Degradation and Dependence Analysis of a
A high regression coefficient (R2 > 0.9) and low p-value < 0.0001 indicated that the correlation of the degradation process was effectively quantified. The results
HDGC3985 Battery Charging and Discharging Tester
HDGC3985 multi-purpose intelligent battery charging and discharging tester use to perform battery constant current discharge, intelligent charging and activation, which can reduce enterprise cost and maintenance personnel labor intensity.
Analysis of BYD''s Battery Management System Functionality
The battery cell group is connected to the first end for charging/discharging, the management system is connected to the second and third ends for powering. The system allows charging any battery pack in the system, isolating failed packs, adjusting conversion efficiency, providing backup power during grid outages, and connecting multiple
Safety risk assessment for automotive battery pack based on
Safety risk assessment is essential for evaluating the health status and averting sudden battery failures in electric vehicles. This study introduces a novel safety risk
Fault Diagnosis and Abnormality Detection of Lithium-ion Battery
the designed coefficient, the systematic faults of battery pack and possible abnormal state can be timely diagnosed. 2) The t-SNE technique, The K-means clustering and Z-score methods are
Charging control strategies for lithium‐ion
However, a battery pack with such a design typically encounter charge imbalance among its cells, which restricts the charging and discharging process . Positively, a
Safety risk assessment for automotive battery pack based on
In the battery pack, the voltage of the cell with minimum capacity will show the fastest growth rate in the charging process and the fastest drop rate in the discharging process (Lamb et al., 2014; Zheng et al., 2014). Correspondingly, the voltage of this cell is lower than others at the low SOC range but becomes higher than the normal cells at the high SOC range,
Integrated framework for battery cell state-of-health estimation in
The fast charging testing platform consists of a switch, battery charging and discharging tester, programmable constant temperature and humidity chamber, and computer for data recording. Intelligent state of health estimation for lithium-ion battery pack based on big data analysis. J Energy Storage, 32 (2020), Article 101836, 10.1016/j.est
Analysis of the Charging and Discharging
This article studies the process of charging and discharging a battery pack composed of cells with different initial charge levels. An attempt was made to determine the risk of
Analysis of cell-level abnormality diagnosis based on battery pack
Download Citation | On Nov 28, 2023, Woochan Kam and others published Analysis of cell-level abnormality diagnosis based on battery pack voltage information | Find, read and cite all the research
Electric vehicle battery pack micro-short circuit fault diagnosis
The charging and discharging of the battery pack is controlled by BTS-600, the thermal chamber is responsible for the temperature of the working environment of the battery pack, and the data acquisition devices are accountable for measuring the status information of each cell. On the other hand, the MSC battery has an abnormal ageing
Data–Driven Fault Diagnosis and
Cells with high SOC reach the charge cut-off voltage first, whereas cells with low SOC reach the discharge cut-off voltage first in the battery pack. However, even in a normal
Multi-fault diagnosis of lithium battery packs based on
Highlights • The multi-fault diagnosis strategy including mixed faults is proposed. • The study using locally weighted Manhattan distance in the discharge phase of
Consistency evaluation and cluster analysis for lithium-ion battery
Signal processing-based: These methods refer to time-domain analysis and frequency-domain analysis. The impedance spectroscopy can directly reflect the electrochemical characteristics of batteries. In Ref. [28], it is applied to investigate the effect of aging on the pack consistency.Ref. [29] presents a method for evaluating battery voltage consistency based on a
Fault Diagnosis and Abnormality Detection of Lithium-ion Battery
Through comprehensive analysis of operation data of the battery pack in E-scooters, we use the statistical technology to analyze the distribution characteristics of each parameter in battery
Charge and discharge strategies of lithium-ion battery based on
By clarifying each capacity loss at different charge and discharge rates and cut-off voltages, it can be concluded that the battery can obtain the better anti-aging characteristics and safety performance with the 1C charge rate, 3.95 V charge cut-off voltage and the 1C discharge rate, 3.00 V discharge cut-off voltage.
Designing a battery Management system for electric vehicles: A
Battery system energy efficiency and operational expenses depend on BMS efficiency. BMS charging and discharging efficiency will be assessed using a congregated approach. The BMS controls the flow of electrical energy into the battery pack to charge the cells efficiently. Efficiency investigation involves assessing charging energy losses.
Fault Diagnosis and Abnormality Detection of Lithium
This study investigates a novel fault diagnosis and abnormality detection method for battery packs of electric scooters based on statistical distribution of operation data that are stored in the
Analysis of the Charging and Discharging Process of LiFePO4 Battery Pack
calculate the SoC change during the charging/discharging cycle according to the following relationship: ΔSoC L 1 C l ±I :t ;dt X 4 (1) where Cn denotes nominal battery capacity, I is charge/discharge current, t is time, and T denotes charge/discharge time.
Anomaly Detection for Charging Voltage Profiles in
For a large lithium battery pack within an energy storage station, the RPCA-based anomaly detection method proposed in this article can effectively detect and identify abnormal battery cells within the battery pack.
