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Batteryless IoT Sensing Using Thermoelectric Energy Harvesting from Industrial Motor Waste Heat

Authors: Kamil Bancik; Jaromir Konecny; Martin Stankus; Radim Hercik; Jiri Koziorek; Vytautas Markevičius; Darius Andriukaitis; +1 Authors

Batteryless IoT Sensing Using Thermoelectric Energy Harvesting from Industrial Motor Waste Heat

Abstract

This study presents the design, implementation, and validation of a thermoelectric energy harvesting system that exploits waste heat from an industrial electric motor to power an autonomous wireless sensor device. The proposed prototype integrates a single thermoelectric generator directly onto the motor housing and leverages the built-in cooling fan to maintain a stable thermal gradient of approximately 4–5 °C. Under real factory conditions, the system harvested 6.17 J of energy over 9612 s, sustaining continuous operation and 41 successful Long Range (LoRa) data transmissions with a positive energy balance. Compared with related works, the prototype achieved competitive or superior performance while operating at a lower motor rating of 0.25 kW, highlighting its efficiency relative to system scale. Key innovations include a hybrid DC/DC conversion chain bridging ultra-low input voltages to modern microcontrollers, and an adaptive transmission strategy that ensures predictable energy management and reliable wireless communication. These results demonstrate the feasibility of battery-free sensing in industrial environments and underline the potential of thermoelectric harvesting as a cost-effective, maintenance-free, and environmentally responsible solution for predictive maintenance and Industry 4.0 applications.

Country
Lithuania
Related Organizations
Keywords

energy harvesting, predictive maintenance, waste heat recovery, Engineering, battery-free sensing, thermoelectric generator, Electrical and Electronic Engineering, Industry 4.0, Article

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    1
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Top 10%
Average
Average
Green
gold