3D Printed Graphene-Based Self-Powered Strain Sensors for Smart Tires in Autonomous Vehicles

Deepam Maurya; Seyedmeysam Khaleghian; Rammohan Sriramdas; Prashant Kumar; Ravi Kishore; Min Kang; Vireshwar Kumar; Hyun-Cheol Song; Seul-Yi Lee; Yongke Yan; Jung-Min Park; Saied Taheri; Shashank Priya

doi:10.1038/s41467-020-19088-y

3D Printed Graphene-Based Self-Powered Strain Sensors for Smart Tires in Autonomous Vehicles

Deepam Maurya, Seyedmeysam Khaleghian, Rammohan Sriramdas, Prashant Kumar, Ravi Kishore, Min Kang, Vireshwar Kumar, Hyun-Cheol Song, Seul-Yi Lee, Yongke Yan, Jung-Min Park, Saied Taheri, Shashank Priya

Building Technologies and Science Center

Research output: Contribution to journal › Article › peer-review

99 Scopus Citations

Abstract

The transition of autonomous vehicles into fleets requires an advanced control system design that relies on continuous feedback from the tires. Smart tires enable continuous monitoring of dynamic parameters by combining strain sensing with traditional tire functions. Here, we provide breakthrough in this direction by demonstrating tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis. Ink of graphene based material was designed to directly print strain sensor for measuring tire-road interactions under varying driving speeds, normal load, and tire pressure. A secure wireless data transfer hardware powered by a piezoelectric patch is implemented to demonstrate self-powered sensing and wireless communication capability. Combined, this study significantly advances the design and fabrication of cost-effective smart tires by demonstrating practical self-powered wireless strain sensing capability.

Original language	American English
Article number	Article No. 5392
Number of pages	10
Journal	Nature Communications
Volume	11
Issue number	1
DOIs	https://doi.org/10.1038/s41467-020-19088-y https://doi.org/10.1038/s41467-020-19088-y
State	Published - 1 Dec 2020

Bibliographical note

Publisher Copyright:
© 2020, The Author(s).

NREL Publication Number

NREL/JA-5500-77921

Keywords

3D printing
energy harvesting
graphene
smart tires
strain sensor

Access to Document

https://www.nrel.gov/docs/fy21osti/77921.pdf

Cite this

Maurya, D., Khaleghian, S., Sriramdas, R., Kumar, P., Kishore, R., Kang, M., Kumar, V., Song, H.-C., Lee, S.-Y., Yan, Y., Park, J.-M., Taheri, S., & Priya, S. (2020). 3D Printed Graphene-Based Self-Powered Strain Sensors for Smart Tires in Autonomous Vehicles. Nature Communications, 11(1), Article Article No. 5392. https://doi.org/10.1038/s41467-020-19088-y, https://doi.org/10.1038/s41467-020-19088-y

@article{11ba3085d5fc4657977e9ce773d3a355,

title = "3D Printed Graphene-Based Self-Powered Strain Sensors for Smart Tires in Autonomous Vehicles",

abstract = "The transition of autonomous vehicles into fleets requires an advanced control system design that relies on continuous feedback from the tires. Smart tires enable continuous monitoring of dynamic parameters by combining strain sensing with traditional tire functions. Here, we provide breakthrough in this direction by demonstrating tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis. Ink of graphene based material was designed to directly print strain sensor for measuring tire-road interactions under varying driving speeds, normal load, and tire pressure. A secure wireless data transfer hardware powered by a piezoelectric patch is implemented to demonstrate self-powered sensing and wireless communication capability. Combined, this study significantly advances the design and fabrication of cost-effective smart tires by demonstrating practical self-powered wireless strain sensing capability.",

keywords = "3D printing, energy harvesting, graphene, smart tires, strain sensor",

author = "Deepam Maurya and Seyedmeysam Khaleghian and Rammohan Sriramdas and Prashant Kumar and Ravi Kishore and Min Kang and Vireshwar Kumar and Hyun-Cheol Song and Seul-Yi Lee and Yongke Yan and Jung-Min Park and Saied Taheri and Shashank Priya",

note = "Publisher Copyright: {\textcopyright} 2020, The Author(s).",

year = "2020",

month = dec,

day = "1",

doi = "10.1038/s41467-020-19088-y",

language = "American English",

volume = "11",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature Research",

number = "1",

}

Maurya, D, Khaleghian, S, Sriramdas, R, Kumar, P, Kishore, R, Kang, M, Kumar, V, Song, H-C, Lee, S-Y, Yan, Y, Park, J-M, Taheri, S & Priya, S 2020, '3D Printed Graphene-Based Self-Powered Strain Sensors for Smart Tires in Autonomous Vehicles', Nature Communications, vol. 11, no. 1, Article No. 5392. https://doi.org/10.1038/s41467-020-19088-y, https://doi.org/10.1038/s41467-020-19088-y

TY - JOUR

T1 - 3D Printed Graphene-Based Self-Powered Strain Sensors for Smart Tires in Autonomous Vehicles

AU - Maurya, Deepam

AU - Khaleghian, Seyedmeysam

AU - Sriramdas, Rammohan

AU - Kumar, Prashant

AU - Kishore, Ravi

AU - Kang, Min

AU - Kumar, Vireshwar

AU - Song, Hyun-Cheol

AU - Lee, Seul-Yi

AU - Yan, Yongke

AU - Park, Jung-Min

AU - Taheri, Saied

AU - Priya, Shashank

PY - 2020/12/1

Y1 - 2020/12/1

N2 - The transition of autonomous vehicles into fleets requires an advanced control system design that relies on continuous feedback from the tires. Smart tires enable continuous monitoring of dynamic parameters by combining strain sensing with traditional tire functions. Here, we provide breakthrough in this direction by demonstrating tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis. Ink of graphene based material was designed to directly print strain sensor for measuring tire-road interactions under varying driving speeds, normal load, and tire pressure. A secure wireless data transfer hardware powered by a piezoelectric patch is implemented to demonstrate self-powered sensing and wireless communication capability. Combined, this study significantly advances the design and fabrication of cost-effective smart tires by demonstrating practical self-powered wireless strain sensing capability.

AB - The transition of autonomous vehicles into fleets requires an advanced control system design that relies on continuous feedback from the tires. Smart tires enable continuous monitoring of dynamic parameters by combining strain sensing with traditional tire functions. Here, we provide breakthrough in this direction by demonstrating tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis. Ink of graphene based material was designed to directly print strain sensor for measuring tire-road interactions under varying driving speeds, normal load, and tire pressure. A secure wireless data transfer hardware powered by a piezoelectric patch is implemented to demonstrate self-powered sensing and wireless communication capability. Combined, this study significantly advances the design and fabrication of cost-effective smart tires by demonstrating practical self-powered wireless strain sensing capability.

KW - 3D printing

KW - energy harvesting

KW - graphene

KW - smart tires

KW - strain sensor

UR - http://www.scopus.com/inward/record.url?scp=85093930522&partnerID=8YFLogxK

U2 - 10.1038/s41467-020-19088-y

DO - 10.1038/s41467-020-19088-y

M3 - Article

C2 - 33106481

AN - SCOPUS:85093930522

SN - 2041-1723

VL - 11

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - Article No. 5392

ER -

3D Printed Graphene-Based Self-Powered Strain Sensors for Smart Tires in Autonomous Vehicles

Abstract

Bibliographical note

NREL Publication Number

Keywords

Access to Document

Other files and links

Fingerprint

Cite this