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

• Tipo: Artigo em Revista Científica Internacional
• Data: 2022

Autores

Chen, LP (Autor) Outra; Wu, XB (Autor) Outra; Machado, JAT (Autor) Outra; António Mendes Lopes (Autor) FEUP; Li, PH (Autor) Outra; Dong, XP (Autor) Outra

Revista

A Revista está pendente de validação pelos Serviços Administrativos.

Título: FRACTAL AND FRACTIONAL

Vol. 6

Página Final: 52

ISSN: 2504-3110

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00W-033

DOI: 10.3390/fractalfract6020052

Abstract (EN): The accuracy of the state-of-charge (SOC) estimation of lithium batteries affects the battery life, driving performance, and the safety of electric vehicles. This paper presents a SOC estimation method based on the fractional-order square-root unscented Kalman filter (FSR-UKF). Firstly, a fractional second-order Resistor-Capacitance (RC) circuit model of the lithium battery is derived. The accuracy of the parameterized model is verified, revealing its superiority over integer-order standard descriptions. Then, the FSR-UKF algorithm is developed, combining the advantages of the square-root unscented Kalman filter and the fractional calculus. The effectiveness of the proposed algorithm is proven under a variety of operational conditions in the perspective of the root-mean-squared error, which is shown to be below <mml:semantics>1.0%</mml:semantics>. In addition, several experiments illustrate the performance of the FSR-UKF.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 20