Journal ArticleDOI
Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs: Part 3. State and parameter estimation
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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.read more
Citations
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Journal ArticleDOI
A new method of modeling and state of charge estimation of the battery
TL;DR: In this article, a fractional order model based on the PNGV (Partnership for a New Generation of Vehicle) model is proposed after analyzing the impedance characteristics of the lithium battery and compared with the integer order model.
Journal ArticleDOI
Online available capacity prediction and state of charge estimation based on advanced data-driven algorithms for lithium iron phosphate battery
TL;DR: In this article, the state estimation and capacity prediction methods are coupled to improve the estimation accuracy at different temperatures among the lifetime of battery, considering the influence of temperature and degradation, the data-driven algorithm namely least squares support vector machine is implemented to predict the available capacity.
Proceedings ArticleDOI
Li-ion battery parameter estimation for state of charge
TL;DR: In this paper, an onboard adaptive algorithm is developed to estimate six electrical parameters for Li-ion batteries and provide a reliable battery state of charge (SOC) based on one of the estimated battery parameters, i.e., open circuit voltage (OCV).
Journal ArticleDOI
Model-based Dynamic Power Assessment of Lithium-Ion Batteries Considering Different Operating Conditions
Xiaosong Hu,Rui Xiong,Bo Egardt +2 more
TL;DR: This paper is concerned with model-based dynamic peak-power evaluation for LiNMC and LiFePO4 batteries under different operating conditions and the robustness of the peak- power estimation approach against varying battery temperatures and aging levels is investigated.
Journal ArticleDOI
State of charge estimation of a lithium ion cell based on a temperature dependent and electrolyte enhanced single particle model
TL;DR: The accuracy of model-based state of charge estimation depends on the accuracy of the underlying model, including temperature effects that greatly influence cell dynamics as discussed by the authors, which is a critical information to system engineers and end users of consumer electronics to electric vehicles.
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
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.