Thermal behavior of nickel–metal hydride battery during charging at a wide range of ambient temperatures

Fang, Kai; Mu, Dao Bin; Chen, Shi; Wu, Feng; Zeng, Xiao Jun

doi:10.1007/s10973-010-1249-z

Cited by 9 publications

(2 citation statements)

References 14 publications

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“…To evaluate the battery heat generation, a common practice is to use direct or indirect calorimetry techniques. 6,14 An alternative approach is to approximate the heat generation rate from electrical performance of the battery, i.e., experimental voltage-time data. 1,15 In the present paper the latter approach is employed to approximate the heat generation rate in the sample NiMH cell during rapid-charging processes with overcharging periods.…”

Section: Thermal Modelmentioning

confidence: 99%

A Computationally-Effective Thermal Model for Spirally Wound Nickel-Metal Hydride Batteries

Yazdanpour

Taheri

Bahrami

2013

J. Electrochem. Soc.

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A new two-dimensional analytical model is developed to investigate the transient thermal behavior of spirally wound batteries. The proposed model is used to analyze the thermal response of a 8 ampere-hour cylindrical nickel-metal hydride (NiMH) battery under fast-charging processes with overcharging periods. Based on the method of integral transformation, a series-form solution for the temperature field in cylindrical batteries is obtained that takes account for transient heat generation, orthotropic heat conduction, and convective heat dissipation. The accuracy of the theoretical solution is tested through comparison with numerical solution and experimental data. Our comparisons show that even the first term of the series solution suffices to accurately describe the two-dimensional temperature field inside the battery core with the modest computational effort.

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Section: Thermal Modelmentioning

confidence: 99%

A Computationally-Effective Thermal Model for Spirally Wound Nickel-Metal Hydride Batteries

Yazdanpour

Taheri

Bahrami

2013

J. Electrochem. Soc.

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“…Liao 17 considered that observational check and capacity measurement are preliminary ways to classification of retired cells and there is no correlation between capacity and Ohm resistance. Fang 18 started from the thermal behavior and built a self‐organizing map (SOM) model affiliated to the artificial neural network to classify the Nickel‐Hydrogen cells. The SOM model used to divide the cells into high‐heat, medium heat and low heat generation cells.…”

Section: Introductionmentioning

confidence: 99%

A novel fast estimation and regroup method of retired lithium‐ion battery cells

et al. 2020

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With the commercialization of the electric vehicles, the large-scale lithium-ion cells as the power of electric vehicles are to be retired. The second-use of retired cells is of great significance to improve the battery economy. A fast classification and regroup evaluation method of the retired lithium-ion cells are proposed in this paper to improve the classification efficiency of retired lithium-ion cells and adapt to the regroup under different conditions. The lithium-ion cells after being balanced in parallel are charged in series with a constant current. A support vector regression (SVR) model with the parameters optimized by the particle swarm optimization (PSO) algorithm is built for the fast capacity estimation and the error will not exceed 0.3%. Different cells regrouped means different performance. In order to improve the consistency of retired cells and satisfy different using conditions, a Weighted-K-means algorithm is proposed in this paper to regroup the cells with the known capacity and internal resistance. The classification method is evaluated by the voltage consistency of cells using different working conditions, which indicates capacity occupied a large proportion can meet the requirement of energy condition meanwhile keep a good consistency. But the resistance will dominate in algorithm under conditions which have requirement for instantaneous power.

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