Journal ArticleDOI
A multi-timescale estimator for battery state of charge and capacity dual estimation based on an online identified model
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TLDR
In this article, a multi-timescale method for dual estimation of state of charge (SOC) and capacity with an online identified battery model is presented, where the model parameters are online adapted with the vector-type recursive least squares (VRLS) to address the different variation rates of them.About:Â
This article is published in Applied Energy.The article was published on 2017-10-15. It has received 235 citations till now. The article focuses on the topics: State of charge & Estimator.read more
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A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems
TL;DR: In this article, a systematic review of the most commonly used battery modeling and state estimation approaches for BMSs is presented, including the physics-based electrochemical models, the integral and fractional order equivalent circuit models, and data-driven models.
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State estimation for advanced battery management: Key challenges and future trends
TL;DR: This paper presents a concise, understandable overview of existing methods, key issues, technical challenges, and future trends of the battery state estimation domain, for the first time, in SOC/SOE/SOH/SOP/SOT/SOS estimation.
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Investigating the error sources of the online state of charge estimation methods for lithium-ion batteries in electric vehicles
TL;DR: A novel perspective focusing on the error analysis of the SOC estimation methods is proposed and the error flow charts are proposed to analyze the error sources from the signal measurement to the models and algorithms for the widely used online SOC estimation Methods in new energy vehicles.
Journal ArticleDOI
Recent development of membrane for vanadium redox flow battery applications: A review
TL;DR: In this paper, the authors reviewed the research on membranes in vanadium redox flow battery (VRFB) system, including the properties, development of traditional commercial membranes as well as recently developed membranes.
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A fast estimation algorithm for lithium-ion battery state of health
TL;DR: A model-based SoH estimator is designed and shown to be capable of closely matching battery's aging data from NASA, with the error less than 2.5%.
References
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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.
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State-of-charge and capacity estimation of lithium-ion battery using a new open-circuit voltage versus state-of-charge
TL;DR: In this article, a modified OCV-SoC relationship based on the conventional OCV/SoC was proposed to avoid the defects of the extended Kalman filter (EKF) by preventing the relationship from varying.
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Combined State of Charge and State of Health estimation over lithium-ion battery cell cycle lifespan for electric vehicles
TL;DR: In this paper, a combined state of charge (SOC) and SOH (State Of Health) estimation method over the lifespan of a lithium-ion battery is proposed, where the SOH is estimated in real-time and the capacity and internal ohmic resistance are updated offline.
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Recursive least squares with forgetting for online estimation of vehicle mass and road grade: theory and experiments
TL;DR: In this article, an ad hoc modification of the update law for the gain in the recursive least square (RLS) scheme is proposed and used in simulation and experiments, demonstrating that the proposed scheme estimates mass within 5% of its actual value and tracks grade with good accuracy.
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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.