A Review on The Battery State of Charge Estimation Methods For Electric Vehicle Battery Management Systems

Aslan, Eyyüp; Yaşa, Yusuf

doi:10.23919/eleco47770.2019.8990463

Cited by 7 publications

(9 citation statements)

References 24 publications

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“…where the capacity of the battery is defined as Q 0 at time t [11,18,19,23]. It is very challenging to accurately estimate SOC by current methodologies.…”

Section: State Of Charge Estimation (Soc)mentioning

confidence: 99%

“…However, all of these approaches have many limitations as described in [12,24]. Similarly, measuring SOC for a battery cell and for a battery pack is different and Table 1 presents this comparison for different methods [19]. SOH provides the health condition of the batteries, i.e., their degree of degradation.…”

Section: State Of Charge Estimation (Soc)mentioning

confidence: 99%

“…where SOH (t 0 ) is the initial battery health condition, δ func is a function which depends on voltage, current, heat, SOC, mechanical vibrations and over-potential, etc. [11,18,19,23].…”

Section: State Of Charge Estimation (Soc)mentioning

confidence: 99%

“…Therefore, the existing approaches have many challenges and SOC estimation under realistic conditions has not been broadly done. The most difficult job is to estimate SOC by using a low cost BMS which should have small memory storage, but fast speed [11,18,19,23].…”

Section: Issues and Challenges Of Bms 61 Soc Estimation Issuesmentioning

confidence: 99%

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Characteristics of Battery Management Systems of Electric Vehicles with Consideration of the Active and Passive Cell Balancing Process

Uzair

Abbas

Hosain

2021

WEVJ

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Energy shortage and environmental pollution issues can be reduced considerably with the development and usage of electric vehicles (EVs). However, electric vehicle performance and battery lifespan depend on a suitable battery arrangement to meet the various battery performance demands. The safety, reliability, and efficiency of EVs largely depends on the constant monitoring of the batteries and management of battery packs. This work comprehensively reviews different aspects of battery management systems (BMS), i.e., architecture, functions, requirements, topologies, fundamentals of battery modeling, different battery models, issues/challenges, recommendations, and active and passive cell balancing approaches, etc., as compared to the existing works which normally discuss one or two aspects only. The work describes BMS functions, battery models and their comparisons in detail for an efficient operation of the battery pack. Similarly, the work presents a comprehensive overview of issues and challenges faced by BMS and also provides recommendations to address these challenges. Cell balancing is very important for the battery performance and in this work various cell balancing methodologies and their comparisons are also presented in detail. Modeling of a cell balancer is presented and a comparative study is also carried out for active and passive cell balance technique in MATLAB/Simulink with an eight cell battery packcell balancing approach. The result shows that the active cell balancing technique is more advantageous than passive balancing for electrical vehicles using lithium-ion batteries.

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“…where the capacity of the battery is defined as Q 0 at time t [11,18,19,23]. It is very challenging to accurately estimate SOC by current methodologies.…”

Section: State Of Charge Estimation (Soc)mentioning

confidence: 99%

Section: State Of Charge Estimation (Soc)mentioning

confidence: 99%

“…where SOH (t 0 ) is the initial battery health condition, δ func is a function which depends on voltage, current, heat, SOC, mechanical vibrations and over-potential, etc. [11,18,19,23].…”

Section: State Of Charge Estimation (Soc)mentioning

confidence: 99%

Section: Issues and Challenges Of Bms 61 Soc Estimation Issuesmentioning

confidence: 99%

See 2 more Smart Citations

Characteristics of Battery Management Systems of Electric Vehicles with Consideration of the Active and Passive Cell Balancing Process

Uzair

Abbas

Hosain

2021

WEVJ

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“…A mostly software based approach is presented, aiming at simplicity and hardware cost reduction, as production cost reduction is essential to enable competitive final prices for the final consumer. Differing from Aslan and Yasa (2019) decentralized processing, data-hungry approach, this paper's technique is based on pre-modelling the power system and treating data in the central hardware. The modelling approach is black-box based, but respectful of previous feature observations in literature.…”

Section: Introductionmentioning

confidence: 99%

Battery Charge And Source Estimation As A Product Component

Souza

Tavares

2020

Anais Do Congresso Brasileiro De Automática 2020

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This paper's goal is to present a low cost, non-conventional solution for battery state of charge estimation and external electrical input presence/absence for a commercial mobile, handheld device whose battery state of charge control is critical. This solution is based on treating and filtering a time series in real-time software, using the battery pack characteristic discharge curve and time series statistical features. The time series is composed of data that is sampled embedded in hardware, communicating directly with the machine's BIOS. The system processes this data and outputs a value that indirectly relates to state of charge, needing further processing to insure accuracy. The data stream is treated in a process that directly relates the output time series with state of charge through a transfer function, effectively treating intermediary conversions as black boxes to simplify analysis and implementation. This process can also detect if an external source is connected/disconnected by exploiting pre-detected features in the time series. This approachadvantages are its low cost and simplicity, reducing hardware complexity and expenses; small dimensional footprint; mostly software-based; and centralization into the main hardware as low computational cost daemons, simplifying data consumption.

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A Critical Review on Available Methods for Estimating the Present State-of-Charge of the Batteries Used in EV/HEV

Vattem,

Gorantla

2023

2023 International Conference on Advanced &Amp; Global Engineering Challenges (AGEC)

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A Review on The Battery State of Charge Estimation Methods For Electric Vehicle Battery Management Systems

Cited by 7 publications

References 24 publications

Characteristics of Battery Management Systems of Electric Vehicles with Consideration of the Active and Passive Cell Balancing Process

Characteristics of Battery Management Systems of Electric Vehicles with Consideration of the Active and Passive Cell Balancing Process

Battery Charge And Source Estimation As A Product Component

A Critical Review on Available Methods for Estimating the Present State-of-Charge of the Batteries Used in EV/HEV

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