A method for estimating the state of health of a power battery suitable for discharging in future uncertain dynamic conditions
By constructing a battery model using the Thevenin model and genetic algorithm, and combining Euclidean distance and empirical models, the accuracy problem of SOH estimation for electric vehicle power batteries under dynamic operating conditions is solved, achieving high-precision and low-computation battery health status assessment.
CN115754724BActive Publication Date: 2026-07-17HARBIN INST OF TECH AT WEIHAI
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HARBIN INST OF TECH AT WEIHAI
- Filing Date
- 2022-09-03
- Publication Date
- 2026-07-17
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Figure CN115754724B_ABST
Abstract
A power battery state of health estimation method suitable for future uncertainty dynamic working condition discharge, comprising the following steps: S1, adopting Thevenin model to construct a battery model; S2, parameter identification of the battery model; S3, extracting the mean and median of the terminal voltage error; S4, adopting Euclidean distance to describe the difference before and after battery aging; S5, establishing an empirical model between Euclidean distance and battery SOH.The beneficial effects of the present application are that the SOH of the battery can be estimated through the data of future uncertainty dynamic working condition discharge, the model has good precision and generalization performance; and the parameters of the battery model at each aging point do not need to be identified, only the parameters of the battery model at the initial cycle need to be identified.
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