STATE OF CHARGE (SOC) AND STATE OF HEALTH (SOH) ESTIMATION OF LITHIUM-ION BATTERY USING DUAL EXTENDED KALMAN FILTER BASED ON POLYNOMIAL BATTERY MODEL

• Main Author: Ayzah Azis, Nadana
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/36492
• Institution: Institut Teknologi Bandung

Utilization of electrical energy as renewable energy to be applied in everyday life is growing. One of them is the use of electrical resources as the fuel of Electric Vehicles. The source of electricity storage that is widely used in electric vehicles is batteries. The important parameters for batteries are State of Charge (SOC) and State of Health (SOH). This parameter is important to help protect the battery, increase battery life and for the safety of the user's operation. Since SOC & SOH from the battery cannot be measured directly, the estimation method is used to obtain SOC & SOH parameters. In this research, Dual Extended Kalman Filter (DEKF) method will be used to estimate SOC, internal resistance and battery capacity. The determination of the SOH of the battery will be conducted using the capacity fade method and resistancy method. The use of DEKF will provide more accurate results because it can compensate noise measurements and models and it does not require initial SOC value. The estimation results with DEKF estimation method will be compared with the EKF estimation method to see the performance of the estimator. In its use, DEKF requires a model from the battery. For this reason, a battery model of an equivalent electric circuit is used. The optimization method is used to estimate the parameter model. Simulation results show that the SOC from the Dual Extended Kalman Filter gives better result and the battery SOH can be known from the results of battery parameters estimation.