International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 2 (March-April 2025) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 7 Issue 2
March-April 2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

AI-Based Optimization of Battery Management Systems for Enhanced Electric Aircraft Efficiency

Author(s) Yashi Garg
Country India
Abstract The aviation industry's shift towards sustainability has brought electric aircraft to the forefront as an eco-friendly alternative to traditional fossil-fuel-powered planes. Central to the efficiency and safety of these aircraft are Battery Management Systems (BMS), which ensure optimal performance through real-time monitoring and advanced energy management. This paper explores the role of AI-based optimization techniques in enhancing BMS functionality, focusing on predictive maintenance, dynamic energy distribution, and fault detection. By leveraging machine, deep, and reinforcement learning, these systems address key challenges such as energy inefficiency, battery degradation, and operational unpredictability. Case studies of electric aviation projects, including Eviation Alice and Rolls-Royce ACCEL, underscore the transformative potential of AI-driven BMS. Additionally, lessons from the electric vehicle industry highlight opportunities for cross-sector innovation. The research concludes that advanced BMS optimization is pivotal for the widespread adoption of electric aircraft, offering significant benefits in energy savings, extended battery life, improved safety, and reduced environmental impact.
Keywords Electric Aircraft, Battery Management Systems (BMS), AI Optimization, Sustainability, Predictive Maintenance, Energy Efficiency, Aviation Technology, Renewable Energy Integration
Field Engineering
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-12-29
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.31365
Short DOI https://doi.org/g82gks
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 2Cover Page Vol 7 Isu 1Cover Page Vol 6 Isu 6

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com