Battery management solutions for li-ion batteries based on artificial intelligence
Yara Khawaja,N Shiva Shankar,Issa Qiqieh,Jafar A. Alzubi,Omar A. Alzubi,M. K. Nallakaruppan,Sanjeevikumar Padmanaban +6 more
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TLDR
In this article , the state estimation of Li-ion batteries can be precisely predicted using Artificial Intelligent methods, which can be combined with a battery management system to improve electric vehicle performance.About:
This article is published in Ain Shams Engineering Journal.The article was published on 2023-03-01 and is currently open access. It has received 2 citations till now. The article focuses on the topics: State of health & Battery pack.read more
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Parameter Identification of Lithium-Ion Battery Model Based on African Vultures Optimization Algorithm
TL;DR: In this article , the African vultures optimization algorithm (AVOA) is used to solve the problem of parameter identification for lithium-ion batteries, where parameter identification is a nonlinear optimization process problem.
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Energy Consumption Analysis for the Prediction of Battery Residual Energy in Electric Vehicles
Keerthi Unni,Sushil Thale +1 more
TL;DR: In this paper , a detailed mathematical equation-based energy consumption analysis of a particular EV model for Indian roads is presented, which can be used for any EV model or vehicle type through simple mathematical equations.
References
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Lithium batteries: Status, prospects and future
Bruno Scrosati,Jürgen Garche +1 more
TL;DR: In this article, the authors present the present status of lithium battery technology, then focus on its near future development and finally examine important new directions aimed at achieving quantum jumps in energy and power content.
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Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
Laith Alzubaidi,Jinglan Zhang,Amjad J. Humaidi,Ayad Q. Al-Dujaili,Ye Duan,Omran Al-Shamma,José Santamaría,Mohammed A. Fadhel,Muthana Al-Amidie,Laith Farhan +9 more
TL;DR: In this paper, a comprehensive survey of the most important aspects of DL and including those enhancements recently added to the field is provided, and the challenges and suggested solutions to help researchers understand the existing research gaps.
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Review on modeling of the anode solid electrolyte interphase (SEI) for lithium-ion batteries
TL;DR: In this article, a review of state-of-the-art modeling progress in the investigation of solid electrolyte interphase (SEI) films on the anodes, ranging from electronic structure calculations to mesoscale modeling, covering the thermodynamics and kinetics of electrolyte reduction reactions, SEI formation, modification through electrolyte design, correlation of SEI properties with battery performance, and the artificial SEI design.
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State-of-Charge Estimation for Lithium-Ion Batteries Using Neural Networks and EKF
TL;DR: This paper presents a method for modeling and estimation of the state of charge (SOC) of lithium-ion (Li-Ion) batteries using neural networks (NNs) and the extended Kalman filter (EKF).
Journal ArticleDOI
State-of-the-Art and Energy Management System of Lithium-Ion Batteries in Electric Vehicle Applications: Issues and Recommendations
TL;DR: This review will hopefully lead to increasing efforts toward the development of an advanced Li-ion battery in terms of economics, longevity, specific power, energy density, safety, and performance in vehicle applications.