Development of tire condition monitoring system (TCMS) based on MEMS sensors

Tjiu, Willy; Ahanchian, A.; Majlis, B.Y.

doi:10.1109/smelec.2004.1620903

Cited by 9 publications

(5 citation statements)

References 1 publication

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“…Furthermore, the interest in tyre pressure monitoring systems (TPMS) for the automotive industry has increased in recent years. First generation of TPMS was based on MEMS pressure sensors and battery-powered active transmitters positioned in every wheel [8]. The use of SAW sensors offers the most promising solution for batteryless second generation TPMS [9,10].…”

Section: Introductionmentioning

confidence: 99%

High precision pressure sensors based on SAW devices in the GHz range

Rodríguez-Madrid

Iriarte

Williams

et al. 2013

Sensors and Actuators A: Physical

100

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In this paper, an AIN/free-standing nanocrystalline diamond (NCD) system is proposed in order to process high frequency surface acoustic wave (SAW) resonators for sensing applications. The main problem of synthetic diamond is its high surface roughness that worsens the sputtered AIN quality and hence the device response. In order to study the feasibility of this structure, AIN films from 150 nm up to 1200 nm thick have been deposited on free-standing NCD. We have then analysed the influence of the AIN layer thickness on its crystal quality and device response. Optimized thin films of 300 nm have been used to fabricate of one-port SAW resonators operating in the 10-14 GHz frequency range. A SAW based sensor pressure with a sensibility of 0.33 MHz/bar has been fabricated.

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Section: Introductionmentioning

confidence: 99%

High precision pressure sensors based on SAW devices in the GHz range

Rodríguez-Madrid

Iriarte

Williams

et al. 2013

Sensors and Actuators A: Physical

100

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“…The tread element deformation is measured by the sensor as a position change of a magnet relative to four crosswisely arranged Hall sensors. Tjiu et al [71] used microelectromechanical system (MEMS) sensors, including a pressure sensor, accelerometer and temperature sensor for a tire condition monitoring system. Yi [72] used polyvinylidene fluoride (PVDF)-based sensors to measure the tread deformation.…”

Section: Advanced Intelligent Tiresmentioning

confidence: 99%

Wireless Monitoring of Automobile Tires for Intelligent Tires

Matsuzaki

Todoroki

2008

Sensors

103

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This review discusses key technologies of intelligent tires focusing on sensors and wireless data transmission. Intelligent automobile tires, which monitor their pressure, deformation, wheel loading, friction, or tread wear, are expected to improve the reliability of tires and tire control systems. However, in installing sensors in a tire, many problems have to be considered, such as compatibility of the sensors with tire rubber, wireless transmission, and battery installments. As regards sensing, this review discusses indirect methods using existing sensors, such as that for wheel speed, and direct methods, such as surface acoustic wave sensors and piezoelectric sensors. For wireless transmission, passive wireless methods and energy harvesting are also discussed.

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“…Moreover, the NHTSA presented tire pressure, temperature, and tread depth as factors that could be perceived before a tire-related accident occurred. In particular, the tire tread depth is related to maintaining the appropriate grip force and braking force of a vehicle during driving [9], [10]. If tires are severely worn, handling the vehicle can become difficult because of traction loss during driving on wet or snowy roads, and there is a possibility of tire blowouts or fires [11], [12].…”

Section: Introductionmentioning

confidence: 99%

Experimental Evaluation of Tire Tread Wear Detection Using Machine Learning in Real-Road Driving Conditions

et al. 2023

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The accurate detection of tire tread wear plays an important role in preventing tire-related accidents. In previous studies, tire wear detection is performed by interpreting mathematical models and tire characteristics. However, this approach may not accurately reflect the real driving environment. In this study, we propose a tire tread wear detection system that utilizes machine learning to provide accurate results under real-road driving conditions. The proposed system comprises (1) an intelligent tire that samples the measured acceleration signals and processes them in a dataset, (2) a preprocessing component that extracts features from the collected data according to the degree of wear, and (3) a detection component that uses a deep neural network to classify the degree of wear. To implement the proposed system in a vehicle, we designed an acceleration-based intelligent tire that can transmit data over wireless networks. At speeds between 30 and 80 km/h, the proposed system was experimentally demonstrated to achieve an accuracy of 95.51% for detecting tire tread wear under real-road driving conditions. Moreover, this system uses only preprocessed acceleration signals and machine-learning algorithms, without requiring complex physical models and numerical analyses.

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Development of tire condition monitoring system (TCMS) based on MEMS sensors

Cited by 9 publications

References 1 publication

High precision pressure sensors based on SAW devices in the GHz range

High precision pressure sensors based on SAW devices in the GHz range

Wireless Monitoring of Automobile Tires for Intelligent Tires

Experimental Evaluation of Tire Tread Wear Detection Using Machine Learning in Real-Road Driving Conditions

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