Research On Acoustic Energy Harvesting System And Output Power Automatic Test System Of Triboelectric Nanogenerator

There are a huge number of widely distributed electronic devices in the Internet of Things.How to realize the mechanical energy in the operating environment to power these electronic devices has become a research hotspot in the academic and industrial circles.In recent years,triboelectric nanogenerator(TENG)has shown great potential for the harvesting of mechanical energy in the environment,providing a new research direction for the power supply of electronic devices in the Internet of Things.In this paper,the acoustic triboelectric nanogenerator(A-TENG)and its application in selfpowered edge sensing are studied.A 3D printing based acoustic triboelectric nanogenerator was developed by selecting perfluorinated Ethylene copolymer(FEP)and Polylactic Acid(PLA)as triboelectric layers.A quarter wavelength acoustic energy harvesting system was developed by combining acoustic triboelectric nanogenerator and quarter wavelength tube.Under acoustic excitation of 100 d B sound pressure level,the maximum open circuit voltage and maximum shortcircuit current of the system are 330 V and 40 μA,respectively.The output power of the acoustic triboelectric nanogenerator is tested.The external load resistance is 7 MΩ,and the maximum output power is 4.3 m W.The system can light up 72 green LED lights,drive a commercial calculator continuously and enable a remote switching on system,demonstrating that it can be used as a power source for low-power electronic devices.At the same time,the self-powered sensing characteristics of acoustic triboelectric nanogenerator were studied,and A self-powerededge sensing system based on A-TENG was developed.Speech signals are first converted into electrical signals via A-TENG and then recognized and processed by the chip via A built-in and pre-trained neural network to control the back-end application circuit.Self-powered edge sensing systems are capable of speech recognition without the need for real-time cloud computing,showing great potential in the low-power and low-cost intelligent Internet of Things.In addition,the internal source resistance of the triboelectric nanogenerator(TENG)is very high,and the output power is different under different resistance values of the external load.To test the power output curve of TENG,an external load is attached and its resistance is constantly changed.The process of adjusting the resistance value for TENG external load is usually done manually,which is a repetitive process that is time-consuming and error-prone.To solve this problem,this paper designs an automatic test system for TENG output power,which can automatically test the TENG output power curve under the control of program.In this system,the resistance value is decomposed by octal decomposition principle,and a resistance synthesis algorithm is proposed to change the resistance value with the minimum step size of 1 Ω.In physical implementation,the use of digital channel control relay,through the relay on and off synthesis of target resistance.The proposed automation system is evaluated and the test results are compared with the traditional manual switching method,which are almost identical.Therefore,the proposed automatic test table for TENG output power will play an important role in the further study of TENG.