SOC estimation for LiFePO4 battery in EVs using recursive least-squares with multiple adaptive forgetting factors
VH Duong, HA Bastawrous, KC Lim… - … Vehicles and Expo …, 2014 - ieeexplore.ieee.org
VH Duong, HA Bastawrous, KC Lim, KW See, P Zhang, SX Dou
2014 International Conference on Connected Vehicles and Expo (ICCVE), 2014•ieeexplore.ieee.orgThis work presents a novel technique which is simple yet effective in estimating electric
model parameters and state-of-charge (SOC) of the LiFePO 4 battery. Unlike the well-known
recursive least-squares-based algorithms with single constant forgetting factor, this
technique employs multiple adaptive forgetting factors to provide the capability to capture
the different dynamics of model parameters. The validity of the proposed method is verified
through experiments using actual driving cycles.
model parameters and state-of-charge (SOC) of the LiFePO 4 battery. Unlike the well-known
recursive least-squares-based algorithms with single constant forgetting factor, this
technique employs multiple adaptive forgetting factors to provide the capability to capture
the different dynamics of model parameters. The validity of the proposed method is verified
through experiments using actual driving cycles.
This work presents a novel technique which is simple yet effective in estimating electric model parameters and state-of-charge (SOC) of the LiFePO 4 battery. Unlike the well-known recursive least-squares-based algorithms with single constant forgetting factor, this technique employs multiple adaptive forgetting factors to provide the capability to capture the different dynamics of model parameters. The validity of the proposed method is verified through experiments using actual driving cycles.
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