Fault detection/diagnosis has become a crucial function of the battery management system (BMS) due to the increasing application of lithium-ion batteries (LIBs) in highly sophisticated and high-power applications to ensure the safe and reliable operation of the system.
Fault reports are documented and maintained as part of the records of BMS [4, 49, 50]. A BMS can identify and report faults that affect battery health and performance. Imbalance, which refers to differences in voltage, current, or capacity among battery cells, can lead to uneven aging, reduced performance, and increased failure risk.
As electric vehicles advance in electrification and intelligence, the diagnostic approach for battery faults is transitioning from individual battery cell analysis to comprehensive assessment of the entire battery system. This shift involves integrating multidimensional data to effectively identify and predict faults.
In addition, a battery system failure index is proposed to evaluate battery fault conditions. The results indicate that the proposed long-term feature analysis method can effectively detect and diagnose faults. Accurate detection and diagnosis battery faults are increasingly important to guarantee safety and reliability of battery systems.
Focus on Battery Management Systems (BMS) and Sensors: The critical roles of BMS and sensors in fault diagnosis are studied, operations, fault management, sensor types. Identification and Categorization of Fault Types: The review categorizes various fault types within lithium-ion battery packs, e.g. internal battery issues, sensor faults.
Within a BMS, identifying faults is crucial for ensuring battery health and safety. This involves detecting, isolating, and estimating faults to prevent batteries from operating in unsafe ranges. Accurate functioning of current, voltage, and temperature sensors is essential.
Review of Lithium-Ion Battery Fault Features, Diagnosis Methods, …
Effective fault diagnosis is thus critical yet challenging. This article reviews LIB fault mechanisms, features, and methods with object of providing an overview of fault diagnosis techniques, emphasizing feature extraction''s critical role in detection via thresholds and isolation via multilevel strategies, and estimating detection quality.
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(PDF) Advanced Fault Diagnosis for Lithium-Ion Battery Systems…
Developing advanced fault diagnosis technologies is becoming increasingly critical for the safe operation of LIBS. This article provides a comprehensive review of the mechanisms, features, and...
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Modeling and simulation of high energy density lithium-ion battery …
Scientific Reports - Modeling and simulation of high energy density lithium-ion battery for multiple fault detection Skip to main content Thank you for visiting nature .
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Recent advances in model-based fault diagnosis for lithium-ion ...
Among these, fault diagnosis plays a pivotal role in preserving the health and reliability of battery systems [6] as even a minor fault could eventually lead severe damage to LIBs [7], [8]. Hence, developing advanced and intelligent fault diagnosis algorithms for early detection of battery faults has become a hot research topic.
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Research progress in fault detection of battery systems: A review
In this paper, the current research progress and future prospect of lithium battery fault diagnosis technology are reviewed. Firstly, this paper describes the fault types and principles of battery system, including battery fault, sensor fault, and connection fault. Then, …
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Review of Lithium-Ion Battery Fault Features, Diagnosis Methods, …
Effective fault diagnosis is thus critical yet challenging. This article reviews LIB fault mechanisms, features, and methods with object of providing an overview of fault …
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Comprehensive fault diagnosis of lithium-ion batteries: An …
All the above fault detection methods have their own advantages in single fault detection, multi-fault detection, classification and location. However, the problem scenarios solved by these methods belong to the simple fault scenario, which is defined as "only one fault occurs in the battery system during a fault detection process". The problem proposed in this paper belongs …
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Online Multi-Fault Detection and Isolation for Battery Systems …
Abstract: Fast and accurate battery system fault diagnosis is essential to ensure electric vehicles'' safe and reliable operation. This paper proposes an online multi-fault detection and isolation method for battery systems by combining improved model-based and signal-processing methods, which eliminates the limitation of interleaved voltage ...
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Efficient Battery Fault Monitoring in Electric Vehicles
Request PDF | Efficient Battery Fault Monitoring in Electric Vehicles: Advancing from Detection to Quantification | Effective monitoring of battery faults is crucial to prevent and mitigate the ...
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Comprehensive fault diagnosis of lithium-ion batteries: An …
All the above fault detection methods have their own advantages in single fault detection, multi-fault detection, classification and location. However, the problem scenarios solved by these …
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A Review of Lithium-Ion Battery Fault Diagnostic …
Fault diagnosis, hence, is an important function in the battery management system (BMS) and is responsible for detecting faults early and providing control actions to minimize fault effects, to ensure the safe and …
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Gaussian process-based online health monitoring and fault …
Health monitoring, fault analysis, and detection methods are important to operate battery systems safely. We apply Gaussian process resistance models on lithium-iron …
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Internal short circuit detection in Li-ion batteries using ...
