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Journal ArticleDOI

Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs: Part 3. State and parameter estimation

Gregory L. Plett
- 12 Aug 2004 - 
- Vol. 134, Iss: 2, pp 277-292
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TLDR
In this article, extended Kalman filtering (EKF) is used to estimate battery state-of-charge, power fade, capacity fade, and instantaneous available power for hybrid-electric-vehicle battery packs.
About
This article is published in Journal of Power Sources.The article was published on 2004-08-12. It has received 1587 citations till now. The article focuses on the topics: Battery pack & State of charge.

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Citations
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Journal ArticleDOI

Algorithms for Advanced Battery-Management Systems

TL;DR: In this paper, the authors present a detailed description and model of a Li-ion battery, which is based on using electrochemical principles to develop a physics-based model in contrast to equivalent circuit models.
Journal ArticleDOI

Critical Review on the Battery State of Charge Estimation Methods for Electric Vehicles

TL;DR: The review presents the key feedback factors that are indispensable for accurate estimation of battery SoC, and presents the possible recommendations for the development of next generation of smart SoC estimation and battery management systems for electric vehicles and battery energy storage system.
Journal ArticleDOI

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.
Journal ArticleDOI

Combined State of Charge and State of Health estimation over lithium-ion battery cell cycle lifespan for electric vehicles

TL;DR: In this paper, a combined state of charge (SOC) and SOH (State Of Health) estimation method over the lifespan of a lithium-ion battery is proposed, where the SOH is estimated in real-time and the capacity and internal ohmic resistance are updated offline.
Journal ArticleDOI

Sigma-point Kalman filtering for battery management systems of LiPB-based HEV battery packs Part 2: Simultaneous state and parameter estimation

TL;DR: In this article, a sigma-point Kalman filter (SPKF) was proposed to estimate the state of a Li-ion polymer battery (LiPB) cell in dynamic conditions.
References
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Book ChapterDOI

A New Approach to Linear Filtering and Prediction Problems

TL;DR: In this paper, the clssical filleting and prediclion problem is re-examined using the Bode-Shannon representation of random processes and the?stat-tran-sition? method of analysis of dynamic systems.
Book

Kalman Filtering and Neural Networks

Simon Haykin
TL;DR: This book takes a nontraditional nonlinear approach and reflects the fact that most practical applications are nonlinear.
Journal ArticleDOI

Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs: Part 2. Modeling and identification

TL;DR: In this article, an extended Kalman filter (EKF) was used to estimate the battery state of charge, power fade, capacity fade, and instantaneous available power of a hybrid electric vehicle battery pack.
Journal ArticleDOI

Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs Part 1. Background

TL;DR: In this paper, an extended Kalman filter (EKF) was proposed to estimate the battery state of charge, power fade, capacity fade, and instantaneous available power of a hybrid-electric-vehicle battery pack.
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