The DETR model is often affected by noise information such as complex backgrounds in the application of defect detection tasks, resulting in detection of some targets is ignored. In this paper, AIA DETR model is proposed by adding AIA (attention in attention) module into transformer encoder part, which makes the model pay more attention to correct defect …
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.
To this end, the study proposes an intelligent diagnosis method for battery pack connection faults based on multiple correlation analysis and adaptive fusion decision-making.
Integrated learning is applied to battery fault diagnosis where the weight matrix determines the accuracy and robustness of the integration results. The weighting matrix reflects the ability of the evidence source to provide the correct assessment or solution for solving a given problem.
Using the difference between the true SOC and the estimated SOC as the residual, the fault detection of the voltage sensor and the current sensor of the lithium-ion battery pack is cleverly realized. Only fault detection and fault isolations are discussed; the fault size and shape cannot be obtained.
The proposed method is more suitable for handling constant or slow-varying faults. Three sliding mode observers and three filters are designed, to realize fault diagnosis, isolation, and estimation in the lithium-ion battery voltage, current, and temperature sensors.
In this section, we conduct MATLAB/Simulink simulations to verify the effect of the PD observer in estimating the fault of lithium-ion battery sensors. The urban dynamometer driving schedule (UDDS) test at 25 °C of the LG 18650HG2 lithium-ion battery is selected to simulate the battery operating conditions of EVs.
The DETR model is often affected by noise information such as complex backgrounds in the application of defect detection tasks, resulting in detection of some targets is ignored. In this paper, AIA DETR model is proposed by adding AIA (attention in attention) module into transformer encoder part, which makes the model pay more attention to correct defect …
Abstract: The fault diagnosis process of battery pack is restricted to its complex internal structure, chemical characteristics and nonlinearity. Internal short circuit (ISC) fault and virtual connection (VC) fault are two imperceptible fault types that can cause severe consequence, such as thermal runaway, which may lead to fire accident. The ...
This article investigates the detection of a wire bond defect in state-of-the art battery modules of electric vehicles based on current pulses and DVA using the sensor …
978-1-5386-3524-7/17/$31.00 ©2017 IEEE 235 Multi-fault Online Detection Method for Series-connected Battery Packs Yongzhe Kang, Bin Duan, Yunlong Shang, Zhongkai Zhou, Chenghui Zhang*
The first layer strategy is like the threshold-based fault detection method, if the battery voltage is lower than the discharge cut-off voltage, the battery is considered to have an …
Battery management systems are highly dependent on sensor measurements to ensure the proper functioning of lithium-ion batteries. Therefore, it is imperative to develop a suitable fault diagnosis scheme for battery sensors, to realize a diagnosis at an early stage.
This method increases the total capacity (Ah) of the battery pack while maintaining the same voltage as a single module. For example, if each battery module has a capacity of 100Ah, connecting three modules in parallel results in a total capacity of 300Ah at the same voltage. Advantages of Parallel Connections:
In order to verify the reliability of the battery power detection device designed in this paper, the three parts of the lithium battery, power detection module, and display terminal will be built for …
Automated robot-assisted disassembly is essential for the flexible disassembly of Li-ion battery modules for economic and safety reasons. In such a case, a CAD model for the planning process is of immense benefit. The geometric uncertainties due to the breathing of the Li-ion cells as well as the presence of component tolerances underline the importance of a …
The context augmentation module (CAM) was introduced in the feature fusion part and the deformable convolution block (DCB) was used to replace the C3 module. AD-Head, a decoupling head with an attention mechanism, was designed in the head part. The RIoU method was proposed to optimize the loss calculation for different aspect ratio objects ...
How to diagnose the multiple faults in the battery pack becomes the focus and difficulty. This paper proposes a multi-fault detection method for battery management systems. Instead of …
The detection algorithm for identifying disconnections among parallel-connected cells in a module is essential for ensuring the safe operation of the battery pack. This paper …
Abstract: The fault diagnosis process of battery pack is restricted to its complex internal structure, chemical characteristics and nonlinearity. Internal short circuit (ISC) fault and virtual …
How to diagnose the multiple faults in the battery pack becomes the focus and difficulty. This paper proposes a multi-fault detection method for battery management systems. Instead of measuring the voltage of individual cells, an interleaved connected voltage measurement method is presented which considers the effects of the contact resistance ...
SZ DJI TECHNOLOGY CO., LTD.,2021-04-15,A battery detection method, a battery, an electronic device and a storage medium. The batt...、
Battery management systems are highly dependent on sensor measurements to ensure the proper functioning of lithium-ion batteries. Therefore, it is imperative to develop a suitable fault diagnosis scheme for battery …
First, the difference sample entropy (DSE) rapidly detects suspicious battery faults to ensure high FDR. Then, the correlation coefficient method precisely diagnoses suspicious faults to significantly improve DAR. Finally, the deep neural network is used to quantify the defined state of fault (SOF) for the first time. The SOF can indicate the ...
In order to verify the reliability of the battery power detection device designed in this paper, the three parts of the lithium battery, power detection module, and display terminal will be built for system monitoring. When the terminal battery voltage is observed, the multimeter will be …
First, the difference sample entropy (DSE) rapidly detects suspicious battery faults to ensure high FDR. Then, the correlation coefficient method precisely diagnoses …
This article investigates the detection of a wire bond defect in state-of-the art battery modules of electric vehicles based on current pulses and DVA using the sensor technology available in series-production vehicles. The simulation of this defect identification methodology was parameterized on the basis of four individual lithium-ion cells ...
An insulation diagnosis method for battery pack based on battery model. To cite this article: Yanhui Zhang et al 2020 IOP Conf. Ser.: Mater. Sci. Eng. 793 012061. View the article online for ...
Internal short circuit (ISCr) is one of the major obstacles to the improvement of the battery safety. The ISCr may lead to the battery thermal runaway and is hard to be detected in the early stage. In this work, a new ISCr detection method based on the symmetrical loop circuit topology (SLCT) is introduced. The SLCT ensures that every battery has the same priority in …
2 · Introduction of a comprehensive framework for SOH estimation of battery modules: By integrating the abovementioned probabilistic model for current distribution, the terminal voltage …
The detection method of battery parameters in battery management system is simple and the accuracy is limited [[27], [28] ... Structure of the battery pack. (a) Battery unit. (b) One battery module. (c) The connecting structure of the module. [10]. Kong et al. [113] proposed a diagnostic method for detecting microshort circuits (MSC) of lithium-ion cell batteries based …
To this end, the study proposes an intelligent diagnosis method for battery pack connection faults based on multiple correlation analysis and adaptive fusion decision-making. The method uses Pearson correlation coefficients (PCC), Spearman correlation …
The detection algorithm for identifying disconnections among parallel-connected cells in a module is essential for ensuring the safe operation of the battery pack. This paper introduces a novel method for detecting contact loss among parallel-connected cells by utilizing the state of charge (SOC) change rate of the cells. The ...
2 · Introduction of a comprehensive framework for SOH estimation of battery modules: By integrating the abovementioned probabilistic model for current distribution, the terminal voltage estimation method, i.e., L-EKF, and the adversarial domain distribution probability network (AdaDDPN), a comprehensive framework for SOH estimation of individual cells within battery …
To this end, the study proposes an intelligent diagnosis method for battery pack connection faults based on multiple correlation analysis and adaptive fusion decision-making. The method uses Pearson correlation coefficients (PCC), Spearman correlation coefficients (SCC), and Kendall correlation coefficients (KCC) to simultaneously quantify the ...
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