State of Charge Estimation of Lithium-Ion Batteries Based on Fuzzy Fractional-Order Unscented Kalman Filter

• Tipo: Artigo em Revista Científica Internacional
• Data: 2021

Autores

Chen, LP (Autor) Outra; Chen, Y (Autor) Outra; António Mendes Lopes (Autor) FEUP; Kong, HF (Autor) Outra; Wu, RC (Autor) Outra

Revista

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Título: FRACTAL AND FRACTIONAL

Página Final: 91

ISSN: 2504-3110

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00V-A3J

DOI: 10.3390/fractalfract5030091

Abstract (EN): The covariance matrix of measurement noise is fixed in the Kalman filter algorithm. However, in the process of battery operation, the measurement noise is affected by different charging and discharging conditions and the external environment. Consequently, obtaining the noise statistical characteristics is difficult, which affects the accuracy of the Kalman filter algorithm. In order to improve the estimation accuracy of the state of charge (SOC) of lithium-ion batteries under actual working conditions, a fuzzy fractional-order unscented Kalman filter (FFUKF) is proposed. The algorithm combines fuzzy inference with fractional-order unscented Kalman filter (FUKF) to infer the measurement noise in real time and take advantage of fractional calculus in describing the dynamic behavior of the lithium batteries. The accuracy of the SOC estimation under different working conditions at three different temperatures is verified. The results show that the accuracy of the proposed algorithm is superior to those of the FUKF and extended Kalman filter (EKF) algorithms.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 17