IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i22p7780-d683536.html
   My bibliography  Save this article

An Average Model of DC–DC Step-Up Converter Considering Switching Losses and Parasitic Elements

Author

Listed:
  • Marco Faifer

    (Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy)

  • Luigi Piegari

    (Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy)

  • Marco Rossi

    (RSE, Ricerca sul Sistema Energetico, Via Rubattino, 20134 Milan, Italy)

  • Sergio Toscani

    (Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy)

Abstract

Power electronic converters represent a pillar of modern power systems, especially since generation from renewable energy sources, such as photovoltaics, have been introduced. One of their main characteristics consists of the high flexibility in converting different voltage levels and waveforms. As for all the conversion devices, they are subjected to unavoidable losses introduced by non-ideal components. For this reason, in the last few decades numerous research activities have been devoted to model their behavior and predicting the global efficiency. In spite of the number of scientific publications on the topic, the non-idealities have been rarely studied in terms of their impact on the input-output characteristics of the converter. In this paper, the conventional equivalent circuit of a step-up DC/DC converter has been upgraded in order to introduce the effects of both conduction and switching losses. The obtained formulation, applicable to all DC/DC converters, allows a more accurate average model that is particularly suitable for the study of multi-converter architectures, as for the most recent renewable energy sources applications. Finally, thanks to a dedicated test setup, the results of an experimental campaign demonstrate how the new formulation faithfully predicts its electrical behavior.

Suggested Citation

  • Marco Faifer & Luigi Piegari & Marco Rossi & Sergio Toscani, 2021. "An Average Model of DC–DC Step-Up Converter Considering Switching Losses and Parasitic Elements," Energies, MDPI, vol. 14(22), pages 1-18, November.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:22:p:7780-:d:683536
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/22/7780/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/22/7780/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Qi, Nanjian & Yin, Yajiang & Dai, Keren & Wu, Chengjun & Wang, Xiaofeng & You, Zheng, 2021. "Comprehensive optimized hybrid energy storage system for long-life solar-powered wireless sensor network nodes," Applied Energy, Elsevier, vol. 290(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lebogang Masike & Michael Njoroge Gitau & Grain P. Adam, 2022. "A Unified Rule-Based Small-Signal Modelling Technique for Two-Switch, Non-Isolated DC–DC Converters in CCM," Energies, MDPI, vol. 15(15), pages 1-23, July.
    2. Marco Bosi & Albert-Miquel Sánchez & Francisco Javier Pajares & Alessandro Campanini & Lorenzo Peretto, 2023. "PLF Design for DC-DC Converters Based on Accurate IL Estimations," Energies, MDPI, vol. 16(5), pages 1-18, February.
    3. Martin A. Alarcón-Carbajal & José E. Carvajal-Rubio & Juan D. Sánchez-Torres & David E. Castro-Palazuelos & Guillermo J. Rubio-Astorga, 2022. "An Output Feedback Discrete-Time Controller for the DC-DC Buck Converter," Energies, MDPI, vol. 15(14), pages 1-21, July.
    4. Angelo Lunardi & Luís F. Normandia Lourenço & Enkhtsetseg Munkhchuluun & Lasantha Meegahapola & Alfeu J. Sguarezi Filho, 2022. "Grid-Connected Power Converters: An Overview of Control Strategies for Renewable Energy," Energies, MDPI, vol. 15(11), pages 1-33, June.

    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. Diana Lemian & Florin Bode, 2022. "Battery-Supercapacitor Energy Storage Systems for Electrical Vehicles: A Review," Energies, MDPI, vol. 15(15), pages 1-13, August.
    2. Liu, Xinzhi & Qi, Nanjian & Dai, Keren & Yin, Yajiang & Zhao, Jiahao & Wang, Xiaofeng & You, Zheng, 2022. "Sponge Supercapacitor rule-based energy management strategy for wireless sensor nodes optimized by using dynamic programing algorithm," Energy, Elsevier, vol. 239(PE).
    3. Duan, Hanbing & Zhang, Wenye & Guo, Zhongyuan & Su, Xiaoxiang & Liu, Yongcun & Meng, Hao & Yu, Xiang & Qin, Gang & Chen, Qiang & Yang, Jia, 2023. "Tough, highly adaptable and self-healing integrated supercapacitor based on double network gel polymer electrolyte," Energy, Elsevier, vol. 264(C).
    4. Denis Artyukhov & Nikolay Gorshkov & Maria Vikulova & Nikolay Kiselev & Artem Zemtsov & Ivan Artyukhov, 2022. "Power Supply of Wireless Sensors Based on Energy Conversion of Separated Gas Flows by Thermoelectrochemical Cells," Energies, MDPI, vol. 15(4), pages 1-16, February.
    5. Li, Wenzhuo & Tang, Rui & Wang, Shengwei & Zheng, Zhuang, 2023. "An optimal design method for communication topology of wireless sensor networks to implement fully distributed optimal control in IoT-enabled smart buildings," Applied Energy, Elsevier, vol. 349(C).
    6. Xie, Haonan & Jiang, Meihui & Zhang, Dongdong & Goh, Hui Hwang & Ahmad, Tanveer & Liu, Hui & Liu, Tianhao & Wang, Shuyao & Wu, Thomas, 2023. "IntelliSense technology in the new power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 177(C).
    7. Adrian Chmielewski & Piotr Piórkowski & Krzysztof Bogdziński & Jakub Możaryn, 2023. "Application of a Bidirectional DC/DC Converter to Control the Power Distribution in the Battery–Ultracapacitor System," Energies, MDPI, vol. 16(9), pages 1-40, April.
    8. Ting, Zhang & Yunna, Wu, 2024. "Collaborative allocation model and balanced interaction strategy of multi flexible resources in the new power system based on Stackelberg game theory," Renewable Energy, Elsevier, vol. 220(C).
    9. Song, Hui & Gu, Mingchen & Liu, Chen & Amani, Ali Moradi & Jalili, Mahdi & Meegahapola, Lasantha & Yu, Xinghuo & Dickeson, George, 2023. "Multi-objective battery energy storage optimization for virtual power plant applications," Applied Energy, Elsevier, vol. 352(C).
    10. Kuo-Yuan Lo & Kuo-Hsiang Liu & Li-Xin Chen & Ching-Yu Chen & Chang-Heng Shih & Jyun-Ting Lin, 2022. "Multi-Mode Control of a Bidirectional Converter for Battery Energy Storage System," Energies, MDPI, vol. 15(21), pages 1-18, October.

    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:gam:jeners:v:14:y:2021:i:22:p:7780-:d:683536. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.