An Improved Battery On-line Parameter Identification and State-of-charge Determining Method
Zhirun Li,Rui Xiong,Hongwen He +2 more
TLDR
Wang et al. as discussed by the authors proposed an improved online parameters identification algorithm for equivalent circuit battery model, which can accurately identify the model parameters within 1% maximum terminal voltage estimation error, and the state of charge error which calculated by the open circuit voltage estimates can be efficiently reduced to an accepted level.About:
This article is published in Energy Procedia.The article was published on 2016-12-01 and is currently open access. It has received 11 citations till now. The article focuses on the topics: State of charge & Battery (electricity).read more
Citations
More filters
Journal ArticleDOI
A hybrid statistical data-driven method for on-line joint state estimation of lithium-ion batteries
TL;DR: This paper proposes a joint lithium-ion battery state estimation approach that takes advantage of the data-driven least-square-support-vector-machine and model-based unscented-particle-filter and achieves the joint estimation with different time scales using the proposed hybrid joint state estimation method.
Journal ArticleDOI
A Novel Variable Forgetting Factor Recursive Least Square Algorithm to Improve the Anti-Interference Ability of Battery Model Parameters Identification
Qiang Song,Yuxuan Mi,Wuxuan Lai +2 more
TL;DR: The analysis indicated that the novel VFF-RLS algorithm has better robustness and convergence ability, and has an acceptable identification accuracy.
Journal ArticleDOI
Experimental validation for Li-ion battery modeling using Extended Kalman Filters
TL;DR: The proposed BMS technique based on EKF is experimentally validated to determine the battery SOC values correlated to those reached by the Coulomb counting method with acceptable small errors.
Journal ArticleDOI
Parameter identification method for lithium-ion batteries based on recursive least square with sliding window difference forgetting factor
TL;DR: In this article, a recursive least square parameter identification approach is proposed by variable forgetting factor with the difference between open circuit and terminal voltages in sliding window mode (SDFF-RLS).
Journal ArticleDOI
Modeling and state of health estimation of nickel–metal hydride battery using an EPSO-based fuzzy c-regression model
TL;DR: A combined battery modeling and SOH estimation method over the lifespan of a nickel–metal hydride (Ni–MH) battery is proposed and a fuzzy c-regression model based on Euclidean particle swarm optimization is applied to modeling a Ni–MH battery.
References
More filters
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
A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion olymer battery in electric vehicles
TL;DR: In this article, a multi-scale extended Kalman filter was employed to estimate battery parameters and state of charge (SoC) in real-time through measured data driven-based battery parameter and SoC estimation.
Journal ArticleDOI
Adaptive state of charge estimator for lithium-ion cells series battery pack in electric vehicles
TL;DR: In this paper, an adaptive extended Kalman filter algorithm has been used to estimate the battery voltage and state of charge (SoC) for electric vehicles with adaptive data-driven based SoC estimator.