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Energy harvesting and strain sensing in smart tire for next generation autonomous vehicles
•Developed high energy density harvester-cum-sensor to power wireless data transfer.•The generated energy from tire strain harvester was enough to directly power 78 LEDs.•A mathematical model for tire-road interaction and piezoelectric response.•Real environment test for sensing tire-road interactio...
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Published in: | Applied energy 2018-12, Vol.232, p.312-322 |
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Main Authors: | , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •Developed high energy density harvester-cum-sensor to power wireless data transfer.•The generated energy from tire strain harvester was enough to directly power 78 LEDs.•A mathematical model for tire-road interaction and piezoelectric response.•Real environment test for sensing tire-road interaction under different variables.•Demonstrated the self-powered smart tire sensor for autonomous vehicles.
We demonstrate the feasibility of the strain energy harvesting from the automobile tires, powering wireless data transfer with enhanced frame rates, and self-powered strain sensing. For this, we used a flexible organic piezoelectric material for continuous power generation and monitoring of the variable strain experienced by a tire under different driving conditions. Power output of ∼580 µW at 16 Hz (∼112 km/h) from the energy-harvester and mounted on a section of a tire, is sufficient to power 78 LEDs. We further demonstrate that the stored energy was sufficient to power the wireless system that transmits tire deformation data with an enhanced frame rate to control system of a vehicle. Using sensors mounted on a tire of a mobile test rig, measurements were conducted on different terrains with varying normal loads and speeds to quantify the sensitivity and self-powered sensing operation. These results provide a foundation for self-powered real-time sensing and energy efficient data transfer in autonomous vehicles. |
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ISSN: | 0306-2619 1872-9118 |
DOI: | 10.1016/j.apenergy.2018.09.183 |