Supervisor of Master's Candidates
Name (Simplified Chinese): 吴慕遥
Name (Pinyin): wumuyao
Date of Birth: 1995-12-08
Date of Employment: 2022-12-27
School/Department: 汽车与交通工程学院
Education Level: With Certificate of Graduation for Doctorate Study
Business Address: 安徽省合肥市屯溪路193号合肥工业大学格物楼515
Gender: Male
Degree: Doctoral Degree in Engineering
Professional Title: Lecturer
Status: Employed
Alma Mater: 中国科学技术大学
Supervisor of Master's Candidates
Discipline: Automobile Engineering
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State of health estimation of the LiFePO4 power battery based on the forgetting factor recursive Total Least Squares and the temperature correction
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Impact Factor:9.0
DOI number:10.1016/j.energy.2023.128437
Journal:Energy
Key Words:LiFePO4 Power Battery, Forgetting Factor Recursive Total Least Squares, Temperature Correction, Capacity Convergence Coefficient, Arrhenius Equation
Abstract:The decline of the lithium-ion power battery's State of Health (SOH) with usage significantly impacts other state estimation results, such as State of Charge (SOC). Hence, accurate estimation of the lithium-ion power battery's SOH holds vital importance in the battery management system. This paper proposes a SOH estimation method for the lithium-ion power battery, utilizing the Forgetting Factor Recursive Total Least Squares (FFRTLS) and incorporating the temperature correction. The FFRTLS effectively addresses the SOC estimation errors and the terminal current measurement noise simultaneously. The temperature correction method, based on the Arrhenius equation, corrects the influence of the ambient temperature during the SOH estimation process, ensuring that the ambient temperature does not affect the accuracy of the SOH estimation results. Additionally, the capacity convergence coefficient enhances the reliability of the SOH estimation results by preventing abrupt changes of the maximum available capacity. Experimental results on a LiFePO4 power battery under diverse working conditions and varying ambient temperatures, validate the effectiveness of the proposed method. The evaluation indexes, including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Maximum Absolute Error (Max-AE), demonstrate the high accuracy of the SOH estimation results, with all indexes below 0.21%, 0.25% and 0.35% respectively.
Note:中科院1区Top
Co-author:Li Wang
First Author:Muyao Wu
Indexed by:Journal paper
Correspondence Author:Ji Wu
Document Code:128437
Discipline:Engineering
Document Type:J
Volume:282
ISSN No.:0360-5442
Translation or Not:no
Date of Publication:2023-07-13
Included Journals:SCI、EI
Links to published journals:https://www.sciencedirect.com/science/article/pii/S0360544223018315
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