Published September 2019 | Version v1
Journal article

Propagation mechanisms and diagnosis of parameter inconsistency within Li-Ion battery packs

  • 1. State Key Laboratory of Mechanical Transmissions, Department of Automotive Engineering, Chongqing University, Chongqing, 400044 (China)
  • 2. School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, 410114 (China)
  • 3. National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, 100081 (China)

Description

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. -- 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.

Additional details

Identifiers

DOI
10.1016/j.rser.2019.05.042;
PII
S1364032119303557;

Publishing Information

Journal Title
Renewable and Sustainable Energy Reviews
Journal Volume
112
Journal Page Range
p. 102-113
ISSN
1364-0321

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
55020141
Subject category
S25: ENERGY STORAGE; S42: ENGINEERING;
Descriptors DEI
ALGORITHMS; COMPUTERIZED SIMULATION; DATA PROCESSING; ELECTRIC-POWERED VEHICLES; ENERGY DENSITY; LITHIUM ION BATTERIES; OPTIMIZATION
Descriptors DEC
ELECTRIC BATTERIES; ELECTROCHEMICAL CELLS; ENERGY STORAGE SYSTEMS; ENERGY SYSTEMS; MATHEMATICAL LOGIC; PROCESSING; SIMULATION; VEHICLES

Optional Information

Copyright
Copyright (c) 2019 Elsevier Ltd. All rights reserved.