Because of access limitations inside the tire, the use of batteries for sensor nodes embedded inside an intelligent tire is not practical. The high vibration levels inside a tire have the potential to generate electrical power using vibration-based energy-harvesting techniques. In this article, the feasibility of using an inertial vibrating energy harvester unit to power a sensor module for tire use is assessed. To predict the electrical power output of the generator, a generic analytical model based on the transfer of energy within the system has been derived. The vibration measurements taken from the test conducted using accelerometers embedded in the tire have been applied as an excitation to the model to predict the power output for a device of suitable dimensions and to study the feasibility of this concept. For the tire applications, a special compact harvester design has been proposed that is able to withstand large shocks and vibrations. Suitable mathematical models for different harvester configurations have been developed to identify the best configuration suited for use inside a tire. The harvester unit demonstrates power generation over a wide speed range and provides a distinct advantage in cost and flexibility of installation while extending the lifetime of the power supply for sensor data acquisition and communication. Results indicate the viability of the procedure outlined in the article.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Piezoelectric Vibration-Based Energy Harvesters for Next-Generation Intelligent Tires


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2013


    Format / Umfang :

    32 Seiten, Bilder, Tabellen, 19 Quellen



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch





    Deep Learning-Based Optimization of Piezoelectric Vibration Energy Harvesters

    Menon, Abhilash M. / Kopparthi, Tanmayee R. / Omprakash, Pravan et al. | AIAA | 2022


    Deep Learning-Based Optimization of Piezoelectric Vibration Energy Harvesters

    Menon, Abhilash M. / Kopparthi, Tanmayee R. / Omprakash, Pravan et al. | TIBKAT | 2022


    Nanostructured piezoelectric energy harvesters

    Briscoe, Joe / Dunn, Steve | TIBKAT | 2014