4.7 Article

Data-Driven Diagnosis of Multiple Faults in Series Battery Packs Based on Cross-Cell Voltage Correlation and Feature Principal Components

Related references

Note: Only part of the references are listed.
Article Engineering, Electrical & Electronic

Data-Driven Fault Diagnosis in Battery Systems Through Cross-Cell Monitoring

Michael Schmid et al.

Summary: Fault diagnosis in Battery Management Systems is crucial to prevent catastrophic consequences such as thermal runaway of battery cells. This study presents a novel data-driven approach based on comparing single cell voltages to detect faults and localize them using Principal Component Analysis. The method shows sensitivity and robustness in detecting abnormalities even under dynamic load profiles and sensor noise, demonstrating fault detection and isolation capabilities in a large battery system.

IEEE SENSORS JOURNAL (2021)

Article Chemistry, Physical

Fault diagnosis and abnormality detection of lithium-ion battery packs based on statistical distribution

Qiao Xue et al.

Summary: A novel fault diagnosis and abnormality detection method for battery packs of electric scooters is proposed in this study, utilizing statistical distribution and parameter variation to determine operation states, employing algorithms and screening methods to detect abnormal cells, and identifying fault types and locating faulty cells by calculating fault frequency.

JOURNAL OF POWER SOURCES (2021)

Article Chemistry, Physical

Future smart battery and management: Advanced sensing from external to embedded multi-dimensional measurement

Zhongbao Wei et al.

Summary: With advancements in technology, smart batteries and management systems have emerged as the new focus. Research is shifting towards smart batteries and smart cell management to address the limitations of traditional BMS. Emerging sensing techniques and system integration innovations present new opportunities and challenges for battery management.

JOURNAL OF POWER SOURCES (2021)

Article Green & Sustainable Science & Technology

Energy management and optimization of PEMFC/battery mobile robot based on hybrid rule strategy and AMPSO

Xueqin Lu et al.

Summary: This research focuses on energy allocation and control strategies for a hybrid power system composed of proton exchange membrane fuel cell and lithium battery to achieve optimal operation and fast response. By considering economic and safety requirements, methods such as fuzzy state machine control and adaptive mutation particle swarm optimization have successfully reduced power fluctuations and improved the system's fuel economy and service life.

RENEWABLE ENERGY (2021)

Article Engineering, Electrical & Electronic

Quantified Assessment of Internal Short-Circuit State for 18 650 Batteries Using an Extreme Learning Machine-Based Pseudo-Distributed Model

Jiale Xie et al.

Summary: This research proposes a method for diagnosing battery internal short circuit using thermal behaviors. By integrating thermal effects and utilizing a multiclass relevance vector machine to assess short circuit intensity, ISC faults can be effectively recognized.

IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION (2021)

Review Chemistry, Multidisciplinary

Questions and Answers Relating to Lithium-Ion Battery Safety Issues

Wensheng Huang et al.

Summary: This article comprehensively discusses issues such as electric vehicle accidents, lithium-ion battery safety, existing safety technology, and solid-state batteries, clarifying the failure mechanisms of lithium-ion batteries and providing advice on creating safer battery systems. The aim is to promote a safer future for battery applications and a wider acceptance of electric vehicles.

CELL REPORTS PHYSICAL SCIENCE (2021)

Article Chemistry, Physical

A multi-fault diagnosis method based on modified Sample Entropy for lithium-ion battery strings

Yunlong Shang et al.

JOURNAL OF POWER SOURCES (2020)

Review Engineering, Electrical & Electronic

Advanced Fault Diagnosis for Lithium-Ion Battery Systems: A Review of Fault Mechanisms, Fault Features, and Diagnosis Procedures

Xiaosong Hu et al.

IEEE INDUSTRIAL ELECTRONICS MAGAZINE (2020)

Article Engineering, Multidisciplinary

Valve regulated lead acid battery diagnostic system based on infrared thermal imaging and fuzzy algorithm

Neeraj Khera et al.

INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT (2020)

Article Automation & Control Systems

Model-Based Battery Thermal Fault Diagnostics: Algorithms, Analysis, and Experiments

Satadru Dey et al.

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY (2019)

Article Engineering, Electrical & Electronic

Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries

Yongzhi Zhang et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2018)

Article Automation & Control Systems

Model Predictive Control for Lithium-Ion Battery Optimal Charging

Changfu Zou et al.

IEEE-ASME TRANSACTIONS ON MECHATRONICS (2018)

Article Chemistry, Physical

A correlation based fault detection method for short circuits in battery packs

Bing Xia et al.

JOURNAL OF POWER SOURCES (2017)

Proceedings Paper Engineering, Industrial

Method for classification of battery separator defects using optical inspection

J. Huber et al.

FACTORIES OF THE FUTURE IN THE DIGITAL ENVIRONMENT (2016)

Article Automation & Control Systems

Adaptive Nonlinear Model-Based Fault Diagnosis of Li-Ion Batteries

Amardeep Sidhu et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2015)

Article Automation & Control Systems

A Survey of Fault Diagnosis and Fault-Tolerant Techniques-Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

Zhiwei Gao et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2015)