Year: 2015
Type: article
Abstract: Recently, secondary batteries have attracted a lot of attention. They have been used as an energy source in electric vehicles (EVs), hybrid electric vehicles (HEVs) and smart grids. This attention increases by emerging more demand for decreasing CO2 gas in the air and having more renewable source. For those applications for rechargeable batteries and specifically Li-ion chemistry based ones, the battery management system (BMS) needs to have a very close to the truth guess of state of charge (SOC) of each individual cell in the battery pack. This research paper presents an extended Kalman filter based method to estimate SOC of Li-ion batteries. The validity of the procedure is demonstrated experimentally for an APR18650m1 LiFePO4 battery.
Author: Ashkan Kavash
Institution: Kathmandu University
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W596501119