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STCKF Algorithm Based SOC Estimation of Li-Ion Battery by Dynamic Parameter Modeling

  • R. RamprasathEmail author
  • R. Shanmughasundaram
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 968)

Abstract

State of Charge (SoC) is the important criterion which reflects the actual battery usage. So, the State of Charge (SoC) has to be precisely estimated for improving the life and the rate of utilization of the battery. During normal operation of the battery, parameters like charge and discharge efficiency, temperature, etc., tend to affect the accurate estimation of SoC. In this paper, for estimating battery SoC with higher accuracy, Strong Tracking Cubature Kalman Filtering (STCKF) is used and the battery model parameters are identified using the method of Recursive Least Square (RLS). Simulation results indicate, STCKF estimates the SoC values as that of Ampere-Hour (AH) method with very minimal error and the dynamically modeled battery parameter values follows the same discharge characteristics as that of real batteries.

Keywords

Estimating SoC STCKF algorithm Lithium-ion battery Dynamic parameter modeling 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Mechanical Engineering, Amrita School of EngineeringAmrita Vishwa VidyapeethamCoimbatoreIndia
  2. 2.Department of Electrical and Electronics Engineering, Amrita School of EngineeringAmrita Vishwa VidyapeethamCoimbatoreIndia

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