A novel classification method of commercial lithium-ion battery cells based on fast and economic detection of self-discharge rate

Zheng, Yuejiu; Wu, Hang; Wei, Yi; Lai, Xin; Dai, Haifeng; Han, Xiao; Ouyang, Minggao

doi:10.1016/j.jpowsour.2020.229039

Cited by 40 publications

(11 citation statements)

References 27 publications

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“…The above experiments show that when the count of cells to be measured is large and a single parallel sorting channel cannot meet the requirements, this continuous sorting scheme proposed in this paper can be adopted. Compared with our previously proposed scheme of sorting after equalization, 30 the method proposed in this paper removes the equalization (half an hour) and the shelving process after equalization (several hours), which not only greatly saves time, but also greatly reduces the complexity of operation. The parallel sorting channel proposed in this paper only takes half an hour to an hour to complete a single sorting, which is more suitable for commercial applications.…”

Section: Continuous Sorting Experiments and Simulation Resultsmentioning

confidence: 99%

“…The self‐discharge current is produced by paralleling resistance at both ends of the cells. Because the designed method is highly sensitive to the corresponding curve of OCV‐SOC, we have previously studied the sensitivity difference at different SOC positions 30 . At lower or higher SOC, the experimental results will be obvious with the increase of SOC and OCV curve slope, and it is easier to find the relationship between self‐discharge rate and parallel sorting branch current.…”

Section: Methodsmentioning

confidence: 99%

“…As the above detection methods cannot measure the SDR with a low cost and high efficiency, we previously proposed a large-scale parallel equalization method. 30 Ensuring that the voltage of the cells is completely consistent during the period of "pre-parallel" equalization. After equalization, the cells are put into the parallel sorting channel which has ammeters.…”

Section: Introductionmentioning

confidence: 99%

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An expeditious and simple scheme for measuring self‐discharge rate of lithium batteries

Hao

Han

et al. 2022

Intl J of Energy Research

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Summary The inconsistency of the self‐discharge rate of each cell in series has an impact on the capacity of the battery pack, which is one of the best interpretations of the Cannikin Law. The cells with high self‐discharge rate in series determine the pack capacity. In addition, the cells with high self‐discharge rate usually means lower reliability and higher safety risk. Compared to traditional measurement methods, we previously proposed a method to calculate the self‐discharge rate by “pre‐parallel” equalization and then observing the current change of parallel branch. However, this method still has the problems of time‐consuming and difficult in batch sorting. This paper replaces the previous “pre‐parallel” operation with the initial voltage measurement of the cells. Combined with the established equivalent circuit model, the self‐discharge rate of each cell is calculated. The method further shortens the measurement time, which is suitable for sorting the cells in batches. The results show that the method can identify the absolute self‐discharge rate of each cell in a shorter time with relatively high accuracy.

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Section: Continuous Sorting Experiments and Simulation Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An expeditious and simple scheme for measuring self‐discharge rate of lithium batteries

Hao

Han

et al. 2022

Intl J of Energy Research

Self Cite

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show abstract

“…[ 10 ] In the process of battery equivalent circuit measurement, a model of the battery equivalent circuit was established. Zheng et al established a first‐order RC circuit model of a battery [ 11 ] and used an equivalent parallel circuit model to estimate its relative self‐discharge rate. However, only the first‐order RC circuit has been used to equate the complex internal self‐discharge mechanism of the battery, and the accuracy of the model needs to be improved.…”

Section: Introductionmentioning

confidence: 99%

Self‐Discharge Voltage Drop Estimation Method Based on Improved Gaussian Process Regression

et al. 2022

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The self-discharge rate is an important index for determining the quality of a lithium-ion battery. Currently, the self-discharge of a battery is mainly determined through experimental tests, which are time-consuming and laborious. To provide a fast and reliable self-discharge rate estimation, an improved Gaussian process regression (GPR) model based on the charge-discharge curve is proposed to estimate the self-discharge voltage drop. In this method, the voltage features extracted from the charge-discharge curve are used as the input of the GPR model. These features reflect the self-discharge performance of batteries from different angles. The gray correlation analysis method is used to analyze the degree of correlation between the selected features and self-discharge voltage drop. Furthermore, a kernel function suitable for voltage drop estimation is selected. Simultaneously, the GPR model is adjusted, and the particle swarm optimization algorithm is used to optimize the superparameters of the GPR model to improve the estimation accuracy of the self-discharge voltage drop of the model. The selfdischarge voltage drop data from the experiment are used to demonstrate the estimation effect of the proposed method. The results reveal that this method is reliable and has a high estimation accuracy for the self-discharge voltage drop.

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“…[ 6 ] The power and capacity fade faster with calendar and cycle aging. [ 7 ] A higher self‐discharge rate [ 8 ] is also a common problem at high temperatures. [ 9 ] While in a cold environment, the power and energy over the entire discharge profile are reduced.…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation of the Collective Impact of Electric Current and Ambient Temperature on the Thermal and Electrical Parameters of Lithium Iron Phosphate Cells

Naik

Nandgaonkar

2021

Energy Tech

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The performance of a lithium‐ion battery depends on the collective impact of discharge current and ambient temperature. Herein, three aspects of such impact are investigated. The first is the relationship between the thermal parameters. At 0 ºC ambient temperature and 1 C discharge rate, the heat generation rate initially increases to more than 50 kW m−3 and then dips by almost 20% due to a consequent rise in battery temperature. The second aspect is the relationship between the thermal and the electrical parameters. The steep rise in battery temperature at low ambient temperatures lifts up the voltage and improves the electrical performance more than expected. The third aspect is the collective impact of ambient temperature and electric current on the battery performance. At 0 °C ambient temperature, an increase in current from 1 to 1.5 C increases the temperature rise rate by more than two. This increases the battery capacity by at least 6% compared with that at a 1 C rate. The investigation results are expected to improve the understanding of the collective impact of current and ambient temperature on battery performance and provide a guideline for developing an optimized thermal management system.

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A novel classification method of commercial lithium-ion battery cells based on fast and economic detection of self-discharge rate

Cited by 40 publications

References 27 publications

An expeditious and simple scheme for measuring self‐discharge rate of lithium batteries

An expeditious and simple scheme for measuring self‐discharge rate of lithium batteries

Self‐Discharge Voltage Drop Estimation Method Based on Improved Gaussian Process Regression

Experimental Investigation of the Collective Impact of Electric Current and Ambient Temperature on the Thermal and Electrical Parameters of Lithium Iron Phosphate Cells

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