Kavitha Kumari.K.S, L. Chitra, Jibin M Abraham, Noyal Joseph, Yedu Krishnan T.K
{"title":"The Role of IOT & AI in Battery Management of Electric Vehicles","authors":"Kavitha Kumari.K.S, L. Chitra, Jibin M Abraham, Noyal Joseph, Yedu Krishnan T.K","doi":"10.1109/IConSCEPT57958.2023.10170275","DOIUrl":null,"url":null,"abstract":"Electric vehicle (EV) performance is influenced by a variety of parameters like battery life, cell voltage and health, safety and charging-discharging speeds. In EVs, the battery management is a crucial task which facilitates the effective functioning of battery. This paper suggests an improved monitoring of battery State-Of-Charge (SOC) using Internet of Things (IOT) and Artificial Intelligence (AI). This paper focus on a problem for researchers in order to ensure the safety of cars and users by exactly estimating SOC, monitoring and spotting in-time breakdowns of the rechargeable batteries of electric vehicles respectively. The voltage obtained from the Photovoltaic (PV) system is improved by the Boost integrated fly back rectifier energy DC-DC (BIFRED) converter which is controlled by an cascaded ANFIS controller. The SOC of the battery is monitored by Recurrent Neural Networks (RNN) and the data is stored in IOT. The IOT allows for the continuous monitoring and transmission of all battery-related data to the cloud, enabling for the capture of real-time battery information. Thus this paper clearly focus on monitoring and estimating time breakdown of the rechargeable batteries of vehicles.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IConSCEPT57958.2023.10170275","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
Electric vehicle (EV) performance is influenced by a variety of parameters like battery life, cell voltage and health, safety and charging-discharging speeds. In EVs, the battery management is a crucial task which facilitates the effective functioning of battery. This paper suggests an improved monitoring of battery State-Of-Charge (SOC) using Internet of Things (IOT) and Artificial Intelligence (AI). This paper focus on a problem for researchers in order to ensure the safety of cars and users by exactly estimating SOC, monitoring and spotting in-time breakdowns of the rechargeable batteries of electric vehicles respectively. The voltage obtained from the Photovoltaic (PV) system is improved by the Boost integrated fly back rectifier energy DC-DC (BIFRED) converter which is controlled by an cascaded ANFIS controller. The SOC of the battery is monitored by Recurrent Neural Networks (RNN) and the data is stored in IOT. The IOT allows for the continuous monitoring and transmission of all battery-related data to the cloud, enabling for the capture of real-time battery information. Thus this paper clearly focus on monitoring and estimating time breakdown of the rechargeable batteries of vehicles.