A Novel Multipurpose Fuel Sensor for Efficient Estimation of Fuel-Level, Dual-Axis Inclination, and Two-Component Fuel Composition

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Narayanan P. P.;Sreenath Vijayakumar
{"title":"A Novel Multipurpose Fuel Sensor for Efficient Estimation of Fuel-Level, Dual-Axis Inclination, and Two-Component Fuel Composition","authors":"Narayanan P. P.;Sreenath Vijayakumar","doi":"10.1109/JSEN.2025.3542559","DOIUrl":null,"url":null,"abstract":"Modern automotive technologies necessitate monitoring of a wide variety of physical parameters, such as fuel level, dual-axis vehicle inclination, and fuel composition. Traditionally, this is achieved through the incorporation of numerous sensors, resulting in increased complexity, expense, and bulkiness. This article proposes a novel solution by designing a single capacitive-based sensor system capable of simultaneously monitoring fuel level, dual-axis vehicle inclination, and fuel mixture composition. In contrast to current fuel sensing architectures, the proposed sensor eliminates the need for movable parts and is immune to fuel type. This makes it compatible with any gasoline-powered combustion engine automobiles. The proposed sensor incorporates a dual-axis inclination measurement, which is essential for accurate level measurement, and ensuring vehicle safety. In addition, due to the current availability of a wide variety of fuel mixtures in the market, knowledge of fuel composition is critical in any vehicle for optimizing engine performance. Implementation of all these features through a single sensor eliminates the requirement for supplementary components, resulting in a reduction in both hardware implementation expenses and system complexity. This is the first of its kind such a single sensing scheme is reported. The prototype sensor demonstrates high linearity of 0.43% and 0.88% for level and inclination measurements, respectively. The sensor prototype was also tested with ethanol-petrol fuel mixtures and exhibits a worst case linearity error of 2.43% for concentrations ranging from E0-petrol to E100-petrol. The developed sensor promises a feasible and economically efficient solution for integration into contemporary automobiles.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 7","pages":"12109-12118"},"PeriodicalIF":4.3000,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/10902073/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

Modern automotive technologies necessitate monitoring of a wide variety of physical parameters, such as fuel level, dual-axis vehicle inclination, and fuel composition. Traditionally, this is achieved through the incorporation of numerous sensors, resulting in increased complexity, expense, and bulkiness. This article proposes a novel solution by designing a single capacitive-based sensor system capable of simultaneously monitoring fuel level, dual-axis vehicle inclination, and fuel mixture composition. In contrast to current fuel sensing architectures, the proposed sensor eliminates the need for movable parts and is immune to fuel type. This makes it compatible with any gasoline-powered combustion engine automobiles. The proposed sensor incorporates a dual-axis inclination measurement, which is essential for accurate level measurement, and ensuring vehicle safety. In addition, due to the current availability of a wide variety of fuel mixtures in the market, knowledge of fuel composition is critical in any vehicle for optimizing engine performance. Implementation of all these features through a single sensor eliminates the requirement for supplementary components, resulting in a reduction in both hardware implementation expenses and system complexity. This is the first of its kind such a single sensing scheme is reported. The prototype sensor demonstrates high linearity of 0.43% and 0.88% for level and inclination measurements, respectively. The sensor prototype was also tested with ethanol-petrol fuel mixtures and exhibits a worst case linearity error of 2.43% for concentrations ranging from E0-petrol to E100-petrol. The developed sensor promises a feasible and economically efficient solution for integration into contemporary automobiles.
求助全文
约1分钟内获得全文 求助全文
来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信