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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
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Total Authors : 21282
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| Paper Title: | Artificial intelligence-powered electric vehicle`s battery management system with IOT |
| Authors Name: | T. Jayabharathi , R. Manjupriya , A. Sowmya , Dr. R. Manikandan , Dr. P. Selvakumar |
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| Author Reg. ID: |
IJRTI_187588
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| Published Paper Id: | IJRTI2307068 |
| Published In: | Volume 8 Issue 7, July-2023 |
| DOI: | |
| Abstract: | As a key part of electric vehicles, batteries are the maximum important parts of electric vehicles because of their charging and discharging functions. They supply the electricity that drives the vehicle's motor. A vehicle powered by electricity could not function without batteries. The vehicle fails to operate smoothly if the batteries aren't functioning properly. The current and voltage variations affect the battery system. So we cannot predict the accurate voltage and current measurement. This research, to monitor and enhance the performance of battery energy management systems (BEMS) with the help of IoT (Internet of Things) and AI (Artificial intelligence) and further explore managing the battery in electric vehicles. Lithium-ion battery used in this system because of greater energy density compared to other conventional batteries. The fact that batteries are an expensive part of an electric vehicle presents a big potential for AI-Powered Cloud Services to improve forecasts of the battery's State of Health (SOH) and State of Charge (SOC) for cost and durability. A cloud-based AI-powered system can adjust to ongoing changes in battery health brought on by operating situations and return updated data to the BMS for continuously enhanced management decisions. The neural network algorithm is built using a Python script. Node-RED designed the user interface and login for the web server. Concerning embedded devices, sensors, and mobile apps, the Internet of Things plays a significant role. MQTT is a reasonably lightweight messaging protocol. |
| Keywords: | Battery Management System (BMS), Embedded System, IoT, Notification, Messaging Protocol |
| Cite Article: | "Artificial intelligence-powered electric vehicle`s battery management system with IOT", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 7, page no.455 - 461, July-2023, Available :http://www.ijrti.org/papers/IJRTI2307068.pdf |
| Downloads: | 000205149 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2307068
Registration ID:187588
Published In: Volume 8 Issue 7, July-2023
DOI (Digital Object Identifier):
Page No: 455 - 461 Country: SALEM, Tamilnadu, India Research Area: Electrical Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2307068 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2307068 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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