Topic
State of charge
About: State of charge is a research topic. Over the lifetime, 12013 publications have been published within this topic receiving 201419 citations. The topic is also known as: SoC & SOC.
Papers published on a yearly basis
Papers
More filters
TL;DR: Ahmed et al. as discussed by the authors presented an effective method for offline battery model parameter estimation at various battery states of health, using an equivalent circuit with one voltage source, one resistance in series, and several RC pairs.
Abstract: Electric vehicles are receiving considerable attention because they offer a more efficient and sustainable transportation alternative compared to conventional fossil-fuel powered vehicles. Since the battery pack represents the primary energy storage component in an electric vehicle powertrain, it requires accurate monitoring and control. In order to effectively estimate the battery pack critical parameters such as the battery state of charge (SOC), state of health (SOH), and remaining capacity, a high-fidelity battery model is needed as part of a robust SOC estimation strategy. As the battery degrades, model parameters significantly change, and this model needs to account for all operating conditions throughout the battery's lifespan. For effective battery management system design, it is critical that the physical model adapts to parameter changes due to aging. In this paper, we present an effective method for offline battery model parameter estimation at various battery states of health. An equivalent circuit with one voltage source, one resistance in series, and several RC pairs modeled the battery charging and discharging dynamics throughout the lifespan of the battery. Accelerated aging tests using real-world driving cycles simulated battery usage. Three lithium nickel-manganese-cobalt oxide (LiNiMnCoO2) cells were tested at temperatures between 35°C and 40°C, with interruptions at every 5% capacity degradation to run reference performance tests for tracking changes in the battery model parameters. The equivalent circuit-based model was validated using real-world driving cycles. The parameter estimation procedure resulted in an efficient model that keeps track of the battery evolution as it ages. CITATION: Ahmed, R., Gazzarri, J., Onori, S., Habibi, S. et al., \"Model-Based Parameter Identification of Healthy and Aged Li-ion Batteries for Electric Vehicle Applications,\" SAE Int. J. Alt. Power. 4(2):2015, doi:10.4271/2015-01-0252. 2015-01-0252 Published 04/14/2015 Copyright © 2015 SAE International doi:10.4271/2015-01-0252 saealtpow.saejournals.org
78 citations
20 Oct 2009
TL;DR: In this paper, the authors developed a battery pack model that would analyze the variation of internal resistance as a function of temperature, and the study of the losses would help in designing a cost effective efficient battery management system.
Abstract: Battery forms a critical part of the hybrid electric vehicle (HEV) drivetrain. An important constraint to the effective performance and reliability of the battery is its unpredictable internal resistance variation along the driving cycle. Temperature has a considerable effect on this internal resistance and thus the battery management system monitors cell and battery pack temperature in accordance with the state-of-charge to prevent thermal runaway. Li-ion batteries which offer possible solutions to the HEVs energy and power density demands thus need to have a good thermal management system in order to enhance their performance. This paper aims to develop a battery pack model that would analyze the variation of internal resistance as a function of temperature. The study of the losses would help in designing a cost effective efficient battery management system.
78 citations
01 Dec 2006
TL;DR: In this article, the authors proposed an online estimation of the current state of charge (SOC) of the battery pack based on the well-known extended Kalman filter (EKF).
Abstract: Battery management systems (BMS) in hybrid electric vehicles (HEVs) should be able to online estimate the present State of Charge (SOC) of the battery pack accurately. In this paper, we proposed a SOC estimating method for battery packs based on the well-known extended Kalman filter (EKF). The underlying dynamic behavior of the battery pack was described by a model which was based on an equivalent circuit comprising of two capacitors and three resistors. Measurements of current and voltage in two different tests were applied to validate the proposed method. By comparing the SOC estimated by model based EKF to the SOC estimated by coulomb counting, we got the results showing that the methodologies we proposed were able to perform a good estimation of SOC of the battery pack. Moreover, a corresponding BMS including hardware and software based on our estimating method was designed.
77 citations
TL;DR: A stack-level model based on the circuit analog method is proposed to research the shunt current loss of the vanadium redox flow battery, in which the SOC (state of charge) of electrolyte is introduced.
77 citations
TL;DR: The effectiveness of the presented method is successfully verified under scaled-down operating condition of hybrid electric tram on the reduced-scale test platform and it has advantages in hydrogen consumption, state of charge fluctuation, efficiency, and fuel cell output power dynamics.
77 citations