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, namely the electric motor drive …
Various methods published in recent years for reliable detection of battery faults (mainly internal short circuit (ISC)) raise the question of comparability and cross-method evaluation, which cannot yet be answered due to significant differences in training data and boundary conditions. This paper provides a Monte Carlo-like simulation …
Fault diagnosis is key to enhancing the performance and safety of battery storage systems. However, it is challenging to realize efficient fault diagnosis for …
Threshold-based fault diagnosis methods are often unable to identify the type of fault and predict the time of failure. Shang et al. [6] introduced a correction factor α to optimize the fault diagnosis method based on sample entropy, so that it can distinguish simple fault types.The correction factor α is defined by the following rules: (1.7) α = − 1, …
In this paper, a non-redundancy interleaved voltage measurement topology proposed in Ref. [30] is introduced to collect fault signatures.The prototype is illustrated in Fig. 1, in which the voltage sensors are interleaved connected.For the battery pack with n series-connected cells, the i t h sensor is connected to the positive electrode of cell i and …
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.
A new method for abnormal data detection in mechanical equipment health monitoring is proposed in this paper. ... realized battery failure detection by evaluating the local deviation of observed ...
The battery cells are an important part of electric and hybrid vehicles, and their deterioration due to aging or malfunction directly affects the life cycle and performance of the whole battery system. Therefore, an early detection of deviation in performance of the battery cells is an important task and its correct solution could significantly ...
This paper aims to compare a new webcam-based eye-tracking system, integrated into the Labvanced platform for online experiments, to a "gold standard" lab-based eye tracker (EyeLink 1000 - SR Research). Specifically, we simultaneously recorded data with both eye trackers in five different tasks, analyzing their real-time performance. …
1. Introduction. Batteries are considered an integral part of any data center which ensure the uninterrupted working of a data center [1].Data centers always get fluctuating power from the grid station, but for a smooth operation stable power is required which is thus maintained by Uninterruptible Power Supply (UPS) systems using batteries.
In case of a new battery bank the alarm is usually due to differences in the initial state of charge of the individual battery. If the deviation increases to more than 3% you should stop charging the battery bank and charge the individual batteries or cells separately. ... A consideration can be made to add a Battery Balancer to the system. A ...
The results show that the proposed dynamical autoencoder approach achieves the best detection results by a 16–33% AUROC boost (Fig. 3 a) and a smaller variance compared to other algorithms ...
Industrial globalization and economic development promote international cooperation and removal of trade barriers, boosts the scale and intensity of activities in the transportation sector (Baloch et al., 2020).However, its heavy reliance on fossil fuels has caused significant environmental challenges, including vehicle carbon emissions and …
The battery terminal voltage in the power battery system is a comprehensive indicator of its internal resistance, capacity, state of charge (SoC) and …
With the large-scale application of lithium-ion batteries, battery safety has attracted more and more attention. This paper summarizes the mainstream modeling …
In this paper, a new battery anomaly detection method based on time series clustering is proposed. This method uses only battery operating data and does not depend on offline testing data, thus provides a way to improve the maintenance efficiency and lessen batteries operating risks in data centers. ... Median absolute deviation …
Liu et al. [10] proposed a method for detecting the deviation from an arbitrary position of the belt conveyor based on inspection robots and deep learning, which extracts the edge of the belt by ...
Accurate detection and diagnosis battery faults are increasingly important to guarantee safety and reliability of battery systems. Developed methods for battery …
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 …
•We propose a new challenging task named power battery detection (PBD) and construct a complex PBD dataset, design an effective baseline, formulate comprehensive
Developed methods for battery early fault diagnosis concentrate on short-term data to analyze the deviation of external features without considering the long-term …
In another work, principal component analysis-based unsupervised learning offers an effective and simple method for detection of battery voltage anomaly for a large battery system consisting of ...
Without any bells and whistles, our segmentation-based MDCNet consistently outperforms various other corner detection, crowd counting and general/tiny object detection-based solutions, making it a strong baseline that can help facilitate future research in PBD. Finally, we share some potential difficulties and works for future …
In this paper, the current research progress and future prospect of lithium battery fault diagnosis technology are reviewed. Firstly, this paper describes the fault …
We propose a new challenging task named power battery detection (PBD) and construct a complex PBD dataset, design an effective baseline, formulate comprehensive metrics, …
Using online measurement to find out odd batteries in data centers is challenging due to lack of training samples since there are only a very few full charging-discharging cycles during the lifetime of batteries. In this paper, a new battery anomaly detection method based on time series clustering is proposed.
Data-driven methods have become a research hotspot in the field of battery fault diagnosis since it does not require a large amount of prior knowledge and is still efficient and robust considering the strong nonlinearity and time-varying nature of battery systems [22].For instance, Xia et al. [23] detected short-circuit faults by calculating the …
In this paper, a novel model-based fault detection in the battery management system of an electric vehicle is proposed. Two adaptive observers are …
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 measurement topologies …
Fault detection. The existing battery fault detection methods can be roughly grouped into two categories: residual evaluation for a battery cell and consistency check for a battery …
Along with global efforts to reduce the carbon footprint, electrification of powertrains is occurring in various applications, certainly including transportation systems. One of the most important components is an electric energy storage system, i.e., a battery pack. Regardless of battery form factors, such as cylindrical, pouch and prismatic type, it …
belt deviation, and specific solutions were given. It has been recognized for a long time that it is very necessary to establish a conveyor state detection system. Radio frequency identification (RFID) technology [4], Embedded conductive detection (ECD) technology [5], and an X-ray testing model [6] were proposed one after another.
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