State of Charge Centralized Estimation of Road Condition Information Based on Fuzzy Sunday Algorithm

Jingwei Hu, Bing Lin, Mingfen Wang, Jie Zhang, Wenliang Zhang and Yu Lu
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Jingwei Hu: College of Physics and Energy, Fujian Normal University, Fuzhou 350117, China
Bing Lin: College of Physics and Energy, Fujian Normal University, Fuzhou 350117, China
Mingfen Wang: Concord University College, Fujian Normal University, Fuzhou 350117, China
Jie Zhang: Concord University College, Fujian Normal University, Fuzhou 350117, China
Wenliang Zhang: College of Physics and Energy, Fujian Normal University, Fuzhou 350117, China
Yu Lu: Concord University College, Fujian Normal University, Fuzhou 350117, China

Energies, 2022, vol. 15, issue 8, 1-15

Abstract: Accurate estimation of the state of charge (SOC) is critical for battery management systems. A backpropagation neural network (BPNN) based on a modified fuzzy Sunday algorithm is proposed to improve the accuracy of SOC predictions of lithium-ion batteries (LIBs). The road condition information relating to the data is obtained using the fuzzy Sunday algorithm, and the acquired feature information is used to estimate SOC using BPNN based on the Levenberg–Marquardt (L–M) training process. The change from exact character matching to fuzzy number matching is an improvement to the Sunday algorithm. The quantification of the road condition is innovatively integrated into the neural network. At present, this kind of feature is new to the estimation process, and our experiment proved that the effect is good. To quickly estimate the SOC under different driving conditions, the same network was used to predict the data of different road conditions. In addition, a strategy is proposed for SOC estimation under unknown road conditions, which improves the estimation accuracy. Studies have shown that the model used in the experiment is more accurate than other machine learning models. This model assures prediction accuracy, reliability, and timeliness.

Keywords: SOC; lithium-ion batteries; Sunday algorithm; BPNN; road condition (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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