Design and analysis of a mechanically intelligent system for biomechanical energy harvesting

Abstract The rapid advancement of wearable electronic devices has paved the way for a more intelligent and interconnected world. However, ensuring the sustainable energy supply for these devices remains a critical challenge, particularly for specialized populations and professionals in demanding environments, where a lack of power can pose life-threatening risks. Herein, we propose a mechanically intelligent biomechanical energy harvesting approach that adapts to complex human motion excitations, thereby improving the energy harvesting performance. Leveraging a mechanical intelligence mechanism, the energy harvester aligns with human physiological habits, selectively activating or deactivating as needed. The system can also adapt to excitations of varying directions, amplitudes, and frequencies. Furthermore, the string tension helps reduce the impact forces on the knee joint during foot strikes. A theoretical model for the biomechanical energy harvesting system is developed to describe its dynamic and electrical characteristics, and a prototype is fabricated and tested under diverse conditions. The experimental results are in good agreement with the simulation trends, validating the effectiveness of the theoretical model. A test subject running at 8 km/h for 90 seconds can successfully power a smartphone for 20 seconds, demonstrating the viability of self-powered applications. This mechanically intelligent biomechanical energy harvesting method holds a promising solution for the sustainable power supply for wearable electronic devices.