000 01179nam a2200337 4500
008 240126t2021 ||||| |||| 00| 0 eng d
041 _aeng
080 _a621.3(043)
100 _aJeewandara, Jeewandara Mudiyanselage Dinidu Srimal
245 _aAn Advanced machine learning approach to estimate the state of charge of battery energy storage system for micro-grid
260 _c[2021]
300 _axii, 114p. : col. charts, col. ill., col. photos, tables,
_eCD-ROM
502 _cEE
_dFAC_ENG
_gUniversity of Moratuwa
_o21
650 _a BATTERY MANAGEMENT SYSTEM
650 _aDEEP LEARNING
650 _aPYTHON
650 _aPREDICTION
650 _aKALMAN FILTER
_913728
650 _aSTATE OF CHARGE
650 _aTIME SERIES FORECASTING
650 _aELECTROTHERMAL BATTERY MODEL
_927321
650 _aPARAMETERIZATION
_99593
650 _aVALIDATION
_9288
650 _a HEAT GENERATION
650 _a ELECTRICAL ENGINEERING – Dissertation
658 _aMSc (Major Component Research)
700 _aProf. J.P. Karunadasa
_esup
700 _aProf. K.T.M.U. Hemapala
_esup
856 _uhttp://dl.lib.uom.lk/handle/123/22540
942 _cTH
999 _c182123
_d182123