TY - JOUR
T1 - Effect of the inherent capacitance optimization on the output performance of triboelectric nanogenerators
AU - Zargari, Siavash
AU - Rezaniakolaei, Alireza
AU - Koozehkanani, Ziaddin
AU - Veladi, Hadi
AU - Sobhi, Jafar
AU - Rosendahl, Lasse
PY - 2022
Y1 - 2022
N2 - Triboelectric nanogenerator (TENG) is a new category of efficient technologies for energy harvesting applications. It has been shown as a promising method for converting low-frequency mechanical motions into electrical energy. The amount of power generated and its optimization are the most important criteria in the design of TENGs. However, some important factors influencing the performance of TENGs are not well known. Here, the TENG inherent capacitance optimization was fully studied, and its impact on the output performance of the energy harvester was assessed. The inherent capacitance of most TENGs varies over time, limiting effective power transfer to the electrical load. Thus, an optimal series capacitor was incorporated into the TENG to stabilize the variations in its inherent capacitance and improve power generation performance. Moreover, this study theoretically demonstrated that this solution increases the system figure of merit, which defines the peak output power in a single cycle. With the addition of the optimal series capacitor into the TENG, the stored energy in a 1000 μF capacitor was increased up to 82.36%. According to the experiments, using a modified power management circuit can dramatically boost the harvested power. Compared to the direct usage of TENG without any interface circuit, using the proposed capacitance optimization method and modification of the power management circuit multiplied the stored energy in a 1000 μF capacitor by 173.9 times. The findings of this study highlight the importance of optimizing the inherent capacitance of the TENG as well as the load resistance, which has important implications for the optimization of TENGs. This method is expected to broaden the applications of TENG devices.
AB - Triboelectric nanogenerator (TENG) is a new category of efficient technologies for energy harvesting applications. It has been shown as a promising method for converting low-frequency mechanical motions into electrical energy. The amount of power generated and its optimization are the most important criteria in the design of TENGs. However, some important factors influencing the performance of TENGs are not well known. Here, the TENG inherent capacitance optimization was fully studied, and its impact on the output performance of the energy harvester was assessed. The inherent capacitance of most TENGs varies over time, limiting effective power transfer to the electrical load. Thus, an optimal series capacitor was incorporated into the TENG to stabilize the variations in its inherent capacitance and improve power generation performance. Moreover, this study theoretically demonstrated that this solution increases the system figure of merit, which defines the peak output power in a single cycle. With the addition of the optimal series capacitor into the TENG, the stored energy in a 1000 μF capacitor was increased up to 82.36%. According to the experiments, using a modified power management circuit can dramatically boost the harvested power. Compared to the direct usage of TENG without any interface circuit, using the proposed capacitance optimization method and modification of the power management circuit multiplied the stored energy in a 1000 μF capacitor by 173.9 times. The findings of this study highlight the importance of optimizing the inherent capacitance of the TENG as well as the load resistance, which has important implications for the optimization of TENGs. This method is expected to broaden the applications of TENG devices.
KW - Figure of merit
KW - Inherent capacitance
KW - Power generation optimization
KW - Power management circuit
KW - Series capacitor
KW - Triboelectric nanogenerator
UR - http://www.scopus.com/inward/record.url?scp=85119267718&partnerID=8YFLogxK
U2 - 10.1016/j.nanoen.2021.106740
DO - 10.1016/j.nanoen.2021.106740
M3 - Journal article
SN - 2211-2855
VL - 92
JO - Nano Energy
JF - Nano Energy
M1 - 106740
ER -