Study of graphene variable capacitance based on intelligent algorithm

Yuchao Shi; Jing Wu; Haiyun Tan; Weihong Hou; Ming Tang; Tao Li

doi:10.1117/12.3006392

26 September 2023 Study of graphene variable capacitance based on intelligent algorithm

Yuchao Shi, Jing Wu, Haiyun Tan, Weihong Hou, Ming Tang, Tao Li

Proceedings Volume 12793, International Conference on Mechatronics and Intelligent Control (ICMIC 2023); 1279308 (2023) https://doi.org/10.1117/12.3006392
Event: International Conference on Mechatronics and Intelligent Control (ICMIC2023), 2023, Wuhan, China

Abstract

Graphene nanosheets have a good development in the field of power capacitors because of their unique structure, strong mechanical properties and excellent electrical conductivity. However, the capacitance capacity based on simple graphene nanomaterials is usually difficult to be adjusted dynamically. To solve this problem, this paper conducts research on the design of related capacitors and the control strategy of capacitance capacity based on the special characteristics of graphene materials. Firstly, an original five-layer graphene capacitor design is carried out in order to take advantage of the graphene material. Secondly, the control circuit and control strategy are designed and experimented, and the BP neural network algorithm is used for verification. The experiments prove that the BP neural network algorithm predicts various errors and disturbances better within the scope of this study, and the corresponding control circuit can intervene according to this prediction; thus the output current of the graphene variable capacitor is more stable.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuchao Shi, Jing Wu, Haiyun Tan, Weihong Hou, Ming Tang, and Tao Li "Study of graphene variable capacitance based on intelligent algorithm", Proc. SPIE 12793, International Conference on Mechatronics and Intelligent Control (ICMIC 2023), 1279308 (26 September 2023); https://doi.org/10.1117/12.3006392

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