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

• Type: Article in International Scientific Journal
• Date: 2022

Authors

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

Journal

The Journal is awaiting validation by the Administrative Services.

Title: FRACTAL AND FRACTIONAL

Vol. 6

Final page: 52

ISSN: 2504-3110

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 0 Citations

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 20