Journal ArticleDOI
State-of-Charge Estimation for Lithium-Ion Batteries Using Neural Networks and EKF
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TLDR
This paper presents a method for modeling and estimation of the state of charge (SOC) of lithium-ion (Li-Ion) batteries using neural networks (NNs) and the extended Kalman filter (EKF).Abstract:
This paper presents a method for modeling and estimation of the state of charge (SOC) of lithium-ion (Li-Ion) batteries using neural networks (NNs) and the extended Kalman filter (EKF). The NN is trained offline using the data collected from the battery-charging process. This network finds the model needed in the state-space equations of the EKF, where the state variables are the battery terminal voltage at the previous sample and the SOC at the present sample. Furthermore, the covariance matrix for the process noise in the EKF is estimated adaptively. The proposed method is implemented on a Li-Ion battery to estimate online the actual SOC of the battery. Experimental results show a good estimation of the SOC and fast convergence of the EKF state variables.read more
Citations
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Journal ArticleDOI
A review on the key issues for lithium-ion battery management in electric vehicles
TL;DR: In this article, a brief introduction to the composition of the battery management system (BMS) and its key issues such as battery cell voltage measurement, battery states estimation, battery uniformity and equalization, battery fault diagnosis and so on, is given.
Journal ArticleDOI
A review on lithium-ion battery ageing mechanisms and estimations for automotive applications
Anthony Barré,Benjamin Deguilhem,Sebastien Grolleau,Mathias Gerard,Frédéric Suard,Delphine Riu +5 more
TL;DR: In this paper, the authors present a summary of techniques, models, and algorithms used for battery ageing estimation, going from a detailed electrochemical approach to statistical methods based on data, and their respective characteristics are discussed.
Journal ArticleDOI
A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations
TL;DR: In this article, a comprehensive review of the battery state of charge estimation and its management system for the sustainable future electric vehicles (EVs) applications is presented, which can guarantee a reliable and safe operation and assess the battery SOC.
Journal ArticleDOI
Evaluation of Lithium-Ion Battery Equivalent Circuit Models for State of Charge Estimation by an Experimental Approach
Hongwen He,Rui Xiong,Jinxin Fan +2 more
TL;DR: In this article, an improved Thevenin model, named dual polarization (DP) model, is put forward by adding an extra RC to simulate the electrochemical polarization and concentration polarization separately.
Journal ArticleDOI
Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles
TL;DR: In this paper, the methods for monitoring the battery state of charge, capacity, impedance parameters, available power, state of health, and remaining useful life are reviewed with the focus on elaboration of their strengths and weaknesses for the use in on-line BMS applications.
References
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Book
Neural Networks: A Comprehensive Foundation
TL;DR: Thorough, well-organized, and completely up to date, this book examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks.
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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 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.