State Separate Modular Modeling Methodology of Multioutput DC-DC Converters

被引:0
作者
Abraham, Nithin Thomas [1 ]
Chowdary, Gajendranath [2 ]
Jagalchandran, Dhanaraj Kakkanattu [1 ,3 ]
机构
[1] Natl Inst Technol Calicut, Dept Elect & Commun, Kozhikode 673601, India
[2] Indian Inst Technol Hyderabad, Dept Elect Engn, Hyderabad 502285, India
[3] Natl Inst Technol Calicut, Dept Elect & Commun, Kozhikode, India
关键词
DC-DC converters; modeling; multioutput; MULTIPLE-OUTPUT; SWITCHING CONVERTERS; EFFICIENCY;
D O I
10.1109/TCAD.2022.3186492
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Conventional modeling and simulation of $n$ -output dc-dc converters requires $(n+1) \times (n+1)$ matrix computations. This approach increases the modeling approach's complexity and increases the design and simulation time required for the modeling process. A state separate modeling methodology is proposed where each state of the dc-dc converter is considered separately and combined with the help of a multiplexer. The proposed modeling approach is modular and thus improves the scalability to multiple outputs. The proposed methodology aids the designer in designing and modeling multioutput dc-dc converters faster, enabling fast prototyping. The proposed model outperforms the existing mathematical models in terms of computation time. The output voltage variation to duty cycles has a root mean square error in between 0.08 and 0.22 V.
引用
收藏
页码:968 / 977
页数:10
相关论文
共 50 条
  • [41] Set-membership methodology for multiple fault detection and isolation in DC-DC Buck Converters
    Thabet, Rihab El Honda
    Chafouk, Houcine
    PROCEEDINGS OF THE 18TH MEDITERRANEAN ELECTROTECHNICAL CONFERENCE MELECON 2016, 2016,
  • [42] Modeling Methodology Based on Fast and Refined Neural Networks for Non-Isolated DC-DC Converters With Configurable Parameter Settings
    Ge, Hanchen
    Huang, Zhihong
    Huang, Zhicong
    IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS, 2023, 13 (02) : 617 - 628
  • [43] Analysis and Optimization of DC-DC Converters Through Sensitivity to Parametric Variations
    Hinov, Nikolay
    Stanchev, Plamen
    Vacheva, Gergana
    TECHNOLOGIES, 2025, 13 (02)
  • [44] Modeling and Advanced Control of Dual-Active-Bridge DC-DC Converters: A Review
    Shao, Shuai
    Chen, Linglin
    Shan, Zhenyu
    Gao, Fei
    Chen, Hui
    Sha, Deshang
    Dragicevic, Tomislav
    IEEE TRANSACTIONS ON POWER ELECTRONICS, 2022, 37 (02) : 1524 - 1547
  • [45] MODELING OF STEP-UP DC-DC CONVERTERS TO FORMULATE DESIGN GUIDELINES FOR OPTIMIZATION
    Hasan, Ayaz
    Gregori, Stefano
    2009 IEEE 22ND CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING, VOLS 1 AND 2, 2009, : 16 - 20
  • [46] Review and Comparative Study of Bi-Directional DC-DC Converters
    Lithesh, Gottapu
    Krishna, Bekkam
    Karthikeyan, V
    2021 IEEE INTERNATIONAL POWER AND RENEWABLE ENERGY CONFERENCE (IPRECON), 2021,
  • [47] Modeling Single Inductor DC-DC Converters With Thermal Phenomena in the Inductor Taken Into Account
    Detka, Kalina
    Gorecki, Krzysztof
    Zarebski, Janusz
    IEEE TRANSACTIONS ON POWER ELECTRONICS, 2017, 32 (09) : 7025 - 7033
  • [48] Modeling and Simulation of Voltage-Controlled DC-DC Converters Using Dynamic Phasors
    Nwaneto, Udoka Chile
    Knight, Andrew Michael
    IECON 2020: THE 46TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2020, : 1371 - 1376
  • [49] Nonlinear large-signal modeling of PWM DC-DC switching power converters
    Chen, YF
    Qui, SS
    Long, M
    2004 INTERNATIONAL CONFERENCE ON COMMUNICATION, CIRCUITS, AND SYSTEMS, VOLS 1 AND 2: VOL 1: COMMUNICATION THEORY AND SYSTEMS - VOL 2: SIGNAL PROCESSING, CIRCUITS AND SYSTEMS, 2004, : 1507 - 1510
  • [50] Blackbox Polytopic Model With Dynamic Weighting Functions for DC-DC Converters
    Frances, Airan
    Asensi, Rafael
    Uceda, Javier
    IEEE ACCESS, 2019, 7 : 160263 - 160273