Lithium-ion battery degradation diagnosis and state-of-health estimation with half cell electrode potential.

• A model for SOH estimation and degradation diagnosis is present. • Proposing a method to select appropriate segments of charging data as model input. • This model development process does not rely on aging data. • The method is validated on real aging data. Lithium-ion batteries (LiBs) have been widely used in electric vehicles and portable electronics. However, the performance and safety of these applications are highly dependent on degradation of LiBs. In this paper, three contributions have been made to achieve reliable degradation diagnosis and State-of-Health (SOH) estimation: (1) Open-circuit voltage is reconstructed to diagnose degradation modes of LiBs by performing scaling and translation transformations on open-circuit potential curves. (2) A degradation diagnosis model is developed to quantify aging characteristics of LiBs. In this model, a segment of charging data is taken to estimate SOH and the degradation modes in a degradation path. (3) An appropriate voltage range of the charging data is selected to improve model estimation accuracy. Experimental results show that the proposed method can achieve reliable degradation diagnosis and accurate SOH estimation with the maximum error of 1.44%. [Display omitted] [ABSTRACT FROM AUTHOR]