A method for SOC estimation based on simplified mechanistic model for LiFePO4 battery. (1st November 2016)

• Record Type: Journal Article
• Authors: Li, Junfu; Lai, Qingzhi; Wang, Lixin; Lyu, Chao; Wang, Han
• Is Part Of: Energy. Volume 114(2016)
• Page Start: 1266
• Page End: 1276
• Publication Date: 2016-11-01
• Subjects: State of charge -- Battery management system -- Simplified mechanistic model -- Excitation response analysis -- Applicability and robustness; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2016.08.080
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Accurate battery state of charge (SOC) estimation conduces to establishing an ideal charging and discharging strategy for battery management system (BMS). And it can also prevent serious damage to battery (pack) from over-charging or over-discharging. This paper firstly establishes a simplified mechanistic model for LiFePO4 battery. Parameter identification conditions are originally designed based on excitation response analysis and essential verifications in terms of model accuracy are conducted. The functional relationship between mechanistic parameters and battery SOC is then established. And lastly, SOC estimation method based on the proposed model is presented. The contributions of this paper are listed as follows: (i) the proposed mechanistic model with obtained parameters can accurately describe LiFePO4 battery behaviors and predict discharge capacity under different operating conditions, (ii) the proposed SOC estimation method based on the battery model has certain applicability and robustness. Analysis and assessment of accuracy of the proposed method indicate that SOC estimation accuracy is acceptable. With the improvement of model simulation, SOC estimation accuracy can be further refined. Highlights: A mechanistic model and model parameter estimation method are proposed. Functional relationship between mechanistic parameters and SOC is established. A SOC estimation method based on simplified mechanistic model is proposed. Estimated SOC shows good agreement with the reference under various conditions. Proposed SOC estimation method has certain applicability and robustness.