Journal ArticleDOI
State of charge estimation for electric vehicle batteries using unscented kalman filtering
TLDR
A model to simulate battery terminal voltage as a function of state of charge under dynamic loading conditions is developed, tailored on-line in order to estimate uncertainty arising from unit-to-unit variations and loading condition changes.About:
This article is published in Microelectronics Reliability.The article was published on 2013-06-01. It has received 295 citations till now. The article focuses on the topics: State of charge & Electric vehicle.read more
Citations
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Journal ArticleDOI
Adaptive Dual Extended Kalman Filter Based on Variational Bayesian Approximation for Joint Estimation of Lithium-Ion Battery State of Charge and Model Parameters
TL;DR: A variational Bayesian approximation-based adaptive dual extended Kalman filter (VB-ADEKF) is proposed, which outperforms the traditional DEKF algorithm in terms of SOC estimation accuracy, convergence rate, and robustness.
Journal ArticleDOI
Research on parameter identification and state of charge estimation of improved equivalent circuit model of Li-ion battery based on temperature effects for battery thermal management
Journal ArticleDOI
Online state of charge estimation of lithium-ion batteries: A moving horizon estimation approach
TL;DR: In this paper, a nonlinear battery state-space model based moving horizon estimation (MHE) approach is proposed to estimate the online state of charge (SOC) within the full range.
Journal ArticleDOI
Estimating the State-of-Charge of Lithium-Ion Batteries Using an H-Infinity Observer with Consideration of the Hysteresis Characteristic
TL;DR: In this article, an impedance-based equivalent circuit model has been constructed with respect to a LiFePO₄ battery by approximating the electrochemical impedance spectrum (EIS) with RC circuits.
References
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Proceedings ArticleDOI
The unscented Kalman filter for nonlinear estimation
Eric A. Wan,R. van der Merwe +1 more
TL;DR: The unscented Kalman filter (UKF) as discussed by the authors was proposed by Julier and Uhlman (1997) for nonlinear control problems, including nonlinear system identification, training of neural networks, and dual estimation.
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
Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries
TL;DR: In this paper, a smart estimation method based on coulomb counting is proposed to improve the estimation accuracy for state-of-charge (SOC) estimation of lithium-ion batteries with high charging and discharging efficiencies.
Journal ArticleDOI
State-of-Charge Estimation of the Lithium-Ion Battery Using an Adaptive Extended Kalman Filter Based on an Improved Thevenin Model
TL;DR: An adaptive Kalman filter algorithm that can greatly improve the dependence of the traditional filter algorithm on the battery model is employed and is evaluated by experiments with federal urban driving schedules, showing that the proposed SOC estimation using AEKF is more accurate and reliable than that using EKF.