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

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TLDR
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.
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This article is published in Journal of Power Sources.The article was published on 2013-11-01 and is currently open access. It has received 1224 citations till now. The article focuses on the topics: Battery (electricity).

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Research opportunities to advance solar energy utilization

TL;DR: Lewis reviews the status of solar thermal and solar fuels approaches for harnessing solar energy, as well as technology gaps for achieving cost-effective scalable deployment combined with storage technologies to provide reliable, dispatchable energy.
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The lithium-ion battery: State of the art and future perspectives

TL;DR: In this article, a detailed review of the state of the art and future perspectives of Li-ion batteries with emphasis on this potential is presented, with a focus on electric vehicles.
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Lithium-ion battery fast charging: A review

TL;DR: Robust model-based charging optimisation strategies are identified as key to enabling fast charging in all conditions, with a particular focus on techniques capable of achieving high speeds and good temperature homogeneities.
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A review on the key issues of the lithium ion battery degradation among the whole life cycle

TL;DR: A comprehensive review on the key issues of the battery degradation among the whole life cycle is provided in this paper, where the battery internal aging mechanisms are reviewed considering different anode and cathode materials for better understanding the battery fade characteristic.
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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.
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Pattern Recognition and Machine Learning

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TL;DR: In this article, a complete revision of a classic, seminal, and authoritative book that has been the model for most books on the topic written since 1970 is presented, focusing on practical techniques throughout, rather than a rigorous mathematical treatment of the subject.
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Pattern Recognition and Machine Learning

Radford M. Neal
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TL;DR: This book covers a broad range of topics for regular factorial designs and presents all of the material in very mathematical fashion and will surely become an invaluable resource for researchers and graduate students doing research in the design of factorial experiments.
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Time Series Analysis Forecasting and Control

TL;DR: This revision of a classic, seminal, and authoritative book explores the building of stochastic models for time series and their use in important areas of application —forecasting, model specification, estimation, and checking, transfer function modeling of dynamic relationships, modeling the effects of intervention events, and process control.
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Frequently Asked Questions (18)
Q1. What have the authors contributed in "A review on lithium-ion battery ageing mechanisms and estimations for automotive applications" ?

This paper reviews various aspects of recent research and developments, from di erent elds, on Lithium-ion battery ageing mechanisms and estimations. 

loss of available Lithium due to side reactions at the graphite negative electrode have been reported as the main source of ageing during storage periods [24]. 

By de nition, the SOC represents the ions proportion present on electrodes, which implies, for high SOC, a huge potential disequilibrium on the electrode/electrolyte interface. 

To sum up, the principal consequences observed on an aged positive electrode are : wear of active mass, electrolyte degradation, electrolyte oxidation and formation of a SEI, interaction of positive electrode element dissolved within the electrolyte at the negative electrode [35, 41, 42]. 

The (secondary) loss of electrode active materials, possibly a material dissolution, structural degradation, particle isolation, and electrode delamination [45].• 

Supposed evolution of EV sales is the result of petroleum prices increasing and is highly sensitive to the battery development [6]. 

Loss of cyclable lithium is related to side reactions which can occur at both electrodes, as the SEI grows at carbon anode due to electrolyte decomposition [44].• 

The main ageing factor on graphite electrode is the development with the time on the electrolyte/electrode interface of a solid interface named Solid Electrolyte Interphase (SEI) [18]. 

Lithium-ion batteries penetrated the market of hybrid and electrical vehicles thanks to the high Lithium's density, the weak weight of the Lithium batteries making them the most promising candidate for this eld of applications [3]. 

There is also a SEI creation on the positive electrode/electrolyte interface, that is more di cult to detect [38, 39], due to high voltages on this electrode [40]. 

under high temperatures, the SEI may dissolve and create Lithium salts less permeable to the Lithium ions and therefore increase the negative electrode impedance [31]. 

In most cases, a battery in use is prone to exothermic e ects [60, 61] and those reactions can be facilitated under high temperatures and provoke battery ageing. 

Lithium-ion batteries have been commercialized since 1991, initially concerning mobile devices such as cell phones and laptops [1]. 

Previously presented factors in uencing battery ageing interact to generate both capacity loss, resistance augmentation and loss of available peak power [67, 68]. 

A high SOC (State Of Charge >80%) should provoke an acceleration of these phenomena as the potential di erence between electrodes interfaces and electrolyte is important [29]. 

Low temperatures enable to limit the development of these phenomena but these conditions engender some problems due to the loss of material di usion and alter the battery chemistry [56]. 

To illustrate this, Asakura et al. [65] show that a battery life halved for an 0.1V augmentation of the charging voltage, the EOL is considered here as 70% of initial capacity. 

On the contrary, cycle ageing is associated with the impact of battery utilization periods named cycles (both charge or discharge).