CAREER: Irregular Modulation: Harnessing the Hidden Potential of PWM

职业:不规则调制:利用 PWM 的隐藏潜力

基本信息

  • 批准号:
    2339806
  • 负责人:
  • 金额:
    $ 55万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2024
  • 资助国家:
    美国
  • 起止时间:
    2024-01-01 至 2028-12-31
  • 项目状态:
    未结题

项目摘要

Modulation, since the birth of modern power electronics, bridges control algorithms with switch operations. Despite its significance, research related to modulation has seen relatively little progress in the past decade, generally due to the widespread use of sequential computing devices (e.g. digital signal processors). However, recent breakthroughs in artificial intelligence (AI) technologies have propelled parallel computing devices into the forefront. To leverage the potential benefits of parallel computing devices and AI, this project proposes an irregular modulation theory, which can be easily applied to parallel computing devices and memristive devices. Additionally, this project will fully unlock the control capacity of modulation, enabling the control bandwidth to truly benefit from the high switching frequency brought in by Wide Bandgap (WBG) devices. This novel modulation approach will inevitably lead to the emergence of new topologies and control strategies, naturally giving rise to novel inverter modeling methodologies. Furthermore, the PI proposes a Mini-Task Inspired Learning Experience (M-TILE) approach to support students, particularly those from underrepresented groups, in overcoming imposter syndrome. To extend the impact of M-TILE, this concept will be shared with local K-12 teachers through a one-day workshop. By deeply integrating irregular modulation and the M-TILE concept, education activities will offer world-class education, inspiring and training future leaders in science, technology, engineering, and mathematics (STEM). The proposed irregular modulation theory will break free from the conventional idea of sawtooth and triangular carriers and lead to a new genre of converter modulation technologies. It will fundamentally change the operating principle of future power converters. Due to the fast response nature of modulation-control integration, it is possible to enable a new ultrafast control loop in addition to the classic double-loop control architecture. This new control loop will accommodate the recent advancement of AI technologies and lead to an entirely new genre of grid services. As a result of irregular modulation, a wide variety of new converter topologies, controls, and models will be revealed, holding the potential to eliminate vulnerable components and reduce voltage/current stress. Therefore, the irregular modulation theory proposed in this project will serve as the fundamental enabler of new topologies. This, in turn, will ultimately reduce device stress and component count, significantly lowering converter cost and enhancing reliability.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
调制,自现代电力电子诞生以来,就将控制算法与开关操作连接起来。尽管具有重要意义,但在过去十年中,与调制相关的研究进展相对较少,这通常是由于顺序计算设备(例如数字信号处理器)的广泛使用。然而,最近人工智能(AI)技术的突破将并行计算设备推向了最前沿。为了利用并行计算设备和人工智能的潜在优势,本项目提出了一种不规则调制理论,该理论可以很容易地应用于并行计算设备和忆阻装置。此外,该项目将充分释放调制的控制能力,使控制带宽真正受益于宽带隙(WBG)设备带来的高开关频率。这种新颖的调制方法将不可避免地导致新的拓扑和控制策略的出现,自然产生新的逆变器建模方法。此外,PI还提出了一种小型任务启发式学习体验(M-TILE)方法,以支持学生,特别是那些来自代表性不足群体的学生,克服冒名顶替综合症。为了扩大M-TILE的影响力,将通过为期一天的研讨会与当地K-12教师分享这一概念。通过深度整合不规则调制和M-TILE概念,教育活动将提供世界一流的教育,激励和培养未来的科学,技术,工程和数学(STEM)领导者。提出的不规则调制理论将打破锯齿形载波和三角形载波的传统观念,带来一种新的变换器调制技术。它将从根本上改变未来电源转换器的工作原理。由于调制控制集成的快速响应特性,除了经典的双环控制结构外,还可以实现新的超快控制回路。这种新的控制回路将适应最近人工智能技术的进步,并导致一种全新的网格服务类型。由于不规则调制,各种各样的新转换器拓扑结构、控制和模型将被揭示,具有消除易感元件和降低电压/电流应力的潜力。因此,本项目提出的不规则调制理论将成为新拓扑的基本推动者。这将最终减少器件压力和元件数量,显著降低转换器成本并提高可靠性。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

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Yunting Liu其他文献

Chiral Bifunctional Squaramide‐Catalyzed Highly Enantioselective Michael Addition of Allomaltol to β,γ‐Unsaturated α‐Ketoesters
手性双功能方酰胺催化异麦芽酚与 β,γ-不饱和 α-酮酯的高对映选择性迈克尔加成反应
  • DOI:
  • 发表时间:
    2014
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Yunting Liu;Qiaohui Wang;Y. Wang;Hai;Zhenghong Zhou
  • 通讯作者:
    Zhenghong Zhou
A dual-enzyme microreactor based on encapsulation and covalent bond for enzymatic electrocatalytic COsub2/sub reduction
基于包封和共价键的双酶微反应器用于酶促电催化二氧化碳还原
  • DOI:
    10.1016/j.cej.2023.146186
  • 发表时间:
    2023-11-01
  • 期刊:
  • 影响因子:
    13.200
  • 作者:
    Guanhua Liu;Lirong Wang;Lihang Yan;Hao Zhao;Yaoxuan Li;Liya Zhou;Ying He;Li Ma;Yunting Liu;Jing Gao;Yanjun Jiang
  • 通讯作者:
    Yanjun Jiang
Medical knowledge decline: the role of active usage
  • DOI:
    10.1007/s10459-025-10461-4
  • 发表时间:
    2025-07-30
  • 期刊:
  • 影响因子:
    3.300
  • 作者:
    Yunting Liu;Yanlin Jiang;Andrew D. Dallas;Mirela Bruza-Augatis
  • 通讯作者:
    Mirela Bruza-Augatis
Quasi-Static Time Series Fatigue Simulation for PV Inverter Semiconductors with Long-Term Solar Profile
具有长期太阳能曲线的光伏逆变器半导体的准静态时间序列疲劳仿真
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Yunting Liu;L. Tolbert;Paychuda Kritprajun;Q. Dong;Lin Zhu;J. Hambrick;K. Schneider;K. Prabakar
  • 通讯作者:
    K. Prabakar
16S rRNA gene sequencing and machine learning reveal correlation between drug abuse and human host gut microbiota
16S rRNA 基因测序和机器学习揭示药物滥用与人类宿主肠道微生物群之间的相关性
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    3.4
  • 作者:
    Yunting Liu;Pei Zhang;Hongmei Sheng;Ding Xu;Daixi Li;Lizhe An
  • 通讯作者:
    Lizhe An

Yunting Liu的其他文献

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