Analysis of piezoelectric harvester with multi-array configuration for ultra-low power sensor nodes

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.

Authors

Publication Details

Journal
PubData
Published
2025-08-25
DOI
https://doi.org/10.48548/pubdata-3131
Primary Topic
Innovative Energy Harvesting Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of piezoelectric harvester with multi-array configuration for ultra-low power sensor nodes

Florian Strakosch, Robert Fromm, Ghada Bouattour, Lydia Schott et al.
PubData
Innovative Energy Harvesting Technologies
article

Analysis of piezoelectric harvester with multi-array configuration for ultra-low power sensor nodes

Florian Strakosch, Robert Fromm, Ghada Bouattour, Lydia Schott, Faouzi Derbel, Olfa Kanoun
article en

Abstract

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.

PubData
Affordable and clean energy
Openalex Percentile: Top 38%
Innovative Energy Harvesting Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.