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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

Robustness of SOC Estimation Algorithms for EV Lithium-Ion Batteries against Modeling Errors and Measurement Noise

TL;DR: In this paper, a comparative study of robustness of state-of-charge estimation algorithms against modeling errors and measurement noises is performed using a typical battery platform for vehicle applications with sensor noise and battery aging.
Journal ArticleDOI

Development and Demonstration of Microgrid System Utilizing Second-Life Electric Vehicle Batteries

TL;DR: In this paper, the design, construction, and operation of a commercial-scale microgrid consisting of 164.5 kW of solar photovoltaics (PV), 262 kWh of energy storage, 2 buildings with a total area of 1550 m2, and an average power demand of 85 kW.
Proceedings ArticleDOI

Sensors fault diagnosis for a BMS

TL;DR: The diagnosis procedure consists on the detection and isolation of sensor faults, even for multiple faults, so as to be low-cost from computation and power point of view.
Journal ArticleDOI

Lithium-Ion Battery SOC Estimation and Hardware-in-the-Loop Simulation Based on EKF

TL;DR: The paper builds the model with chip computing capabilities and performs hardware-in-the-loop simulation tests using SpeedGoat as a platform and the Real-Time Workshop as an automatic code generation tool to verify the feasibility and effectiveness of the SoC algorithm in the battery management system (BMS).
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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