State-of-charge estimation based on microcontroller-implemented sigma-point Kalman filter in a modular cell balancing system for Lithium-Ion battery packs

Zhong, Fan; Rehman, Muhammad Muneeb Ur; Wang, Hongjie; Levron, Yoash; Plett, Gregory L.; Zane, Regan; Maksimović, Dragan

doi:10.1109/compel.2015.7236525

Cited by 20 publications

(8 citation statements)

References 12 publications

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“…Besides EKFs, Unscented Kalman Filters (UKFs) like the Sigma-Point KF are applied for SOC estimation [194,195]. Adaptive KFs are utilized too [196,197].…”

Section: Online Identification Of Core Temperaturementioning

confidence: 99%

Critical Review of Intelligent Battery Systems: Challenges, Implementation, and Potential for Electric Vehicles

et al. 2021

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This review provides an overview of new strategies to address the current challenges of automotive battery systems: Intelligent Battery Systems. They have the potential to make battery systems more performant and future-proof for coming generations of electric vehicles. The essential features of Intelligent Battery Systems are the accurate and robust determination of cell individual states and the ability to control the current of each cell by reconfiguration. They enable high-level functions like fault diagnostics, multi-objective balancing strategies, multilevel inverters, and hybrid energy storage systems. State of the art and recent advances in these topics are compiled and critically discussed in this article. A comprising, critical discussion of the implementation aspects of Intelligent Battery Systems complements the review. We touch on sensing, battery topologies and management, switching elements, communication architecture, and impact on the single-cell. This review contributes to transferring the best technologies from research to product development.

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“…Besides EKFs, Unscented Kalman Filters (UKFs) like the Sigma-Point KF are applied for SOC estimation [194,195]. Adaptive KFs are utilized too [196,197].…”

Section: Online Identification Of Core Temperaturementioning

confidence: 99%

Critical Review of Intelligent Battery Systems: Challenges, Implementation, and Potential for Electric Vehicles

et al. 2021

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“…Therefore, even batteries of identical design and chemistry from the same batch are never truly equal. In a BMS, algorithms that rely on model accuracy can use observer methods such as Kalman filters [74,82] to compensate the small differences between individual cells that are supposed to be equal.…”

Section: Parameter Estimationmentioning

confidence: 99%

Review of computational parameter estimation methods for electrochemical models

Miguel

Plett

Trimboli

et al. 2021

Journal of Energy Storage

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“…This section is an extended version of [13] and [28], which addresses the modeling of a lithium-ion cell for online monitoring and offline benchmarking purposes. It is based on a modified version of the enhanced self-correcting model (ESC) originally proposed by [24], which is an equivalent circuit model with one RC element in parallel and an additional hysteresis voltage source (compare Figure 2c in reference [39]). This physical lithium-ion cell model is combined with smoothly interpolated lookup table of cell characteristic information from laboratory tests.…”

Section: A Constrained Nonlinear Battery Observermentioning

confidence: 99%

A Physical Model-Based Observer Framework for Nonlinear Constrained State Estimation Applied to Battery State Estimation

Brembeck

2019

Sensors

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Future electrified autonomous vehicles demand higly accurate knowledge of their system states to guarantee a high-fidelity and reliable control. This constitutes a challenging task—firstly, due to rising complexity and operational safeness, and secondly, due to the need for embedded service oriented architecture which demands a continuous development of new functionalities. Based on this, a novel model based Kalman filter framework is outlined in this publication, which enables the automatic incorporation of multiphysical Modelica models into discrete-time estimation algorithms. Additionally, these estimation algorithms are extended with nonlinear inequality constraint handling functionalities. The proposed framework is applied to a constrained nonlinear state of charge lithium-ion cell observer and is validated with experimental data.

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State-of-charge estimation based on microcontroller-implemented sigma-point Kalman filter in a modular cell balancing system for Lithium-Ion battery packs

Cited by 20 publications

References 12 publications

Critical Review of Intelligent Battery Systems: Challenges, Implementation, and Potential for Electric Vehicles

Critical Review of Intelligent Battery Systems: Challenges, Implementation, and Potential for Electric Vehicles

Review of computational parameter estimation methods for electrochemical models

A Physical Model-Based Observer Framework for Nonlinear Constrained State Estimation Applied to Battery State Estimation

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