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This paper describes a novel low-cost tire pressure monitoring system (TPMS) for bicycles. The system is based on a battery-less near field communication (NFC) tag that integrates a pressure sensor, which is placed between the tire and the inner tube. The system uses no battery since the energy is obtained from the magnetic field induced by the reader in order to establish the communication. The pressure can be read by any NFC-enabled reader such as a smartphone. The pressure sensor is a force-sensing resistor (FSR) that controls the oscillation frequency of a 555 timer-based oscillator. The frequency is read and computed by a microcontroller, and the result is written via $\text{I}^{2}\text{C}$ bus to the memory of a near-field communication integrated circuit (IC), which is read by a commercial smartphone or NFC reader. A prototype is designed on an FR4 substrate which integrates a $12 \times 16$ mm antenna connected to the NFC IC (NT3H211 from NXP). The proposed prototype has a 3D-printed enclosure to protect the components mounted on the surface of the PCB and to protect the tire from punctures. A system for characterizing the read range is presented. The tag requires a minimum magnetic field of $2.9~A_{RMS}/m$ to operate up to a distance of 8 mm between reader and the tire, providing enough power to supply energy to the whole circuitry and to receive the information stored at the NFC IC. The system has been tested with a 59 mm-width mountain bike tire. The sensor has been characterized using a simple polynomial fitting to obtain the pressure from the measurement of the oscillation frequency. An accuracy of 0.1 has been accomplished in the range of 0.5 to 2.2 bar. To test the system, several inflation cycles have been performed and showed that the system presents good repeatability.

Tire pressure monitoring is essential to driving safety. Indirect tire pressure monitoring system (TPMS) is a cost-effective alternative to direct tire pressure monitoring system. Its performance depends on the algorithm for data pre-processing and analysis which is normally complicated, sensitive to initial calibration with limited working range. In this work, four tests were carried out with Baojun 530 with a different deflated tire in each case. Speed data read through ABS CAN bus was analyzed and traditional frequency based method was employed to identify the deflated tire. To simplify the data pre-processing and improve response speed and working range, a new artificial neural network (ANN) based method was also proposed to identify deflated tire based on speed data point collected through antilock brake system (ABS) sensors in tests. A long short-term memory (LSTM) network was developed to locate the deflated tire with an accuracy of 0.83 after training for individual data points. And performance of this method can be further improved by employing a soft voting mechanism with 3 LSTM networks. In proposed ANN based method, benchmark data from properly inflated tire is not required, which makes it a promising solution for multiple deflated tires cases which is challenging for traditional frequency-based method.

This paper presents a new indirect tire pressure monitoring system (TPMS) based on adaptive extended Kalman filtering with unknown input (AEKF-UI) estimation of vehicle suspension systems. The suggested methodology is based on the explicit correlation between tire pressure and tire stiffness and is available in real time. AEKF-UI is used to simultaneously estimate the time-varying parameter (tire stiffness) of vehicle suspension systems and the road roughness using an unknown input estimator. Simulation studies demonstrate that the proposed algorithm can simultaneously estimate tire stiffness (i.e., tire inflation pressure) variation and unknown road roughness input. The feasibility and effectiveness of the proposed estimation algorithm are verified through a laboratory-level experiment. This study offers a potential application for an alternative indirect TPMS and the estimation of unknown road roughness used for automotive controller design.

In recent years, the development of IT systems for fleet monitoring was observed. Tire pressure monitoring systems are constantly improved. Decreased values in tire pressure can cause deformation of tires. Monitoring of tire pressure is an important function in oversized transport trucks. Tire pressure and rolling resistant influence fuel consumption. The purpose of this paper was to determine the impact of tire pressure on fuel consumption in a fleet of trucks with tire pressure monitoring system installed and to determine the impact of other factors that may affect fuel consumption, such as the vehicle weight, brake usage and cruise control usage. The results of the research were developed using a multiple regression model describing the above dependence.

The aim of this study is to explore whether risk perception or anticipated regret is responsible for intensifying the participants’ intention to adopt a tire pressure monitoring system (TPMS) to prevent a tire-related accident, and whether the optimism bias has a moderator effect between risk perception/anticipated regret and intention. With 274 valid questionnaires and PLS-SEM (partial least squares structural equation modeling) analysis, the results indicate a significant positive relationship between risk perception and intention to adopt TPMS, but not between anticipated regret and intention. The moderator effect of optimism bias on risk perception and anticipated regret is not found in the model. The findings will prove useful for public service advertising campaigns by providing a basis for an understanding of the role of cognitive and emotional factors in tire-blowout accident prevention, thereby increasing the motivation for drivers in Taiwan to take advantage of the protection afforded them by using TPMS.

