A low-power-consumption boost converter with maximum power tracking algorithm for indoor photovoltaic energy harvesting

Dian Lin Tsai, Hung Hsien Wu, Chia-Ling Wei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In recent years, wireless sensor network technique develops rapidly, but its operation life is still limited by the energy storage element. Thus, if ambient energy can be harvested to supply the sensors, the operation life can be increased and the cost can be reduced. A boost converter for indoor photovoltaic energy harvesting with low power consumption is proposed in this work. For harvesting energy from photovoltaic cells, the proposed converter uses the maximum power point tracking algorithm, which regulates the conduction time of the power transistors. The harvested energy is stored in a super capacitor. The proposed system is integrated into a chip, which was fabricated by using a 0.18μm 1P6M mixed-signal process, and the total area is 853×1006 μm2.

Original languageEnglish
Title of host publicationWPTC 2017 - Wireless Power Transfer Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509045853
DOIs
Publication statusPublished - 2017 Jun 19
Event2017 Wireless Power Transfer Conference, WPTC 2017 - Taipei, Taiwan
Duration: 2017 May 102017 May 12

Publication series

NameWPTC 2017 - Wireless Power Transfer Conference

Other

Other2017 Wireless Power Transfer Conference, WPTC 2017
CountryTaiwan
CityTaipei
Period17-05-1017-05-12

Fingerprint

Energy harvesting
Electric power utilization
Photovoltaic cells
Energy storage
Wireless sensor networks
Capacitors
Sensors
Costs
Power transistors

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology

Cite this

Tsai, D. L., Wu, H. H., & Wei, C-L. (2017). A low-power-consumption boost converter with maximum power tracking algorithm for indoor photovoltaic energy harvesting. In WPTC 2017 - Wireless Power Transfer Conference [7953840] (WPTC 2017 - Wireless Power Transfer Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WPT.2017.7953840
Tsai, Dian Lin ; Wu, Hung Hsien ; Wei, Chia-Ling. / A low-power-consumption boost converter with maximum power tracking algorithm for indoor photovoltaic energy harvesting. WPTC 2017 - Wireless Power Transfer Conference. Institute of Electrical and Electronics Engineers Inc., 2017. (WPTC 2017 - Wireless Power Transfer Conference).
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abstract = "In recent years, wireless sensor network technique develops rapidly, but its operation life is still limited by the energy storage element. Thus, if ambient energy can be harvested to supply the sensors, the operation life can be increased and the cost can be reduced. A boost converter for indoor photovoltaic energy harvesting with low power consumption is proposed in this work. For harvesting energy from photovoltaic cells, the proposed converter uses the maximum power point tracking algorithm, which regulates the conduction time of the power transistors. The harvested energy is stored in a super capacitor. The proposed system is integrated into a chip, which was fabricated by using a 0.18μm 1P6M mixed-signal process, and the total area is 853×1006 μm2.",
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Tsai, DL, Wu, HH & Wei, C-L 2017, A low-power-consumption boost converter with maximum power tracking algorithm for indoor photovoltaic energy harvesting. in WPTC 2017 - Wireless Power Transfer Conference., 7953840, WPTC 2017 - Wireless Power Transfer Conference, Institute of Electrical and Electronics Engineers Inc., 2017 Wireless Power Transfer Conference, WPTC 2017, Taipei, Taiwan, 17-05-10. https://doi.org/10.1109/WPT.2017.7953840

A low-power-consumption boost converter with maximum power tracking algorithm for indoor photovoltaic energy harvesting. / Tsai, Dian Lin; Wu, Hung Hsien; Wei, Chia-Ling.

WPTC 2017 - Wireless Power Transfer Conference. Institute of Electrical and Electronics Engineers Inc., 2017. 7953840 (WPTC 2017 - Wireless Power Transfer Conference).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Wu, Hung Hsien

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N2 - In recent years, wireless sensor network technique develops rapidly, but its operation life is still limited by the energy storage element. Thus, if ambient energy can be harvested to supply the sensors, the operation life can be increased and the cost can be reduced. A boost converter for indoor photovoltaic energy harvesting with low power consumption is proposed in this work. For harvesting energy from photovoltaic cells, the proposed converter uses the maximum power point tracking algorithm, which regulates the conduction time of the power transistors. The harvested energy is stored in a super capacitor. The proposed system is integrated into a chip, which was fabricated by using a 0.18μm 1P6M mixed-signal process, and the total area is 853×1006 μm2.

AB - In recent years, wireless sensor network technique develops rapidly, but its operation life is still limited by the energy storage element. Thus, if ambient energy can be harvested to supply the sensors, the operation life can be increased and the cost can be reduced. A boost converter for indoor photovoltaic energy harvesting with low power consumption is proposed in this work. For harvesting energy from photovoltaic cells, the proposed converter uses the maximum power point tracking algorithm, which regulates the conduction time of the power transistors. The harvested energy is stored in a super capacitor. The proposed system is integrated into a chip, which was fabricated by using a 0.18μm 1P6M mixed-signal process, and the total area is 853×1006 μm2.

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Tsai DL, Wu HH, Wei C-L. A low-power-consumption boost converter with maximum power tracking algorithm for indoor photovoltaic energy harvesting. In WPTC 2017 - Wireless Power Transfer Conference. Institute of Electrical and Electronics Engineers Inc. 2017. 7953840. (WPTC 2017 - Wireless Power Transfer Conference). https://doi.org/10.1109/WPT.2017.7953840