Degradation and Dependence Analysis of a Lithium
The unbalanced state will make the degradation process more complex and cause abnormal discharge parameters, which brings challenges in the analysis of the state of health (SOH) of battery packs.
An intelligent diagnosis method for battery pack connection
The safety status of the battery pack is usually monitored by the Battery Management System (BMS) installed in the electric vehicle. The BMS [9] evaluates the state of the battery pack by using signals such as current, voltage, and temperature collected during the operation of the battery system.However, the existing techniques mainly focus on the accuracy
Battery Pack Modeling for the Analysis of Battery Temperature
The temperature and current management of battery storage systems are crucial for the performance, safety, and longevity of electric vehicles (EVs). This paper describes a battery temperature and current monitoring and control system for a battery EV storage system that allows for real-time temperature and current monitoring and control while charging and
Method for judging abnormality of battery pack, and battery pack
the cell voltage When the cell voltage reaches the end voltage Vm, the cell voltage is switched to a constant current (CC) charge region, and the terminal voltage of the charge / discharge terminal of the battery pack is 4.2 V per cell, which is a predetermined end voltage Vf For example, in the case of 3 cells in series, the end voltage Vf is applied to the charging terminal until 12.6 V
Anomaly Detection Method for Lithium-Ion
The data analysis and experimental verification results based on actual vehicle operating conditions indicate that this method can accurately identify an abnormal
EP2632016A1
EP2632016A1 EP11834134.6A EP11834134A EP2632016A1 EP 2632016 A1 EP2632016 A1 EP 2632016A1 EP 11834134 A EP11834134 A EP 11834134A EP 2632016 A1 EP2632016 A1 EP 2632016A1 Authority
Analysis of 7 Functions of Power Battery BMS
BMS has the function of battery protection, which can monitor abnormal conditions such as overcharge, overdischarge and overtemperature of the battery pack, cut off the power supply in time or take other protective measures to prevent battery damage or safety accidents. 3. Battery balance control. during the charging and discharging process
A comprehensive review of the lithium-ion battery state of health
Lithium-ion battery aging macro performance is manifested as the reduction of battery pack performance, the reduction of vehicle mileage, the rapid decline in power, the abnormal temperature during charging and discharging, and the battery drum. The main macro factors affecting battery aging are the following four aspects: 1.
Data–Driven Fault Diagnosis and Cause Analysis of
full charging, the charge and discharge voltage data were generated by designating the SOC as 100–97% using a simulation. The SOCs were assigned as Cell 1 = 100%, Cell 2 = 99%,
Cloud Platform-Oriented Electrical Vehicle Abnormal
Cloud Platform-Oriented Electrical Vehicle Abnormal Battery Cell Detection and Pack Consistency Evaluation With Big Data: Devising an Early-Warning System for Latent Risks November 2021 IEEE
Battery management system (BMS) function, failure analysis
10. Thermal management function: the collected temperature of each point of the battery pack, during charging and discharging, BMS decides whether to turn on heating and cooling; 11. Network function: including online calibration and health, online program download. When a communication interruption or control abnormality occurs in the
A Method for Abnormality Detection of Lithium-Ion Battery
Accordingly, this paper proposes a feature selection method based on Kullback-Leibler (K-L) test and an improved Greenwald-Khanna (GK) clustering algorithm.
6 FAQs about [Battery pack charging and discharging abnormality analysis]
How can faults detection and abnormality of battery pack be detected?
As discussed above, the faults diagnosis and abnormality of battery pack can be detected in real time. In addition, timely detection and positioning of faults and defects of cells can improve the health and safety of the whole battery pack.
Why do we need to detect abnormal cells in a battery pack?
When the malfunction worsens, the degree of abnormality in the battery will rapidly evolve, ultimately leading to safety accidents. Therefore, we need to detect abnormal cells within the battery pack before the battery fault deteriorates.
Can a battery cell anomaly detection method prevent safety accidents?
Therefore, timely and accurate detection of abnormal monomers can prevent safety accidents and reduce property losses. In this paper, a battery cell anomaly detection method is proposed based on time series decomposition and an improved Manhattan distance algorithm for actual operating data of electric vehicles.
Can a voltage abnormal detection method predict a faulty battery?
Reference proposes a voltage abnormal detection method for electric vehicle batteries based on modified Shannon entropy and standard deviation, which can predict the exact times and locations of faulty batteries in battery packs ahead of time.
Can RPCA-based anomaly detection detect a large lithium battery pack?
For a large lithium battery pack within an energy storage station, the RPCA-based anomaly detection method proposed in this article can effectively detect and identify abnormal battery cells within the battery pack.
Can voltage fault diagnosis detect an aberrant battery cell accurately?
Therefore, the proposed method for voltage fault diagnosis can detect the aberrant battery cell accurately in a timely manner, thereby enabling great significance to prognosis and safety management of future battery failures. In this study, a large amount of voltage data are analyzed based on the Gaussian distribution.