A unique harvesting-sensing integrated methodology using dual capacitor matching and event-triggered energy management for self-powered sensing

Conventional self-powered sensing typically uses energy harvesters solely as power sources for external sensors. However, energy harvesters can inherently serve as sensors by transducing physical stimuli into electrical signals. Inspired by this, this work proposes a harvesting-sensing integration methodology (HSIM) that enables simultaneous energy harvesting and sensing using a single energy harvester, eliminating the need for separate sensors. To address the core challenge of signal distortion caused by the load effect under dynamic load conditions, the HSIM is implemented through energy management, which is divided into two key steps. Firstly, a dual capacitor matching method (DCMM) is proposed to dynamically isolate load from harvester, protecting signal integrity. Secondly, an event-triggered stepwise operation strategy (ESOS) is designed to detect signal distortion and prevent unreliable sensing. To validate the effectiveness of HSIM, a harvesting-sensing integration prototype was developed comprehensive experimentally tested. The experimental results demonstrate that the proposed DCMM effectively mitigates signal distortion. Moreover, Using commercial accelerometers as reference, quantitative analysis shows that the proposed method reduces the harvester sensing error by 58.3%, achieving reliable detection. In addition, the efficiency of the prototype in cold start operation is 66.45%, proving the effectiveness of the DCMM design. This inclusive design philosophy and demonstrative HSIM provide new method for the future development of battery-free energy harvesting Internet of Things.