Lithium ion batteries have a high energy density high charging efficiency and a wide operating temperature range So they have been widely used in electronic products transportation military aerospace and other fields [1] The requirement of a Battery Management System BMS is to keep the individual cells and battery packs in a healthy safe and optimized
Lithium iron phosphate LFP batteries are extensively used in automobile industries as a source of electricity in electric/hybrid electric vehicles due to their specific characteristics such as low cost high power capacity long cycle life low toxicity thermal safety extended energy storage and high reversibility Li et al 2020 The cathode material
Lithium ion batteries LIBs are an essential energy storage device for a majority of advanced electronics used in our everyday lives from cell phones and laptops to medical devices and electric vehicles Despite their continued widespread adoption methods to recycle and reuse end of life EOL LIB materials are still under active development In the first part of
To achieve more precise and reliable lithium ion battery state of charge SOC estimation this paper performs a comparative study of different adaptive extended Kalman filters AEKFs /adaptive unscented Kalman filters AUKFs Firstly three scenarios are artificially established to evaluate different AEKFs/AUKFs estimation accuracy sensitivity to uncertainty
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As an important power source with the characteristic of lightweight and high energy density lithium ion batteries have attracted increasing attention and are widely used in many industrial applications such as spacecraft aircraft and electric vehicles [1] Especially in the field of electric vehicles lithium ion batteries have maintained rapid growth in sales [2]
The accurate estimation of SOC is always a research hotspot in energy storage systems Researchers have proposed many different methods which can be divided into parameter based characterization methods including ampere hour integration [8] and open circuit voltage OCV method [9] model based methods and data driven methods including fuzzy
Abstract The application of lithium ion batteries LIBs in consumer electronics and electric vehicles has been growing rapidly in recent years This increased demand has greatly stimulated lithium ion battery production which subsequently has led to greatly increased quantities of spent LIBs Because of this considerable efforts are underway to minimize
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In recent years the lithium ion battery has achieved significant benefits in terms of its high energy density [1] reduced memory effect [2] low self discharge rate [3] and long life cycle [4] It has played an important role in many fields such as electric vehicles portable electronic products aerospace [5] and smart power system [6] However with normal long
Common types of lithium based secondary batteries include lithium ion batteries LIBs lithium metal batteries and lithium polymer batteries each with different constituents In 2019 the Occupational Safety and Health Administration in the United States announced fire and explosion risk and safety measures for LIB powered devices whereas
Accurate state of charge SOC estimation for lithium ion battery is a core function in battery management system BMS Although the physical meaning of SOC is similar to fuel gauge used in conventional vehicles [1] unfortunately SOC can only be estimated with measured information by BMS such as current voltage and the high
The method based on black box battery model usually uses the method based on computational intelligence to build battery model [17] For example using artificial neural network ANN [18] fuzzy control FC [19] support vector machine SVM [20] and other methods the relationship between them and SOC is obtained by training the data of current voltage
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Precise capacity and state of charge SOC estimation is crucial to assure safe and reliable operation of lithium ion battery To lower the influence of cross interference between these two estimated states and possible divergence existing in two way transmitted co estimation framework a novel double adaptive extended Kalman filters AEKFs based one way
A secondary lithium ion battery LIB is a rechargeable electrochemical energy storage device Since their development in the 1970s and because of their unique characteristics of high energy capacity and long lifespan LIBs have become important in the field of portable electronic goods [1 2] Compared to other types of batteries NiMH and Pb acid LIBs
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Lithium ion Li ion battery pack is vital for storage of energy produced from different sources and has been extensively used for various applications such as electric vehicles EVs watches cookers etc For an efficient real time monitoring and fault diagnosis of battery operated systems it is important to have a quantified information on the state of health SoH
Robinson et al [9] analyzed the change of ultrasonic signal amplitude to determine the density change of electrode material caused by embedded and delithiated lithium and the results showed that the shift of anode and cathode density during the charging process showed an opposite trend with SOC
