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contributor authorYu, Victor
contributor authorHeadley, Alex
contributor authorChen, Dongmei
date accessioned2017-05-09T01:06:31Z
date available2017-05-09T01:06:31Z
date issued2014
identifier issn0022-0434
identifier otherds_136_04_041013.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/154361
description abstractOne of the main issues with vanadium redox flow batteries (VRFBs) is that vanadium ions travel across the membrane during operation which leads to a concentration imbalance and capacity loss after longterm cycling. Precise stateofcharge (SOC) monitoring allows the operator to effectively schedule electrolyte rebalancing and devise a control strategy to keep the battery running under optimal conditions. However, current SOC monitoring methods are too expensive and impractical to implement on commercial VRFB systems. Furthermore, physical models alone are neither reliable nor accurate enough to predict longterm capacity loss due to crossover. In this paper, we present an application of using an extended Kalman filter (EKF) to estimate the total vanadium concentration in each halfcell by combining three voltage measurements and a state prediction model without crossover effects. Simulation results show that the EKF can accurately predict capacity loss for different crossover patterns over a few hundred cycles.
publisherThe American Society of Mechanical Engineers (ASME)
titleA Constrained Extended Kalman Filter for State of Charge Estimation of a Vanadium Redox Flow Battery With Crossover Effects
typeJournal Paper
journal volume136
journal issue4
journal titleJournal of Dynamic Systems, Measurement, and Control
identifier doi10.1115/1.4026654
journal fristpage41013
journal lastpage41013
identifier eissn1528-9028
treeJournal of Dynamic Systems, Measurement, and Control:;2014:;volume( 136 ):;issue: 004
contenttypeFulltext


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