Xiaoli Tang, M. Longden, Yu Shi, Boyue Chen, Rabiya Farooq, Harry Lees, Yu Jia
{"title":"Towards Power Neutral Wireless Sensors: a Real-Time Wheel Alignment Monitoring System","authors":"Xiaoli Tang, M. Longden, Yu Shi, Boyue Chen, Rabiya Farooq, Harry Lees, Yu Jia","doi":"10.1109/PowerMEMS54003.2021.9658408","DOIUrl":null,"url":null,"abstract":"Misalignment of vehicle wheels, especially for those heavy good vehicles (HGVs), will lead to rapid irregular wear on both tires and roads, which is extremely harmful to safe operation, human health and the environment. The traditional wheel alignment techniques mainly focus on wheel alignment inspection and adjustment at the maintenance center. However, as the uncertainty of external influence factors, the degree of wear caused by misalignment cannot be estimated. Therefore, we designed a low-power wireless wheel alignment monitoring system to monitor the wheel alignment condition in real time and long time and remind the customers to perform maintenance timely. For applications in specific scenarios and extension of battery service life, a dual wake-up strategy was proposed to wake the processor from a deep sleep state. The current of the designed system is low to 9.13μA when the processor sleeps, but a real-time clock (RTC) is enabled. A 1000mAh battery with a nominal voltage of 3.7V can work for nearly 5 years if the data is collected twice a day with the proposed dual wake-up strategy. Importantly, with the assistance of energy harvesting, it has the potential to realize a fully autonomous condition monitoring system in the future.","PeriodicalId":165158,"journal":{"name":"2021 IEEE 20th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS)","volume":"46 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 20th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PowerMEMS54003.2021.9658408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Misalignment of vehicle wheels, especially for those heavy good vehicles (HGVs), will lead to rapid irregular wear on both tires and roads, which is extremely harmful to safe operation, human health and the environment. The traditional wheel alignment techniques mainly focus on wheel alignment inspection and adjustment at the maintenance center. However, as the uncertainty of external influence factors, the degree of wear caused by misalignment cannot be estimated. Therefore, we designed a low-power wireless wheel alignment monitoring system to monitor the wheel alignment condition in real time and long time and remind the customers to perform maintenance timely. For applications in specific scenarios and extension of battery service life, a dual wake-up strategy was proposed to wake the processor from a deep sleep state. The current of the designed system is low to 9.13μA when the processor sleeps, but a real-time clock (RTC) is enabled. A 1000mAh battery with a nominal voltage of 3.7V can work for nearly 5 years if the data is collected twice a day with the proposed dual wake-up strategy. Importantly, with the assistance of energy harvesting, it has the potential to realize a fully autonomous condition monitoring system in the future.