Nonlinear Fractional-Order Estimator With Guaranteed Robustness and Stability for Lithium-Ion Batteries

• Published in: IEEE transactions on industrial electronics (1982) 2018-07, Vol.65 (7), p.5951-5961
• Main Authors: Changfu Zou, Xiaosong Hu, Dey, Satadru, Lei Zhang, Xiaolin Tang
• Format: Article
• Language: English
• Subjects: Algorithms; Computational modeling; Estimation; Fractional-order battery model; Integrated circuit modeling; Liapunov direct method; Lithium; Lithium-ion batteries; lithium-ion battery; Mathematical model; nonlinear fractional-order estimator; Rechargeable batteries; Robustness; robustness and stability; Stability; Stability analysis; State of charge; state-of-charge (SoC) estimation
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2017.2782691

This paper proposes a new estimator design algorithm for state-of-charge (SoC) indication of lithium-ion batteries. A fractional-order model-based nonlinear estimator is first framed including a Luenberger term and a sliding mode term. The estimator gains are designed by Lyapunov's direct method, providing a guarantee for stability and robustness of the error system under certain assumptions. This generic estimation algorithm is then applied to lithium-ion batteries. A fractional-order circuit model is adopted to predict battery dynamic behaviours. Assumptions based on which the estimation algorithm is developed are justified and remarked. Experiments corresponding to electric vehicle applications are conducted to parameterize the battery model and demonstrate the estimation performance. It shows that the proposed approach is able to estimate SoC with errors less than 0.03 in the presence of initial deviation and persistent noise. Furthermore, the benefits of using the proposed estimator relative to other estimators are calculated over different cycles and conditions.