Zero-free-parameter modeling approach to predict the voltage of batteries of different chemistries and supercapacitors under arbitrary load

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dc.citation.epageA1280en_US
dc.citation.issueNumber6en_US
dc.citation.spageA1274en_US
dc.citation.volumeNumber164en_US
dc.contributor.authorÖzdemir, E.en_US
dc.contributor.authorUzundal, C. B.en_US
dc.contributor.authorUlgut, B.en_US
dc.date.accessioned2018-04-12T11:01:48Z
dc.date.available2018-04-12T11:01:48Z
dc.date.issued2017en_US
dc.departmentDepartment of Chemistryen_US
dc.description.abstractPerformance modeling of electrochemical energy storage systems is gathering increasingly higher attention in recent years. With the ever increasing power demand of mobile applications, predicting voltage behavior under different load profiles is of utmost importance for communications, automotive and consumer electronics. The ideal modelling approach needs not only to accurately predict the response of the battery, but also be robust, easy to implement and have low computational complexity. We will present a new algorithm that is algebraically straightforward, that has no adjustable parameters and that can accurately predict the voltage response of batteries and supercapacitors. The approach works well in a variety of discharge profiles ranging from simple long DC discharge/charge profiles to pulse schemes based on drive schedules published by regulatory bodies. Our approach is based on Electrochemical Impedance Spectroscopy measurements done on the system to be predicted. The spectrum is used in the frequency domain without any further processing to predict the fast moving portion of the voltage in the frequency domain. DC response is added in through a straightforward lookup table. This widely applicable approach can predict the voltage of with less than 1% error, without any adjustable parameters to a large variety of discharge profiles.en_US
dc.description.provenanceMade available in DSpace on 2018-04-12T11:01:48Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 179475 bytes, checksum: ea0bedeb05ac9ccfb983c327e155f0c2 (MD5) Previous issue date: 2017en
dc.identifier.doi10.1149/2.1521706jesen_US
dc.identifier.issn0013-4651
dc.identifier.urihttp://hdl.handle.net/11693/37067
dc.language.isoEnglishen_US
dc.publisherElectrochemical Society, Inc.en_US
dc.relation.isversionofhttp://dx.doi.org/10.1149/2.1521706jesen_US
dc.source.titleJournal of the Electrochemical Societyen_US
dc.subjectConsumer behavioren_US
dc.subjectElectric batteriesen_US
dc.subjectElectric dischargesen_US
dc.subjectElectrochemical impedance spectroscopyen_US
dc.subjectFrequency domain analysisen_US
dc.subjectSecondary batteriesen_US
dc.subjectSupercapacitoren_US
dc.subjectTable lookupen_US
dc.subjectAdjustable parametersen_US
dc.subjectDischarge profilesen_US
dc.subjectElectrochemical energy storageen_US
dc.subjectElectrochemical impedance spectroscopy measurementsen_US
dc.subjectLow computational complexityen_US
dc.subjectMobile applicationsen_US
dc.subjectPerformance Modelen_US
dc.subjectRegulatory bodiesen_US
dc.subjectForecastingen_US
dc.titleZero-free-parameter modeling approach to predict the voltage of batteries of different chemistries and supercapacitors under arbitrary loaden_US
dc.typeArticleen_US

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