Lithium Battery SoC Estimation Based on Improved Iterated Extended Kalman Filter
Source abstract
Abstract
With the application of lithium batteries more and more widely, in order to accurately estimate the state of charge (SoC) of the battery, this paper uses the iterated extended Kalman filter (IEKF) algorithm to estimate the SoC. The Levenberg–Marquardt (LM) method is used to optimize the error covariance matrix of IKEF. Based on the hybrid pulse power characteristics experiment, a second-order Thevenin model with variable parameters is established on the MATLAB platform. The experimental results show that the proposed model is effective under the constant current discharge condition, the Federal Urban Driving Schedule (FUDS) condition, and the Beijing dynamic stress test (BJDST) condition. The results show that the simulation error of the improved LM-IEKF algorithm is less than 2% under different working conditions, which is lower than that of the IKEF algorithm. The improved algorithm has a fast convergence speed to the true value, and it has a good estimation accuracy in the case of large changes in external input current. Additionally, the fluctuation of error is relatively stable, which proves the reliability of the algorithm.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Battery Technologies Research · Advancements in Battery Materials · Fault Detection and Control Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Electronics and Control Engineering, Chang’an University, Xi’an 710064, China
School of Automotive Engineering, Harbin Institute of Technology, Weihai 264209, China
School of Energy and Electrical Engineering, Chang’an University, Xi’an 710064, China
Funding
National Natural Science Foundation of China · Key Research and Development Program of Shaanxi Province · Fundamental Research Funds for the Central Universities CHD · Natural Science Foundation of Shaanxi Province
References (35)
Show source-provided references
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