Macro Fiber Composite (MFC) is extensively utilized in aviation, aerospace, civilian, and military domains owing to its high piezoelectricity, flexibility, and minimal loss. Nevertheless, contemporary research on MFC sensors has predominantly focused on material applications, with a conspicuous lack of systematic investigation into the simulation and modeling of MFC sensor devices. In this study, three models—namely, a Representative Volume Element (RVE) model, a Direct model, and a Hybrid model—have been introduced to analyze the finite element models of MFC, encompassing scales ranging from microscopic to macroscopic.
On one hand, the equivalent RVE model facilitates an understanding of the internal electric field distribution within MFC, thereby establishing a theoretical foundation for force-electric coupling. On the other hand, the application of the Direct and Hybrid models aligns with the boundary conditions in MFC applications, laying a theoretical groundwork for the stress sensing and resonance sensing mechanisms of MFC. These models constitute effective tools for predicting the sensing performance of MFC smart element sensors. The simulation outcomes indicate that resonant sensors exhibit significantly superior performance compared to patch sensors. Under conditions where the excitation acceleration is 5 m/s² and the cantilever substrate length is 80 mm, the simulated resonant frequency of the MFC resonant sensor is 67 Hz, with an output voltage of 4.17 V. Experimental results corroborate these findings, reporting a resonant frequency of 74 Hz and an output voltage of 3.59 V for the MFC sensor. The notable consistency between the simulation and experimental results for the MFC sensor is worth highlighting. Furthermore, the MFC sensor demonstrates exceptional sensing sensitivity at low frequencies, with a sensitivity of 7.35 V/g. It is evident that MFC exhibits remarkable sensing characteristics at low-frequency resonance, and the three finite element models developed in this research are proficient in predicting the sensing performance of MFC sensors, thereby ensuring reliable performance prediction for such sensors.