With the proliferation of Li-ion batteries in smart phones, safety is the main concern and an on-line detection of battery faults is much wanting. Internal short circuit is a very critical issue ...
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(PDF) Machine Learning-Based Data-Driven Fault …
Fault detection/diagnosis has become a crucial function of the battery management system (BMS) due to the increasing application of lithium-ion batteries (LIBs) in highly...
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Machine learning method for early fault detection could make …
More information: Gaussian Process-Based Online Health Monitoring and Fault Analysis of Lithium-Ion Battery Systems From Field Data, Cell Reports Physical Science (2024). DOI: 10.1016/j.xcrp.2024.102258 .
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Advanced data-driven fault diagnosis in lithium-ion battery …
LIB system fault diagnostics include fault detection, fault isolation, and fault estimation. Additionally, fault prognostics can provide early detection or prediction for battery faults with a slow evolution process. The fault handling module analyzes and evaluates the results from fault diagnosis and fault prognosis, making decisions such as ...
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Fault Diagnosis and Detection for Battery System in Real-World …
Accurate detection and diagnosis battery faults are increasingly important to guarantee safety and reliability of battery systems. Developed methods for battery early fault diagnosis concentrate on short-term data to analyze the deviation of external features without considering the long-term latent period of faults. This work proposes a novel data-driven …
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Gaussian process-based online health monitoring and fault …
Health monitoring, fault analysis, and detection methods are important to operate battery systems safely. We apply Gaussian process resistance models on lithium-iron-phosphate (LFP) battery field data to separate the time …
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Fault Diagnosis and Detection for Battery System in Real-World …
This work proposes a novel data-driven method to detect long-term latent fault and abnormality for electric vehicles (EVs) based on real-world operation data. Specifically, the battery fault features are extracted from the incremental capacity (IC) curves, which are smoothed by advanced filter algorithms. Second, principal component analysis ...
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Advanced data-driven fault diagnosis in lithium-ion battery …
LIB system fault diagnostics include fault detection, fault isolation, and fault estimation. Additionally, fault prognostics can provide early detection or prediction for battery …
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Research progress in fault detection of battery systems: A review
In this paper, the current research progress and future prospect of lithium battery fault diagnosis technology are reviewed. Firstly, this paper describes the fault types and principles of battery system, including battery fault, sensor fault, and connection fault. Then, the importance of parameter selection in fault diagnosis is discussed, and ...
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(PDF) Machine Learning-Based Data-Driven Fault Detection
Fault detection/diagnosis has become a crucial function of the battery management system (BMS) due to the increasing application of lithium-ion batteries (LIBs) in highly...
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A Fault Detection Method for Electric Vehicle Battery System …
2544 EE, 2024, vol.121, no.9 may cause short circuits and thermal runaway, and even cause battery combustion, which seriously jeopardizes driving safety [3,4].
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Fault Diagnosis and Detection for Battery System in Real-World …
This work proposes a novel data-driven method to detect long-term latent fault and abnormality for electric vehicles (EVs) based on real-world operation data. Specifically, …
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(PDF) Advanced Fault Diagnosis for Lithium-Ion Battery …
Developing advanced fault diagnosis technologies is becoming increasingly critical for the safe operation of LIBS. This article provides a comprehensive review of the mechanisms, features, and...
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Fault Diagnosis Method for Lithium-Ion Battery Packs in Real …
In this paper, an initial microfault diagnosis method is proposed for the data of electric vehicles in actual operation. First, a robust locally weighted regression data smoothing method is proposed that can effectively remove noisy data and retain fault characteristics.
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AI-Powered Vehicle Battery Fault Detection, Monitoring and
AI-Powered Vehicle Battery Fault Detection, Monitoring and Prediction Aby Johny1, Amithrajith V2, Jom Sebastian3, Tony John Jose4 1 UG ... The system tackles real-time fault detection, continuous health monitoring, and remaining useful life (RUL) prediction of lithium-ion batteries. 3.1 Architecture Data Acquisition and Data Pre-processing: Data streams from the Battery …
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Fault Diagnosis Method for Lithium-Ion Battery Packs …
In this paper, an initial microfault diagnosis method is proposed for the data of electric vehicles in actual operation. First, a robust locally weighted regression data smoothing method is proposed that can effectively remove …
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Online Multi-Fault Detection and Isolation for Battery Systems …
Abstract: Fast and accurate battery system fault diagnosis is essential to ensure electric vehicles'' safe and reliable operation. This paper proposes an online multi-fault detection and isolation …
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