Associate professor
Supervisor of Master's Candidates
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DOI number:10.1109/TTE.2024.3414190
Journal:IEEE Transactions on Transportation Electrification
Key Words:LIB, Feature extraction, Clustering methods, Internal-external Euclidean distance, Stepwise regrouping
Abstract:LIB regrouping echelon utilization application scenarios are very wide, such as communication base station backup power supply, distributed energy storage system, photovoltaic power station, etc. A key challenge is to ensure the consistency and scale of the regrouping LIB module. However, the inadequacies of existing solutions have hindered the widespread adoption of echelon utilization. Hence, two optimized features are determined as the screening criteria. Meanwhile, FCM clustering algorithm and subtractive clustering algorithm are proposed to combine to carry out LIB clustering efficiently. Furthermore, a new stepwise regrouping approach based on internal-external Euclidean distance is put forward to ensure the scale same of each LIB module and meet the direct echelon utilization application scenario requirements. Compared with the random regrouping method, the innovatively proposed multidimensional evaluation indexes including maximum available capacity, terminal voltage and SOC, indicate that the consistency of the LIB module based on the proposed method in this paper is obviously improved. The inconsistency evaluation indexes of each dimension are all decreased by more than 20%, which may contribute to the advancement of LIB regrouping echelon utilization.
Indexed by:Journal paper
Discipline:Engineering
Document Type:J
Page Number:Early Access
Translation or Not:no
Date of Publication:2024-06-13
Included Journals:SCI
Links to published journals:https://ieeexplore.ieee.org/document/10556634
