A negative-work knee energy harvester based on homo-phase transfer for wearable monitoring devices

A Self-Sensing and Self-Powered Wearable System Based on Multi-Source Human Motion Energy Harvesting

Wearable devices play an indispensable role in modern life, and the human body contains multiple wasted energies available for wearable devices. This study proposes a self-sensing and self-powered wearable system (SS-WS) based on scavenging waist motion energy and knee negative energy. The proposed SS-WS consists of a three-degree-of-freedom triboelectric nanogenerator (TDF-TENG) and a negative energy harvester (NEH). The TDF-TENG is driven by waist motion energy and the generated triboelectric signals are processed by deep learning for recognizing the human motion. The triboelectric signals generated by TDF-TENG can accurately recognize the motion state after processing based on Gate Recurrent Unit deep learning model. With double frequency up-conversion, the NEH recovers knee negative energy generation for powering wearable devices. A model wearing the single energy harvester can generate the power of 27.01 mW when the movement speed is 8 km h-1, and the power density of NEH reaches 0.3 W kg-1 at an external excitation condition of 3 Hz. Experiments and analysis prove that the proposed SS-WS can realize self-sensing and effectively power wearable devices.

A self-powered and self-sensing knee negative energy harvester

Wearable devices realize health monitoring, information transmission, etc. In this study, the human-friendliness, adaptability, reliability, and economy (HARE) principle for designing human energy harvesters is first proposed and then a biomechanical energy harvester (BMEH) is proposed to recover the knee negative energy to generate electricity. The proposed BMEH is mounted on the waist of the human body and connected to the ankles by ropes for driving. Double-rotor mechanism and half-wave rectification mechanism design effectively improves energy conversion efficiency with higher power output density for more stable power output. The experimental results demonstrate that the double-rotor mechanism increases the output power of the BMEH by 70% compared to the single magnet-rotor mechanism. And the output power density of BMEH reaches 0.07 W/kg at a speed of 7 km/h. Furthermore, the BMEH demonstrates the excitation mode detection accuracy of 99.8% based on the Gate Recurrent Unit deep learning model with optimal parameters.

Parameter optimization analysis of rotary electromagnetic vibration energy harvester for performance enhancement under free vibration

In this paper, three new important aspects of rotary electromagnetic vibration energy harvesting technology (RE-VEH) are concerned and investigated: (i) vibro-electric coupling mechanism of the RE-VEH system is studied through theoretical modeling; (ii) quantitative analysis of system parameters based on numerical simulation method is carried out for the optimal design of RE-VEH; and (iii) dynamic power output performance of the RE-VEH system in free vibration is discussed. The parameter adjusting methods of the RE-VEH system in free vibration mode are obtained through theoretical analysis and numerical simulation. The experimental results show that the power output performance of RE-VEH in free vibration mode matches the numerical simulation results. The simulation and experimental results show that the maximum voltage output and power output of the RE-VEH with different structure parameters under free vibration can be up to the level of 100∼101 V/watt. The above results indicate that RE-VEH in a free vibration environment has significant energy output performance.