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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Proceedings ArticleDOI
A composite estimation method for state of charge of batteries in a power station engineering
TL;DR: This paper uses a composite method to estimate the SOC, which is the Extended Kalman estimation method combine the Ah integral and the Open Circuit Voltage method, and verifies that this composite algorithm has a high accuracy, and the error within 6% in a power station engineering.
Proceedings ArticleDOI
Performance Analysis of R-int Approximation in Battery Equivalent Circuit Models
TL;DR: In this article , the R-int reduced-order equivalent circuit model is used to estimate the parameters of a battery management system and the theoretical performance analysis is presented by deriving the Cramer-Rao lower bound on the estimation error variance.
Proceedings ArticleDOI
Development of a Machine Learning Technique to Accurately Estimate Battery State of Charge
Varsha Pendyala,Fnu Nishanth +1 more
TL;DR: In this article , a machine learning technique is developed to estimate the battery state of charge and it's performance is evaluated over drive cycle data that was experimentally collected from a commercial electric vehicle under different test conditions.
Journal ArticleDOI
State of Charge Estimation of Li-ion Battery using Extended Kalman Filter and Combined Battery Model
Journal ArticleDOI
Robust adaptive sliding mode observer for core temperature and state of charge monitoring of Li-ion battery: A simulation study
TL;DR: In this article , an equivalent circuit model (ECM) together with a lumped thermal model has been considered as design model for an online adaptive sliding mode observer, which uses measurement of battery terminal voltage and surface temperature in order to estimate SOC and core temperature, both of which play decisive role in BMS applications.
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.