Journal ArticleDOI
State of Charge Estimation of Lithium-Ion Batteries in Electric Drive Vehicles Using Extended Kalman Filtering
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TLDR
A more accurate battery state of charge (SOC) estimation method for electric drive vehicles is developed based on a nonlinear battery model and an extended Kalman filter supported by experimental data.Abstract:
In this paper, a more accurate battery state of charge (SOC) estimation method for electric drive vehicles is developed based on a nonlinear battery model and an extended Kalman filter (EKF) supported by experimental data. A nonlinear battery model is constructed by separating the model into a nonlinear open circuit voltage and a two-order resistance-capacitance model. EKF is used to eliminate the measurement and process noise and remove the need of prior knowledge of initial SOC. A hardware-in-the-loop test bench was built to validate the method. The experimental results show that the proposed method can estimate the battery SOC with high accuracy.read more
Citations
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Book ChapterDOI
State estimation methodologies for lithium-sulfur battery management systems
TL;DR: In this paper , the state of the art in lithium-sulfur battery state estimation is presented, explaining the limitations of standard lithium-ion techniques and presenting two groups of techniques that have shown promise in the literature.
Proceedings ArticleDOI
Multi-cell SOC estimation for Li-Ion battery applied to an energy storage system
TL;DR: This paper focuses on SOC estimation for a multi-cell ESS, ready to be embedded in the BMS and explores a smoothing algorithm to improve the estimation results.
Journal ArticleDOI
State of Charge Estimation Techniques for Lithium-ION Batteries Used in Electric Vehicle Applications
Proceedings ArticleDOI
State of Charge Estimation for a Lithium-Ion Battery Pack
F. Sanjit,Harris John,Rani Chinnappa Naidu,S. Hemachandra S. Hemachandra,Derick Mathew,Rajeshkumar Muthu +5 more
TL;DR: In this article , a variety of ways for estimating the level of charge of a cell or a battery pack have been investigated, along with their shortcomings, such as the Kalman Filter and Extended Kalman filter.
Proceedings ArticleDOI
State of Charge Estimation for a Lithium-Ion Battery Pack
TL;DR: In this article , a variety of methods to counter sensor errors have been explored, the Kalman Filter, as well as the Extended Kalman filter algorithm, have both been explored in detail particularly.
References
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Journal ArticleDOI
Accurate electrical battery model capable of predicting runtime and I-V performance
Min Chen,Gabriel A. Rincon-Mora +1 more
TL;DR: An accurate, intuitive, and comprehensive electrical battery model is proposed and implemented in a Cadence environment that accounts for all dynamic characteristics of the battery, from nonlinear open-circuit voltage, current-, temperature-, cycle number-, and storage time-dependent capacity to transient response.
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 3. State and parameter estimation
TL;DR: 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.
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.
Journal ArticleDOI
Dynamic lithium-ion battery model for system simulation
TL;DR: In this article, the authors present a complete dynamic model of a lithium ion battery that is suitable for virtual prototyping of portable battery-powered systems, based on publicly available data such as the manufacturers' data sheets.