Results 11 to 20 of about 629,063 (301)

State-of-charge and state-of-health prediction of lead-acid batteries for hybrid electric vehicles using non-linear observers [PDF]

open access: yes, 2005
The paper describes the application of state-estimation techniques for the real-time prediction of state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells.
Bentley, P   +3 more
core   +1 more source

SoC Estimation in Lithium-Ion Batteries with Noisy Measurements and Absence of Excitation

open access: yesBatteries, 2023
Accurate State-of-Charge estimation is crucial for applications that utilise lithium-ion batteries. In real-time scenarios, battery models tend to present significant uncertainty, making it desirable to jointly estimate both the State of Charge and ...
Miquel Martí-Florences   +3 more
doaj   +1 more source

A New State of Charge Estimation Algorithm for Lithium-Ion Batteries Based on the Fractional Unscented Kalman Filter

open access: yesEnergies, 2017
An accurate state of charge (SOC) estimation is the basis of the Battery Management System (BMS). In this paper, a new estimation method which considers fractional calculus is proposed to estimate the lithium battery state of charge.
Yixing Chen   +5 more
doaj   +1 more source

A State Observer Design for Simultaneous Estimation of Charge State and Crossover in Self-Discharging Disproportionation Redox Flow Batteries [PDF]

open access: yes, 2019
This paper presents an augmented state observer design for the simultaneous estimation of charge state and crossover flux in disproportionation redox flow batteries, which exhibits exponential estimation error convergence to a bounded residual set.
Ascencio, Pedro   +3 more
core   +3 more sources

Design of a Robust Unknown Input Observer for the State of Charge Estimation for Lithium-Ion Batteries [PDF]

open access: yesAdvances in Engineering and Intelligence Systems, 2023
The robustness of an observer against model uncertainties is a main challenge during the Lithiumion battery state of charge (SoC) estimation. Also, for large-scale applications such as electric vehicles, disturbances in measurement may increase the SoC ...
Omid Rezaei, Mohammadali Faghih
doaj   +1 more source

Influence of State of Charge Estimation Uncertainty on Energy Management Strategies for Hybrid Electric Vehicles [PDF]

open access: yes, 2011
This paper studies how the optimal energy management of a hybrid electric vehicle and a plug-in hybrid electric vehicle is affected by uncertain estimates of the battery state of charge.
Egardt, Bo   +2 more
core   +1 more source

Observer techniques for estimating the state-of-charge and state-of-health of VRLABs for hybrid electric vehicles [PDF]

open access: yes, 2005
The paper describes the application of observer-based state-estimation techniques for the real-time prediction of state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells.
Bentley, P   +3 more
core   +1 more source

A Behavioral Algorithm for State of Charge Estimation [PDF]

open access: yesWorld Electric Vehicle Journal, 2012
In Hybrid Electricle Vehicles (HEV), performing online energy management is an important task to be achieved to reduce emissions, fuel consumption and increase vehicle performance. For this task, estimating the State of Charge (SOC) is needed since it serves as a measure of energy that is left inside an electrochemical battery.
Ayca Balkan   +3 more
openaire   +1 more source

Quadrature Kalman filter–based state of charge estimation for lithium-ion battery

open access: yesAdvances in Mechanical Engineering, 2020
This article presents an approach to lithium-ion battery state of charge estimation based on the quadrature Kalman filter. Among the existing state of charge estimation approaches, the extended Kalman filter–based state of charge and unscented filter ...
Mengtao Huang   +4 more
doaj   +1 more source

Electric vehicle battery model identification and state of charge estimation in real world driving cycles [PDF]

open access: yes, 2015
This paper describes a study demonstrating a new method of state-of-charge (SoC) estimation for batteries in real-world electric vehicle applications. This method combines realtime model identification with an adaptive neuro-fuzzy inference system (ANFIS)
Auger, Daniel J.   +2 more
core   +1 more source

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