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Journal ArticleDOI

Life prediction of batteries for selecting the technically most suitable and cost effective battery

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TLDR
In this article, the authors present a procedure that can be used for lifetime prediction, outlines some of the requirements for a prediction, and discusses the principles of battery models and their potential use in lifetime prediction.
About
This article is published in Journal of Power Sources.The article was published on 2005-06-15. It has received 180 citations till now. The article focuses on the topics: Battery (electricity).

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Citations
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A review on the key issues for lithium-ion battery management in electric vehicles

TL;DR: In this article, a brief introduction to the composition of the battery management system (BMS) and its key issues such as battery cell voltage measurement, battery states estimation, battery uniformity and equalization, battery fault diagnosis and so on, is given.
Journal ArticleDOI

A review on lithium-ion battery ageing mechanisms and estimations for automotive applications

TL;DR: In this paper, the authors present a summary of techniques, models, and algorithms used for battery ageing estimation, going from a detailed electrochemical approach to statistical methods based on data, and their respective characteristics are discussed.
Journal ArticleDOI

A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations

TL;DR: In this article, a comprehensive review of the battery state of charge estimation and its management system for the sustainable future electric vehicles (EVs) applications is presented, which can guarantee a reliable and safe operation and assess the battery SOC.
Journal ArticleDOI

Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review

TL;DR: This review categorises data-driven battery health estimation methods according to their underlying models/algorithms and discusses their advantages and limitations, then focuses on challenges of real-time battery health management and discuss potential next-generation techniques.
Journal ArticleDOI

Review and recent advances in battery health monitoring and prognostics technologies for electric vehicle (EV) safety and mobility

TL;DR: A review of battery prognostics and health management techniques, with a focus on major unmet needs in this area for battery manufacturers, car designers, and electric vehicle drivers, is provided in this article.
References
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Journal ArticleDOI

Design of Primary and Secondary Cells II . An Equation Describing Battery Discharge

TL;DR: In this paper, a discussion is given of the derivation and application of an equation which gives an excellent description of a wide variety of cell and battery discharges, and a simple numerical method for fitting this equation to a particular set of battery discharge curves.
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Battery Monitoring and Electrical Energy Management: Precondition for future vehicle electric power systems

TL;DR: In this paper, the authors present a solution for battery monitoring and energy management for series vehicles launched in years 2001-2003, operating at the 14-V level, with an intelligent integration of the battery as the storage medium into the overall concept of the vehicle Energy Management.
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The available capacity computation model based on artificial neural network for lead–acid batteries in electric vehicles

TL;DR: The results of the experiment have proven the accuracy of the proposed model and the computation values are in good agreement with experimental data, and the associated error has been considered acceptable from an engineering point of view.
Proceedings ArticleDOI

Battery Life Prediction Method for Hybrid Power Applications: Preprint

TL;DR: In this article, a new battery life prediction method was developed to investigate the effects of two primary determinants of battery life in hybrid power applications, varying depths of discharge and varying rates of discharge.
Journal ArticleDOI

Numerical Modeling of Coupled Electrochemical and Transport Processes in Lead‐Acid Batteries

TL;DR: In this article, a numerical model is developed to predict transient behaviors of electric vehicle lead-acid batteries during discharge and charge processes, which not only accounts for coupled processes of electrochemical kinetics and mass transport occurring in a battery cell, but also considers free convection resulting from density variations due to acid stratification.
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