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However, misdiagnosis and missed diagnosis happened occasionally. In this paper, a statistical analysis-based multi-fault diagnosis method is proposed to detect and localize short circuit faults, electrical connection faults and voltage sensor faults in LFP battery packs.
An efficient fault diagnostic scheme for battery packs using a novel sensor topology and signal processing procedure that can give accurate and reliable assessments on different fault specifics, with a fault isolation success rate of 84% and a fault severity grading success rates of 90%. 2023 IEEE International Conference on Industrial…
An improved correlation coefficient utilized to percept anomalies in series battery packs. Signal imaging techniques employed to emphasize cross-temporal characteristics as image textures. A CNN-based diagnostic framework proposed to infer fault type and evaluate fault grade.
Battery fault diagnosis is crucial for stable, reliable, and safe operation of electric vehicles, especially the thermal runaway early warning. Developing methods for early failure detection and… —Early detection and tracing of anomalous operation in battery packs are critical to improving performance and ensuring safety.
Finally, CNN models are employed to analyze the images for fault symptoms, thereby detecting fault occurrence, inferring fault type and evaluating fault grade. To obtain realistic dataset, different types and severities of faults are physically triggered on a li-ion battery pack.
In order to verify the feasibility and performance of the detection and diagnosis method, several types of fault detection and diagnosis experiments are set up, which use a temperature chamber, charge equipment and several 50Ah LFP batteries, as shown in Fig. 3. The frequency of measurement is 10 Hz, and the voltage accuracy is 0.1 %.
Fault diagnosis of voltage sensor and current sensor for lithium-ion battery pack using hybrid system modeling and unscented particle filter
An efficient fault diagnostic scheme for battery packs using a novel sensor topology and signal processing procedure that can give accurate and reliable assessments on …
Existing methods of cell failure detection are usually based on voltage, current, or surface temperature measurements. Looking at the voltage signal, a significant voltage drop …
Yang et al. [149] implemented SC fault detection via the difference between the estimated SOCs by the EKF and those computed by a Coulomb counting method. Xu et al. [141] developed a …
The common faults of battery pack can be classified into three categories: battery abuse faults, connection faults and sensor faults [15], [16], [17], as shown in Fig. 1.These …
The proposed multi-fault detection and diagnosis procedure based on interleaved voltage measurement topology can be divided into three steps, which are …
After training with large amounts of labeled battery fault data, Naha et al. [17] detect short circuits up to C / 429 leakage current in lithium-ion battery ... Download full-size image; Fig. 3. Block …
This study addresses the shortcomings of existing lithium-ion battery pack detection systems and proposes a lithium-ion battery monitoring system based on NB-IoT …
Faulty Lithium-Ion Cell Identification in Battery Packs - Seeed Wio Terminal. A TinyML model using Edge Impulse and the Wio Terminal with a thermal camera to predict faulty lithium ion …
A low-redundancy battery pack diagnosis method is proposed to address the data redundancy issue in electric vehicle battery pack fault detection of ISC and VC. The fault diagnosis …
Voltage fault detection for Li-Ion battery pack using local outlier factor This research introduces a new method for detecting voltage faults in Li-ion battery packs. This …
In particular, we developed a fast and high confidence level detection method of hard internal short circuit events for a battery pack by measuring cell expansion force and monitoring CO2 ...
The aim of this paper is to develop a fault detection method dedicated for a liquid leakage and liquid intrusion detection system (in the form of electronic control unit, ECU), that …
for thermal image-based fault detection in EV battery cells, considering th e balance between accuracy and computational efficiency. Keywords: convolutional neural network (CNN), …
Ensure passenger safety and regulatory compliance with innovative battery pack monitoring. Our solutions include thermal runaway detection, battery disconnection monitoring, isolation …
This paper focuses on a novel approach to fault diagnosis by utilizing a personalized battery pack and employing image recognition.
Fault detection and diagnosis (FDD) is of utmost importance in ensuring the safety and reliability of electric vehicles (EVs). The EV''s power train and energy storage, …
Therefore, based on the designed fault diagnosis coefficient, the proposed method can not only effectively diagnose the system fault, but also detect the abnormality of …
Sample of battery fault images: (a) the right side shows the normal image and the left side shows the burn image; (b) the right side shows the cover is the wrong image, and the …
In particular, we developed a fast and high confidence level detection method of hard internal short circuit events for a battery pack by measuring cell expansion force and …