multiple Quantum Well-based Solar Cells using Dynamic Programming,” Chinese Journal of Electronics, vol. x, no. x, pp. 1–10, xxxx doi: 10.23919/cje.2023.00.337

Model Parameter Extraction for InGaN/GaN Multiple Quantum Well-based Solar Cells using Dynamic Programming

doi: 10.23919/cje.2023.00.337
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  • Author Bio:

    Hengsheng SHAN was born in 1984. He received the Ph.D. degree in Xidian University. He is now a lecturer with School of Physical and Information Sciences, Shaanxi University of Science and Technology, Xi’an, China. His interests include InGaN solar cell design and manufacture, antiradiation strengthening technology of InGaN solar cell, and wireless power transmission. (Email: hsshan@sust.edu.cn)

    Chengke LI was born in 1998. He is now pursuing the Master’s degree in Shaanxi University of Science and Technology, Xi’an, China. His interests include InGaN solar cell design and manufacture, antiradiation strengthening technology of InGaN solar cell, and wireless power transmission. (Email: 838340262@qq.com)

    Xiaoya LI was born in 1988. She received the Ph.D. degree in Xidian University. She is now a lecturer with School of Information Science and Technology, Northwest University. Her research interests focus on InGaN solar cell performance analysis and device simulation, millimeter wave transmission, and wireless power transmission. (Email: xyli@nwu.edu.cn)

    Minghui LI was born in 1999. She is now pursuing the Master’s degree in Shaanxi University of Science and Technology, Xi’an, China. Her interests include InGaN solar cell design and manufacture, antiradiation strengthening technology of InGaN solar cell, and wireless power trans- mission. (Email: 1624957070@qq.com)

    Yifan SONG was born in 1997. He is now pursuing the Master’s degree in Shaanxi University of Science and Technology, Xi’an, China. His interests include InGaN solar cell design and manufacture, antiradiation strengthening technology of InGaN solar cell, and wireless power trans- mission. (Email: 1274639733@qq.com)

    Shufang MA was born in 1970. She received the Ph.D. degree in Taiyuan University of Technology. She is now a professor at School of Physical and Information Sciences, Shaanxi University of Science and Technology. Her interests include semiconductor laser materials and device of III-V family compounds. (Email: mashufang@sust.edu.cn)

    Bingshe XU was born in 1955. He received the Ph.D. degree in the Tokyo University. He has worked as a disciplinary leading scientist in School of Physical and Information Sciences, Shaanxi University of Science and Technology. His interests include photoelectric film materials and devices, electrochemical energy storage materials and devices. (Email: xubingshe@sust.edu.cn )

  • Corresponding author: Email: xyli@nwu.edu.cn
  • Available Online: 2024-03-02
  • A dynamic programming (DP) algorithm is proposed for parameter extraction of the single-diode model (SDM). Five parameters of SDM are extracted from current-voltage (I-V) curves of InGaN/GaN Multi-quantum wells solar cells (SCs) under AM1.5 standard sunlight conditions, with indium (In) compositions of 7% and 18%. Firstly, the range of series resistance (Rs) of the device is adaptively selected and its value is randomly determined. Next, after the series resistance and the range of ideal factors are planned the parameters of SDM are iteratively solved using the root mean square error (RMSE) of the I-V curve and the photoelectric conversion efficiency (η). Due to this approach, the proposed algorithm is fast and accurate compared with other conventional algorithms. Additionally, the obtained RMSE value is controlled within 1.2e-5, and the calculated fill factor (FF) and η are consistent with the measured values. This study provides a reference for power optimization of advanced semiconductor photovoltaic cell systems.
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