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JEET, Vol. 13, No. 5, September 2018
Battery State Estimation Algorithm for High-Capacity Lithium Secondary Battery for EVs Considering Temperature Change Characteristics
Dong-Hee Kim
Area B - Electric Machinery and Power Electronics
Abstract In this paper, we studied the state of charge (SOC) estimation algorithm of a high-capacity lithium secondary battery for electric vehicles (EVs) considering temperature characteristics. Nonlinear characteristics of high-capacity lithium secondary batteries are represented by differential equations in the mathematical form and expressed by the state space equation through battery modeling to extract the characteristic parameters of the lithium secondary battery. Charging and discharging equipment were used to perform characteristic tests for the extraction of parameters of lithium secondary batteries at various temperatures. An extended Kalman filter (EKF) algorithm, a state observer, was used to estimate the state of the battery. The battery capacity and internal resistance of the high-capacity lithium secondary battery were investigated through battery modeling. The proposed modeling was applied to the battery pack for EVs to estimate the state of the battery. We confirmed the feasibility of the proposed study by comparing the estimated SOC values and the SOC values from the experiment. The proposed method using the EKF is expected to be highly applicable in estimating the state of the high-capacity rechargeable lithium battery pack for electric vehicles.
Keyword Battery modeling,Electric vehicles,Lithium-ion battery,State of charge,Extended Kalman filter,State space equation.
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