Propagation mechanisms and diagnosis of parameter inconsistency within Li-Ion battery packs. (September 2019)

• Record Type: Journal Article
• Authors: Feng, Fei; Hu, Xiaosong; Hu, Lin; Hu, Fengling; Li, Yang; Zhang, Lei
• Is Part Of: Renewable & sustainable energy reviews. Volume 112(2019)
• Page Start: 102
• Page End: 113
• Publication Date: 2019-09
• Subjects: Li-ion battery packs -- Parameter inconsistency -- Propagation mechanism -- Feature extraction -- Diagnosis method; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2019.05.042
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: 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. Highlights: The propagation mechanisms of parameter inconsistency in battery packs are analyzed. Parameter inconsistency in series- and parallel-connected battery pack models is summarized. Feature extraction methods for parameter inconsistency are proposed, highlighting the significance of feature optimization. Methods of battery inconsistency evaluation and diagnosis based on these features are reviewed. Existing problems and future research directions in this field are outlined.