Self-Resonant Energy Harvester With a Passively Tuned Sliding Mass

IF 1 Q4 AUTOMATION & CONTROL SYSTEMS
Hongjip Kim, Arthur C. Smith, O. Barry, L. Zuo
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引用次数: 2

Abstract

Passive tuning phenomenon with a sliding mass on a vibrating beam has been observed and studied in the literature. Such a phenomenon can be extended to self-resonant energy harvesting, where the natural frequency can be favorably adjusted to the excitation frequency for enhanced energy harvesting. In this paper, we consider the nonlinear dynamic coupling of a piezoelectric clamped-clamped beam with sliding mass and study experimentally and numerically how these nonlinear interactions affect the performance of the energy harvester. We derive the mathematical model using the extended Hamilton principle. The governing equations of motion are obtained as three coupled nonlinear partial differential equations. The Galerkin method is employed to obtain a reduced order model. Our mathematical formulation is validated via experiments and the results show very good agreement between the simulation and the experiment. Parametric studies are carried out to examine how key parameters affect the performance of the energy harvester. The findings suggest that a passively tuned mechanism with a small sliding mass can increase the power output even when the excitation frequency is far off the original resonance.
具有被动调谐滑动质量的自共振能量采集器
已有文献对振动梁上滑动质量的被动调谐现象进行了观察和研究。这种现象可以扩展到自谐振能量收集,其中固有频率可以很好地调整到激励频率,以增强能量收集。本文考虑了具有滑动质量的压电夹紧梁的非线性动力耦合,并通过实验和数值研究了这些非线性相互作用对能量收集器性能的影响。我们利用扩展的汉密尔顿原理推导了数学模型。得到了三个耦合非线性偏微分方程的运动控制方程。采用伽辽金方法得到降阶模型。通过实验验证了本文的数学公式,仿真结果与实验结果吻合较好。进行了参数化研究,以检验关键参数如何影响能量采集器的性能。研究结果表明,小滑动质量的被动调谐机构即使在激励频率远离原共振时也能提高输出功率。
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来源期刊
Mechatronic Systems and Control
Mechatronic Systems and Control AUTOMATION & CONTROL SYSTEMS-
CiteScore
1.40
自引率
66.70%
发文量
27
期刊介绍: This international journal publishes both theoretical and application-oriented papers on various aspects of mechatronic systems, modelling, design, conventional and intelligent control, and intelligent systems. Application areas of mechatronics may include robotics, transportation, energy systems, manufacturing, sensors, actuators, and automation. Techniques of artificial intelligence may include soft computing (fuzzy logic, neural networks, genetic algorithms/evolutionary computing, probabilistic methods, etc.). Techniques may cover frequency and time domains, linear and nonlinear systems, and deterministic and stochastic processes. Hybrid techniques of mechatronics that combine conventional and intelligent methods are also included. First published in 1972, this journal originated with an emphasis on conventional control systems and computer-based applications. Subsequently, with rapid advances in the field and in view of the widespread interest and application of soft computing in control systems, this latter aspect was integrated into the journal. Now the area of mechatronics is included as the main focus. A unique feature of the journal is its pioneering role in bridging the gap between conventional systems and intelligent systems, with an equal emphasis on theory and practical applications, including system modelling, design and instrumentation. It appears four times per year.
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