A hybrid state-of-charge estimation method based on credible increment for electric vehicle applications with large sensor and model errors. (February 2020)

• Record Type: Journal Article
• Authors: Lai, Xin; Wang, Shuyu; He, Long; Zhou, Long; Zheng, Yuejiu
• Is Part Of: Journal of energy storage. Volume 27(2020)
• Publication Date: 2020-02
• Subjects: Hybrid state-of-charge estimation method -- Extended Kalman filter -- Ampere-hour counting method -- Lithium-ion battery -- Electric vehicle; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2019.101106
• Languages: English
• ISSNs: 2352-152X

Abstract

Highlights: SOC increment errors of two estimation methods are investigated. A hybrid SOC estimator is developed to suppress the negative effect of sensor and model errors. Proposed method is evaluated by two batteries under three dynamical stress tests. Abstract: State-of-charge (SOC) estimation is a key issue in electric vehicles, which is affected by model and sensor errors. In this paper, a novel SOC estimation method based on the SOC increment with high credibility is proposed to deal with the large errors of the model and sensor. Firstly, the characteristics of SOC error increment about the ampere-hour counting (AHC) and extended Kalman filter (EKF) methods are examined and the more credible SOC increment is determined. Secondly, a hybrid SOC estimation method, which utilizes the no correlation between the AHC method and the errors of the voltage sensor and the equivalent circuit model, in combination with the weak correlation between the EKF method and the errors of the current sensor and the water tank model, is developed over the whole SOC range. Finally, the proposed hybrid method is evaluated by two types of batteries under three dynamical stress tests, and the results demonstrate that the proposed method can greatly suppress the large sensor and model errors and achieve high accuracy and robustness.