A Sustainable Free-Standing Triboelectric Nanogenerator Made of Flexible Composite Film for Brake Pattern Recognition in Automobiles

被引:2
|
作者
Kim, Nayoon [1 ]
Hwang, Subhin [1 ]
Panda, Swati [1 ]
Hajra, Sugato [1 ]
Jo, Junghun [1 ]
Song, Heewon [1 ]
Belal, Mohamed A. [1 ]
Vivekananthan, Venkateswaran [2 ]
Panigrahi, Basanta Kumar [3 ]
Achary, P. Ganga Raju [4 ]
Kim, Hoe Joon [1 ]
机构
[1] Daegu Gyeongbuk Inst Sci & Technol, Dept Robot & Mechatron Engn, Daegu 42988, South Korea
[2] Koneru Lakshmaiah Educ Fdn, Ctr Flexible Elect, Dept Elect & Commun Engn, Vijayawada 522302, Andhra Pradesh, India
[3] Siksha O Anusandhan Univ, Dept Elect Engn, Bhubaneswar 751030, India
[4] Siksha O Anusandhan Univ, Dept Chem, Bhubaneswar 751030, India
基金
新加坡国家研究基金会;
关键词
automobile sensor; brake pattern; free-standing; nanogenerator; triboelectric; VEHICLES; SYSTEM;
D O I
10.1002/marc.202400431
中图分类号
O63 [高分子化学(高聚物)];
学科分类号
070305 ; 080501 ; 081704 ;
摘要
In recent years, the automotive industry has made significant progress in integrating multifunctional sensors to improve vehicle performance, safety, and efficiency. As the number of integrated sensors keeps increasing, there is a growing interest in alternative energy sources. Specifically, self-powered sensor systems based on energy harvesting are drawing much attention, with a main focus on sustainability and reducing reliance on typical batteries. This paper demonstrates the use of triboelectric nanogenerators (TENGs) in a computer mouse for efficient energy harvesting and in automobile braking systems for safety applications using SrBi2Ta2O9 (SBTO) perovskite, blended PDMS composite operating in free-standing mode with an interdigitated patterned aluminum electrode. This self-powered sensor is capable of distinguishing between normal and abnormal braking patterns using digital signal processing techniques. It is noteworthy that the addition of 15% wt. of the SBTO in PDMS composite-based TENG delivered 13.5 V, 45 nA, and an output power of 0.98 mu W. This new combination of energy harvesting and safety applications enables real-time monitoring and predictive maintenance in the automotive industry.
引用
收藏
页数:10
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