Cost-Effective Measurement Techniques for Accurate Characterization of Triboelectric Nanogenerators

Sustainable energy harvesting technologies have gained significant attention for their potential to power modern electronic applications like the Internet of Things (IoT), wearable devices, and self-powered systems. Among these technologies, triboelectric nanogenerators (TENGs) stand out for their ability to convert mechanical energy into electricity. Their lightweight structure, scalability, and flexibility to harvest energy from various sources make them particularly well-suited for these applications. However, accurately characterizing their performance remains challenging due to their high internal impedance and dynamic operating conditions, leading to measurement inaccuracies that hinder research and practical adoption. This paper presents a practical and cost-effective voltage divider method for measuring triboelectric nanogenerator (TENG) output, addressing the impedance mismatch issue with standard instruments. The approach is simple, reproducible, and validated through simulations and experiments, demonstrating high accuracy (within <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$85-97 \%$</tex> of a professional electrometer). The proposed approach was validated through simulations in LTspice and experimental tests with a wind energy harvester, demonstrating improved measurement accuracy across different TENG setups. These results represent a significant advancement in overcoming TENG measurement challenges and pave the way for broader integration of TENGs into emerging technologies.

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Published
2025-07-20
DOI
https://doi.org/10.1109/antem64578.2025.11114189
Primary Topic
Advanced Sensor and Energy Harvesting Materials
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article
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article

Cost-Effective Measurement Techniques for Accurate Characterization of Triboelectric Nanogenerators

Hamed Nasiri, Sophia Zhang, Ting Zou, Lihong Zhang et al.
Advanced Sensor and Energy Harvesting Materials
article

Cost-Effective Measurement Techniques for Accurate Characterization of Triboelectric Nanogenerators

Hamed Nasiri, Sophia Zhang, Ting Zou, Lihong Zhang, Abel Mwepu Tshimbu
article en

Abstract

Sustainable energy harvesting technologies have gained significant attention for their potential to power modern electronic applications like the Internet of Things (IoT), wearable devices, and self-powered systems. Among these technologies, triboelectric nanogenerators (TENGs) stand out for their ability to convert mechanical energy into electricity. Their lightweight structure, scalability, and flexibility to harvest energy from various sources make them particularly well-suited for these applications. However, accurately characterizing their performance remains challenging due to their high internal impedance and dynamic operating conditions, leading to measurement inaccuracies that hinder research and practical adoption. This paper presents a practical and cost-effective voltage divider method for measuring triboelectric nanogenerator (TENG) output, addressing the impedance mismatch issue with standard instruments. The approach is simple, reproducible, and validated through simulations and experiments, demonstrating high accuracy (within <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$85-97 \%$</tex> of a professional electrometer). The proposed approach was validated through simulations in LTspice and experimental tests with a wind energy harvester, demonstrating improved measurement accuracy across different TENG setups. These results represent a significant advancement in overcoming TENG measurement challenges and pave the way for broader integration of TENGs into emerging technologies.

Memorial University of Newfoundland (CA), Holy Family University (US)
Openalex Percentile: Top 80%
Advanced Sensor and Energy Harvesting Materials
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Cost-Effective Measurement Techniques for Accurate Characterization of Triboelectric Nanogenerators — Hamed Nasiri, Sophia Zhang, et al. · (2025) | TGRS Research Map | TGRS