TY - JOUR
T1 - Propagation mechanisms and diagnosis of parameter inconsistency within Li-Ion battery packs
AU - Feng, Fei
AU - Hu, Xiaosong
AU - Hu, Lin
AU - Hu, Fengling
AU - Li, Yang
AU - Zhang, Lei
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/9
Y1 - 2019/9
N2 - Traction batteries constitute a core technology for electric vehicles. The cells used in such batteries are usually connected in a series-parallel structure. Significant degradation in energy density, cycle life, and safety occurs with battery usage, thanks to discrepancies among cell parameters, such as resistance, capacity, and State of Charge. Hence, it is imperative to explore propagation mechanisms of parameter inconsistency and develop methods to diagnose them. The state of the art in the two aspects are elaborated from three perspectives of internal, external, and coupling effects. Modeling approaches for parameter inconsistency available in the existing literature are comprehensively surveyed, with the purpose of spurring innovative ideas for establishing new models. Methods of data processing and feature extraction are systematically summarized in order to promote diagnostic efficiency and credibility. Moreover, methods of battery inconsistency evaluation and diagnosis are reviewed with the aim of catalyzing the development of new diagnostic algorithms. Finally, existing problems and future trends in the field of battery pack inconsistency research are elucidated.
AB - Traction batteries constitute a core technology for electric vehicles. The cells used in such batteries are usually connected in a series-parallel structure. Significant degradation in energy density, cycle life, and safety occurs with battery usage, thanks to discrepancies among cell parameters, such as resistance, capacity, and State of Charge. Hence, it is imperative to explore propagation mechanisms of parameter inconsistency and develop methods to diagnose them. The state of the art in the two aspects are elaborated from three perspectives of internal, external, and coupling effects. Modeling approaches for parameter inconsistency available in the existing literature are comprehensively surveyed, with the purpose of spurring innovative ideas for establishing new models. Methods of data processing and feature extraction are systematically summarized in order to promote diagnostic efficiency and credibility. Moreover, methods of battery inconsistency evaluation and diagnosis are reviewed with the aim of catalyzing the development of new diagnostic algorithms. Finally, existing problems and future trends in the field of battery pack inconsistency research are elucidated.
KW - Diagnosis method
KW - Feature extraction
KW - Li-ion battery packs
KW - Parameter inconsistency
KW - Propagation mechanism
UR - http://www.scopus.com/inward/record.url?scp=85066269721&partnerID=8YFLogxK
U2 - 10.1016/j.rser.2019.05.042
DO - 10.1016/j.rser.2019.05.042
M3 - Review article
AN - SCOPUS:85066269721
SN - 1364-0321
VL - 112
SP - 102
EP - 113
JO - Renewable and Sustainable Energy Reviews
JF - Renewable and Sustainable Energy Reviews
ER -