A Fast Online State of Health Estimation Method for Lithium-Ion Batteries Based on Incremental Capacity Analysis

Shaofei Qu, Yongzhe Kang, Pingwei Gu, Chenghui Zhang and Bin Duan
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Shaofei Qu: School of Control Science and Engineering, Shandong University, Shandong 250061, China
Yongzhe Kang: School of Control Science and Engineering, Shandong University, Shandong 250061, China
Pingwei Gu: School of Control Science and Engineering, Shandong University, Shandong 250061, China
Chenghui Zhang: School of Control Science and Engineering, Shandong University, Shandong 250061, China
Bin Duan: School of Control Science and Engineering, Shandong University, Shandong 250061, China

Energies, 2019, vol. 12, issue 17, 1-11

Abstract: Efficient and accurate state of health (SoH) estimation is an important challenge for safe and efficient management of batteries. This paper proposes a fast and efficient online estimation method for lithium-ion batteries based on incremental capacity analysis (ICA), which can estimate SoH through the relationship between SoH and capacity differentiation over voltage ( dQ / dV ) at different states of charge (SoC). This method estimates SoH using arbitrary dQ / dV over a large range of charging processes, rather than just one or a limited number of incremental capacity peaks, and reduces the SoH estimation time greatly. Specifically, this method establishes a black box model based on fitting curves first, which has a smaller amount of calculation. Then, this paper analyzes the influence of different SoC ranges to obtain reasonable fitting curves. Additionally, the selection of a reasonable dV is taken into account to balance the efficiency and accuracy of the SoH estimation. Finally, experimental results validate the feasibility and accuracy of the method. The SoH estimation error is within 5% and the mean absolute error is 1.08%. The estimation time of this method is less than six minutes. Compared to traditional methods, this method is easier to obtain effective calculation samples and saves computation time.

Keywords: lithium-ion battery; state of health; incremental capacity analysis; state of charge (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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