{"title":"通过估算氧气浓度量化 PEM 燃料电池氢气泄漏的扩展卡尔曼滤波器","authors":"Alireza Beigi , Wesley Romey , Krishna Vijayaraghavan","doi":"10.1016/j.ijhydene.2024.06.094","DOIUrl":null,"url":null,"abstract":"<div><p>Hydrogen transfer leaks are one of the most important life-limiting faults in polymer electrolyte membrane fuel cells (PEMFCs). Hydrogen transfer leaks result in a reduction in the amount of oxygen available in the cathode (air) channel, with large leaks resulting in oxygen starvation and hydrogen emission. This paper aims to develop an adaptive extended Kalman filter (EKF) to estimate the unknown oxygen concentration, which is then used to infer hydrogen leaks. To this end, the paper first develops the lumped model of the fuel cell from a pseudo-2D model of a fuel cell. Next, a (non-adaptive) EKF is developed to estimate the fuel cell states under both normal and oxygen-starved conditions. The adaptive EKF is then implemented by adding the unknown hydrogen leak to the list of estimated states. Finally, the paper demonstrates the efficacy of the proposed adaptive EKF by using it to accurately estimate unknown hydrogen leaks in a high-fidelity virtual fuel cell under excessively noisy conditions.</p></div>","PeriodicalId":337,"journal":{"name":"International Journal of Hydrogen Energy","volume":null,"pages":null},"PeriodicalIF":8.1000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Extended kalman filter for quantifying hydrogen leaks in PEM fuel cells by estimating oxygen concentration\",\"authors\":\"Alireza Beigi , Wesley Romey , Krishna Vijayaraghavan\",\"doi\":\"10.1016/j.ijhydene.2024.06.094\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Hydrogen transfer leaks are one of the most important life-limiting faults in polymer electrolyte membrane fuel cells (PEMFCs). Hydrogen transfer leaks result in a reduction in the amount of oxygen available in the cathode (air) channel, with large leaks resulting in oxygen starvation and hydrogen emission. This paper aims to develop an adaptive extended Kalman filter (EKF) to estimate the unknown oxygen concentration, which is then used to infer hydrogen leaks. To this end, the paper first develops the lumped model of the fuel cell from a pseudo-2D model of a fuel cell. Next, a (non-adaptive) EKF is developed to estimate the fuel cell states under both normal and oxygen-starved conditions. The adaptive EKF is then implemented by adding the unknown hydrogen leak to the list of estimated states. Finally, the paper demonstrates the efficacy of the proposed adaptive EKF by using it to accurately estimate unknown hydrogen leaks in a high-fidelity virtual fuel cell under excessively noisy conditions.</p></div>\",\"PeriodicalId\":337,\"journal\":{\"name\":\"International Journal of Hydrogen Energy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":8.1000,\"publicationDate\":\"2024-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Hydrogen Energy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0360319924022936\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Hydrogen Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360319924022936","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
Extended kalman filter for quantifying hydrogen leaks in PEM fuel cells by estimating oxygen concentration
Hydrogen transfer leaks are one of the most important life-limiting faults in polymer electrolyte membrane fuel cells (PEMFCs). Hydrogen transfer leaks result in a reduction in the amount of oxygen available in the cathode (air) channel, with large leaks resulting in oxygen starvation and hydrogen emission. This paper aims to develop an adaptive extended Kalman filter (EKF) to estimate the unknown oxygen concentration, which is then used to infer hydrogen leaks. To this end, the paper first develops the lumped model of the fuel cell from a pseudo-2D model of a fuel cell. Next, a (non-adaptive) EKF is developed to estimate the fuel cell states under both normal and oxygen-starved conditions. The adaptive EKF is then implemented by adding the unknown hydrogen leak to the list of estimated states. Finally, the paper demonstrates the efficacy of the proposed adaptive EKF by using it to accurately estimate unknown hydrogen leaks in a high-fidelity virtual fuel cell under excessively noisy conditions.
期刊介绍:
The objective of the International Journal of Hydrogen Energy is to facilitate the exchange of new ideas, technological advancements, and research findings in the field of Hydrogen Energy among scientists and engineers worldwide. This journal showcases original research, both analytical and experimental, covering various aspects of Hydrogen Energy. These include production, storage, transmission, utilization, enabling technologies, environmental impact, economic considerations, and global perspectives on hydrogen and its carriers such as NH3, CH4, alcohols, etc.
The utilization aspect encompasses various methods such as thermochemical (combustion), photochemical, electrochemical (fuel cells), and nuclear conversion of hydrogen, hydrogen isotopes, and hydrogen carriers into thermal, mechanical, and electrical energies. The applications of these energies can be found in transportation (including aerospace), industrial, commercial, and residential sectors.