A Review of Battery Management System and Modern State Estimation Approaches in Lithiumion Batteries for Electric Vehicle

Bashir, Hamza; Yaqoob, Ammar; Jawaid, Iqra; Khalid, Waqas; Javed, Muhammad Yaqoob; Sultan, Wajahat

doi:10.1109/icece54634.2022.9758962

Cited by 9 publications

(2 citation statements)

References 35 publications

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“…In real-time operating conditions, the battery state changes due to complex, timevarying and nonlinear battery characteristics [156]. Battery state estimation enhances the battery operability and increases the durability of the designed system [157]. State estimation is mainly referred to SoC and SoH estimation.…”

Section: State Estimationmentioning

confidence: 99%

Review on Battery State Estimation and Management Solutions for Next-Generation Connected Vehicles

Di Luca,

Di Blasio,

Gimelli

et al. 2023

Energies

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The transport sector is tackling the challenge of reducing vehicle pollutant emissions and carbon footprints by means of a shift to electrified powertrains, i.e., battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). However, electrified vehicles pose new issues associated with the design and energy management for the efficient use of onboard energy storage systems (ESSs). Thus, strong attention should be devoted to ensuring the safety and efficient operation of the ESSs. In this framework, a dedicated battery management system (BMS) is required to contemporaneously optimize the battery’s state of charge (SoC) and to increase the battery’s lifespan through tight control of its state of health (SoH). Despite the advancements in the modern onboard BMS, more detailed data-driven algorithms for SoC, SoH, and fault diagnosis cannot be implemented due to limited computing capabilities. To overcome such limitations, the conceptualization and/or implementation of BMS in-cloud applications are under investigation. The present study hence aims to produce a new and comprehensive review of the advancements in battery management solutions in terms of functionality, usability, and drawbacks, with specific attention to cloud-based BMS solutions as well as SoC and SoH prediction and estimation. Current gaps and challenges are addressed considering V2X connectivity to fully exploit the latest cloud-based solutions.

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Section: State Estimationmentioning

confidence: 99%

Review on Battery State Estimation and Management Solutions for Next-Generation Connected Vehicles

Di Luca,

Di Blasio,

Gimelli

et al. 2023

Energies

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show abstract

“…This charge imbalance makes subsequent charge/discharge cycles more challenging and reduces the battery's total capacity. Due to differences in production and temperature, internal impedance, and self-discharge rates, cells in series strings will always be mismatched [25]. As the performance of a battery is dictated by the weakest cell in the chain, a mismatch results in a loss of capacity or power during charge or discharge mode.…”

Section: Introductionmentioning

confidence: 99%

Switched-Resistor Passive Balancing of Li-Ion Battery Pack and Estimation of Power Limits for Battery Management System

Kumar

Rao

Singh

et al. 2023

International Journal of Energy Research

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The battery pack performance and expected lifespan are crucial in electric vehicle applications. Balancing the charge on a battery pack connected in series and parallel is crucial due to manufacturing discrepancies and distinct performance of each cell in a standard battery pack. In this paper, a switched-resistor passive balancing-based method is proposed for balancing cells in a battery management system (BMS). The value of the available voltage at the battery cell terminals is balanced using resistors in an electrical circuit, and the excess voltage is eliminated. The cell balancing outcome demonstrates that the electrical circuit can maintain an even voltage across each cell. The procedure of balancing involves individually adjusting each cell’s level of charge. Passive balancing releases energy as heat by draining charge from cells that have too much charge. A passive cell balancer is a cost-effective solution and easy to install, but due to thermal loss from a resistor, it has a low energy efficiency for cell balancing and necessitates a lengthy balancing process. This passive cell balancer is an effective and reliable method for low-power devices and portable applications such as electrical vehicles. The power limits during charging and discharging are estimated using the bisection method.

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Secondary Life of Electric Vehicle Batteries: Degradation, State of Health Estimation Using Incremental Capacity Analysis, Applications and Challenges

John,

Kudva,

Jayalakshmi

2024

IEEE Access

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Electric vehicles (EVs) have created a revolution in sustainable transportation. The number of EV users has increased significantly within a short period globally. EVs running largely on the battery source require large-capacity battery packs to handle the range anxiety. The primary lifetime of such batteries in EV applications is said to end when their capacity drops to 80% of their initial capacity. This is termed as the end of-life of these batteries. These batteries can still be utilized for secondary applications based on their remaining capacity. Batteries undergo many degradations throughout their lifecycle which affects their capacity. This paper carries out a detailed study on the major degradation factors like solid electrolyte interphase and lithium plating which results in loss of lithium inventory. These affect the capacity of the battery in the long run. Remaining useful capacity must be accurately estimated to identify if the cells are useful for the next phase or must be recycled. Many estimation techniques are available with attention rising towards data derivational methods due to their accuracy and their sensitivity towards battery degradation which thereby makes it easy to track them. Incremental capacity analysis is one such method which is discussed in detail in this paper. The method starts from the initial stage of data extraction and extends to the training set of the models. This method is greatly beneficial as it can reveal the deviations in battery behavior with the help of the valley peak locations and alterations in the slope. The quantitative insights make it an advantageous technique in the field of battery health monitoring and diagnostics. These are discussed in detail and validated by experimental analysis and results. This paper also discusses the market prospects, developments, various ageing mechanisms in batteries, applications, comparison with other estimation techniques and challenges related to secondary life applications. The complete analysis of the estimation method along with the detailed steps also aims to serve as a foundation for the upcoming developments and research in this field.INDEX TERMS Electric vehicle, incremental capacity analysis, second life of EV battery, state of health estimation.

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A Review of Battery Management System and Modern State Estimation Approaches in Lithiumion Batteries for Electric Vehicle

Cited by 9 publications

References 35 publications

Review on Battery State Estimation and Management Solutions for Next-Generation Connected Vehicles

Review on Battery State Estimation and Management Solutions for Next-Generation Connected Vehicles

Switched-Resistor Passive Balancing of Li-Ion Battery Pack and Estimation of Power Limits for Battery Management System

Secondary Life of Electric Vehicle Batteries: Degradation, State of Health Estimation Using Incremental Capacity Analysis, Applications and Challenges

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