High-precision and multi-modal monitoring of UAV using flexible and durable magnetoelectric sensors based on interface-engineered piezoelectric polyurethane/MnFe2O4 composite

Enhanced interfacial coupling boosts flexible magnetoelectric sensors. • Enables bias-free sensing of motor speed, vibration, and transient impact. • High sensitivity, rapid response, and high accuracy in UAV motor speed monitoring. • Provides integrated structural health monitoring for UAV propulsion systems. With the growth of low-altitude economy, the rapid spread of unmanned aerial vehicles (UAVs) accompanied by frequent safety accidents has created demands for real-time and in-situ monitoring of their propulsion systems, which are responsible for most of the UAV accidents. However, the limited space and energy supply in propulsion systems pose significant challenges to develop miniature size, high flexibility, low power dissipation, and multi-modal integration of sensors. In this work, a flexible magnetoelectric composite sensor (MCS) was developed using an intrinsically piezoelectric polyurethane (SS-PU) matrix and titanate-modified MnFe 2 O 4 (MFO) nanoparticles. The piezoelectric polyurethane is synthesized with phase-separated segments, whose polyester-based soft segments provide numerous C O dipoles to achieve high piezoelectricity, and the aromatic and disulfide hard segments provide mechanical strength. Additionally, by using a titanate coupling agent as a “molecular bridge” for interfacial engineering, the compatibility between the filler and matrix is highly improved, leading to high efficiency in strain transfer between them. As a result, the composite achieved a notable magnetoelectric coupling coefficient of 33.11 mV/cm ∙ Oe, which is nearly two times compared with that of unmodified composites. The optimized MCS shows a high sensitivity of 2.365 mV/kPa, an ultra-fast response time of 4.2 ms, and a tensile strength of 10.1 MPa. In brushless motor rotation speed monitoring, it presents a linear correlation coefficient of R 2  = 0.99998 and an error < 1.5%. Additionally, the composite sensor supports multi-modal sensing of complex flight conditions, including rotation speed, mechanical vibration, and transient impact. This research offers a new approach to building integrated structural health monitoring systems for future intelligent propulsion systems.