{"title":"Attack-resilient energy management architecture of hybrid emergency power system for more-electric aircrafts","authors":"M. Kamal, Jin Wei","doi":"10.1109/ISGT.2017.8085993","DOIUrl":null,"url":null,"abstract":"This paper proposes an attack-resilient energy management architecture for a hybrid emergency power system of More-Electric Aircrafts (MEAs). Our proposed architecture develops an Adaptive Neuro-Fuzzy Interference System (ANFIS)-based method to evaluate the integrity of the power output of the fuel-cell in the fuel-cell based hybrid auxiliary power unit (APU), which is vulnerable to the cyber-attacks and critical for the effective energy management and emergency control. Our ANFIS-based method achieves the integrity evaluation by leveraging the real-time measures on the State of Charge (SOC) of the battery, power output of the ultra-capacitor and the load profile. In our simulation, we evaluate the performance of our proposed ANFIS-based method to support the integrity of the Energy Management Strategies (EMSs) used in hybrid emergency power system for more-electric aircrafts by using MATLAB/Simulink. Our simulation results illustrate the effectiveness of our proposed method in effectively evaluating the integrity of critical data and achieving resilient control.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGT.2017.8085993","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper proposes an attack-resilient energy management architecture for a hybrid emergency power system of More-Electric Aircrafts (MEAs). Our proposed architecture develops an Adaptive Neuro-Fuzzy Interference System (ANFIS)-based method to evaluate the integrity of the power output of the fuel-cell in the fuel-cell based hybrid auxiliary power unit (APU), which is vulnerable to the cyber-attacks and critical for the effective energy management and emergency control. Our ANFIS-based method achieves the integrity evaluation by leveraging the real-time measures on the State of Charge (SOC) of the battery, power output of the ultra-capacitor and the load profile. In our simulation, we evaluate the performance of our proposed ANFIS-based method to support the integrity of the Energy Management Strategies (EMSs) used in hybrid emergency power system for more-electric aircrafts by using MATLAB/Simulink. Our simulation results illustrate the effectiveness of our proposed method in effectively evaluating the integrity of critical data and achieving resilient control.