The Tire Pressure Monitoring System (TPMS) displays the state of a tire on a display to inform a driver of the relevant information, by means of a sensor installed on the tire of the vehicle. When the data measured from the tire are wirelessly transmitted to a receiving antenna located in the center of the vehicle, the exact transmission of data is affected by the interference from various external electronic and electrical devices. In this paper, we suggest a minimum variance distortionless response (MVDR) beamformer based on the angle-of-arrival (AOA) vector for suppressing external interference and receiving accurate data. Although the MVDR beamformer effectively suppresses the interference, it has high computational complexity because of the calculation of an autocorrelation matrix. In order to address this issue, we also suggest a generalized sidelobe canceler (GSC) beamformer which does not have the same performance of the interference suppression to MVDR but also has low computational complexity. Since the signal from each tire can cause interference to others, we consider utilizing a unique Gold Code to each tire to minimize intertire interference and reduce power consumption of a battery installed in each tire.

Harvesting kinetic energy from the environment is an ideal alternative to traditional electrochemical batteries as a power source for low-power electronics such as pressure sensors and thermometers. A tire pressure monitoring system (TPMS) is a key device in preventing a flat tire, which is one of the most frequent causes of car accidents. The U.S.A., European Union, and a number of Asian countries are currently considering the implementation of TPMSrelated legislation. Existing TPMS are powered by a battery, but there are drawbacks to these batteries, such as their limited durability and environmental pollution upon disposal. For this reason, this chapter is aimed at developing a TPMS energy harvester in a rotating wheel.

TPMS (Tire Pressure Monitoring System) is becoming an industry standard for driving safety and fuel efficiency. The receiving antenna for TPMS resides in the near field of the sensor antenna and this makes it very difficult to establish a reliable RF link for large vehicles. In the design of receiving antenna, it is paramount to consider the electric field distribution around the vehicle due to transmitter sensor. Through extensive large vehicle simulations, we show optimum locations for the receive antenna and we designed two candidate antennas for best reception. © 2011 IEEE. 2011 30th URSI General Assembly and Scientific Symposium, URSIGASS 2011 -- 13 August 2011 through 20 August 2011 -- Istanbul -- 87252

3D integration is a key solution to the predicted performance problems of future ICs as well as it offers extreme miniaturization and cost-effective fabrication of More than Moore products. Through silicon via (TSV) technologies enable high interconnect performance compared to 3D packaging. At present TSVs are associated with a relatively high fabrication cost, but research world wide strive to bring the cost down to an acceptable level. An example of a 3D System-on-Chip (3D-SOC) technology is to introduce a post backend-of-line TSV process as an optimized technology for heterogeneous system integration. The introduced ICV-SLID process, that combines both TSVs and bonding, enables 3D integration of fabricated devices. Reliability issues related to thermo-mechanical stress caused by the TSV formation and the bonding are considered. 3D-SOC technology choices made to realize a heterogeneous ultra-small IC stack for a wireless tire pressure monitoring system (TPMS) as an automotive application are described.

International audience; Many papers dealing with the TPMS (Tire Pressure Monitoring System) communication mechanisms between sensors (transmitters) and receiver have been published, but most of the work has been focused on the particular effects of the radiofrequency channel [1], the antenna design [2], the communication protocol or the mechanical housing. The full transmission context analysis lacks to the understanding of the observed phenomena, in particular the effects of propagation channel on dynamic reception quality for TPMS. In this study, we propose a step by step analysis by evaluating the influence of each element contributing to the overall performance of the communication process. In the first section, an original space sounding is developed to characterize the radiofrequency channel variation. The second part presents simulations in order to improve the burst reception efficiency: the protocol is investigated versus different channel profiles in order to reduce the rate of lost frames.

An EPC Class-1 Generation-2 C1G2 RFID tag based on Farsens' batteryless sensor technology is proposed to build a Tire Pressure Monitoring System TPMS. Built in a compact printed circuit board format and encapsulated in a cushion gum housing, the tag includes a MS5803-14BA pressure and ambient temperature sensor from Measurements Specialties with an absolute pressure range from 0 bar to 30 bar and ambient temperature range from -40i¾?$$^{\circ }$$i¾?C to 85i¾?$$^{\circ }$$i¾?C. Additionally, the tag includes a thermistor in the tire contact side for contact temperature monitoring. These RFID sensor tags are compatible with commercial UHF RFID readers EPC C1G2. The proposed set-up has been successfully installed and tested in cars. With a 2W ERP setup the battery-less temperature and pressure sensor can communicate to over one meter and a half.