Autonomous wireless sensor networks (WSNs) have been identified as playing a crucial role in monitoring applications in hard-to-access and industrial environments. This study presents a comprehensive investigation of multi-piezoelectric configurations, including series, parallel, and hybrid configurations, for vibration-based energy harvesting in wake-up receiver (WuRx) nodes, with a particular focus on the gearbox of bucket wheel excavators. A novel analytical model has been developed to predict the electrical behaviour and power output of identical piezoelectric elements under various connection schemes and operating conditions. The experimental validation of the model yielded maximum deviations of 14% in the load power and 9% in the impedance estimates, thereby underscoring the model's reliability. A total of ten distinct configurations were evaluated, each comprising four piezoelectric elements. The four-in-parallel (0S4P) arrangement was found to demonstrate superior performance by enabling supercapacitor power peaks of 75mW, representing the peak instantaneous power stored in the capacitor and sustained over 240ms. These outcomes emphasise the potency of optimised piezoelectric configurations in facilitating autonomous, self-sufficient WuRx-enabled sensor nodes. The findings offer critical insights for designing resilient, energy-autonomous WSNs tailored for predictive maintenance and monitoring in high-vibration industrial environments.
Schott et al. (2025) studied this question.