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Type of publication: research article
Type of publication (PDB): Straipsnis konferencijos medžiagoje kitose duomenų bazėse / Article in conference proceedings in other databases (P1c)
Field of Science: Informatika / Informatics (N009)
Author(s): Man, K. L;Ting, T. O;Krilavičius, Tomas;Wan, Kaiyu;Chen, C;Chang, J;Poon, S. H
Title: Towards a hybrid approach to SoC estimation for a smart battery management system (BMS) and battery supported Cyber-physical systems (CPS)
Is part of: 2nd Baltic congress on future internet communications, 25-27 April 2012, Vilnius, Lithuania. Piscataway, NJ : IEEE Press, 2012
Extent: p. 1-4
Date: 2012
Keywords: Baterijų valdymo sistemos;Pakrovimo būsena;Dirbtinis intelektas;Kiberfizinės sistemos;Battery management system;Cyber-physical systems;State of charge
ISBN: 9781467316705
Abstract: One of the most important and indispensable parameters of a Battery Management System (BMS) is to accurately estimate the State of Charge (SoC) of battery. Precise estimation of SoC can prevent battery from damage or premature aging by avoiding over charge or discharge. Due to the limited capacity of a battery, advanced methods must be used to estimate precisely the SoC in order to keep battery safely being charged and discharged at a suitable level and to prolong its life cycle. We review several existing effective approaches such as Coulomb counting, Open Circuit Voltage (OCV) and Kalman Filter method for performing the SoC estimation. Then we investigate both Artificial Intelligence (AI) approach and Formal Methods (FM) approach that can be efficiently used to precisely determine the SoC estimation for the smart battery management system as presented in [1]. By using presented approach, a more accurate SoC measurement can be obtained for the smart battery management system and battery supported Cyber-Physical Systems (CPS)
Affiliation(s): Taikomosios informatikos katedra
Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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