Pregled bibliografske jedinice broj: 715753
Battery state-of-charge and parameter estimation algorithm based on Kalman filter
Battery state-of-charge and parameter estimation algorithm based on Kalman filter // EUROCON, 2013 IEEE
Cavtat, Hrvatska, 2013. str. 1519-1525 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 715753 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Battery state-of-charge and parameter estimation algorithm based on Kalman filter
Autori
Dragicevic, Tomislav ; Sučić, Stjepan ; Guerrero, Joseph Maria J.M.
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
EUROCON, 2013 IEEE
/ - , 2013, 1519-1525
Skup
Energy Conference (ENERGYCON), 2014 IEEE International
Mjesto i datum
Cavtat, Hrvatska, 13.05.2014. - 16.05.2014
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Lead acid battery; Kalman filter; estimation; state-of-charge; battery management system
(Lead acid battery; Kalman filter; estimation; state-of-charge; battery management system.)
Sažetak
Electrochemical battery is the most widely used energy storage technology, finding its application in various devices ranging from low power consumer electronics to utility back-up power. All types of batteries show highly non-linear behaviour in terms of dependence of internal parameters on operating conditions, momentary replenishment and a number of past charge/discharge cycles. A good indicator for the quality of overall customer service in any battery based application is the availability and reliability of these informations, as they point out important runtime variables such as the actual state of charge (SOC) and state of health (SOH). Therefore, a modern battery management systems (BMSs) should incorporate functions that accommodate real time tracking of these non- linearities. For that purpose, Kalman filter based algorithms emerged as a convenient solution due to their ability to adapt the underlying battery model on-line according to internal processes and measurements. This paper proposes an enhancement of previously proposed algorithms for estimation of the battery SOC and internal parameters. The validity of the algorithm is confirmed through the simulation on experimental data captured from the lead acid battery stack installed in the real-world remote telecommunication station.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Tomislav Dragičević
(autor)