Towards self-powered technique in underwater robots via a high-efficiency electromagnetic transducer with circularly abrupt magnetic flux density change

Li, Zhongjie; Jiang, Xiaomeng; Yin, Peilun; Tang, Lihua; Wu, Hao; Peng, Yan; Luo, Jun; Xie, Shaorong; Pu, Huayan; Dai-feng, Wang

doi:10.1016/j.apenergy.2021.117569

Cited by 51 publications

(17 citation statements)

References 86 publications

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“…Meanwhile, portable wireless electronics are undergoing explosive advancement, with the total number increasing tremendously and power consumption decreasing significantly. 11 Converting various energy, such as solar, 12 wind, 13 electromagnetic, [14][15][16] and mechanical [17][18][19] energy, into electricity is a practical strategy. Among these energy sources, the mechanical energy generated by human motion displays distinct advantages of high density, wide distribution, and convenient acquisition, which makes it a premier choice for portable energy supply units.…”

Section: Introductionmentioning

confidence: 99%

Human body IoT systems based on the triboelectrification effect: energy harvesting, sensing, interfacing and communication

Zhang

Xin

Fan

et al. 2022

Energy Environ. Sci.

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157

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Section: Introductionmentioning

confidence: 99%

Human body IoT systems based on the triboelectrification effect: energy harvesting, sensing, interfacing and communication

Zhang

Xin

Fan

et al. 2022

Energy Environ. Sci.

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157

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“…Various renewable energy harvesters have been designed with unique structures in recent years. These regenerative harvesters' principles consist of the piezoelectric effect [1], the triboelectric effect [2], the electromagnetic effect [3], and the hybrid between them. As a renewable energy harvester, triboelectric nanogenerators (TENGs) provide an alternative method that converts mechanical motion into electrical energy.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Power Density of Triboelectric Generators via Frequency-up-Conversion Method

Chao

Peng

et al. 2023

J. Phys.: Conf. Ser.

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In this paper, we experimentally compared the instantaneous volume power density and the average volume power density of the triboelectric nanogenerator (TENG) with and without a frequency-up conversion mechanism. We first proposed a double-cantilever structure TENG (DC-TENG). A conventional contact-separation TENG was also constructed as the control case for electric output comparison. A few experiments were then conducted to investigate how the cantilever’s high-frequency vibrations influence the output voltage, instantaneous power, etc., before those of the triboelectric nanogenerator without frequency conversion. The results indicate that the double-cantilever system effectively converts low-frequency linear impact into high-frequency vibration. As of the best contrast, the DC-TENG yields a maximal open-circuit voltage of 141.5 V, an instantaneous power of 0.76 mW, and an average power of 0.77 μW excited by a linear impact, which frequency is 0.6 Hz and amplitude is 8 mm. The peak and the average power density of generators with the frequency convert device are enhanced by 34 times and 13 times as high as those of the original case, respectively. This finding proves that the cantilever integrated with triboelectric nanogenerators is an effective configuration with evident performance improvement.

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“…When TENGs are utilized to collect energy from human body, TENGs are generally fixed at joints (knee, elbow, shoulder). TENGs have to bear a large deformation and frequent bending, which cause TENGs to fracture. ,, In the domain of marine energy harvesting, the problem of seawater corrosion and adhesion of microorganisms cannot be ignored. − Most of the wind-driven TENGs adopt rotary structures, which are prone to abrasion because of surface friction. , Most TENGs are designed as fully encapsulated structures to maintain a robust operation environment, and such limitations show a challenge to monitor the operating state. Local defects occur the inside of TENGs, which cannot be directly detected.…”

Section: Introductionmentioning

confidence: 99%

Interface Defect Detection and Identification of Triboelectric Nanogenerators via Voltage Waveforms and Artificial Neural Network

Fan

Xin

et al. 2022

ACS Appl. Mater. Interfaces

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To provide a robust working environment for TENGs, most TENGs are designed as sealed structures that isolate TENGs from the external environment, and thus their operating conditions cannot be directly monitored. Here, for the first time, we propose an artificial neural network for interface defect detection and identification of triboelectric nanogenerators via training voltage waveforms. First, interface defects of TENGs are classified and their causes are discussed in detail. Then we build a lightweight artificial neural network model which shows high sensitivity to voltage waveforms and low time complexity. The model takes 2.1 s for training one epoch, and the recognition rate of defect detection is 98.9% after 100 epochs. Meanwhile, the model successfully demonstrates the learning ability for low-resolution samples (100 × 75 pixels), which can identify six types of TENG defects, such as edge fracture, adhesion, and abnormal vibration, with a high recognition rate of 93.6%. This work provides a new strategy for the fault diagnosis and intelligent application of TENGs.

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Towards self-powered technique in underwater robots via a high-efficiency electromagnetic transducer with circularly abrupt magnetic flux density change

Cited by 51 publications

References 86 publications

Human body IoT systems based on the triboelectrification effect: energy harvesting, sensing, interfacing and communication

Human body IoT systems based on the triboelectrification effect: energy harvesting, sensing, interfacing and communication

Comparison of Power Density of Triboelectric Generators via Frequency-up-Conversion Method

Interface Defect Detection and Identification of Triboelectric Nanogenerators via Voltage Waveforms and Artificial Neural Network

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