Influence of uncertainty of thermal conductivity on prediction accuracy of thermal model of lithium-ion battery
IEEE Transactions on Transportation Electrification(2024)
Abstract
This study employed the transient plane source method (TPS) to measure the battery’s thermal conductivity. The probe heated the battery and collected its temperature. Based on the measured temperature, the thermal conductivity was calculated. Then, this tested thermal conductivity is compared with the theoretical value to get the prediction error of the theoretical algorithm. For the 27 Ah battery, the relative error of thermal conductivity through material layer
kx
is 30.2%, while those of thermal conductivities along material layer
ky
and
kz
are 89.8%. Then, a three-dimensional thermal model based on the thermal network was established, and it applied the calculated and measured thermal conductivity to quickly predict battery temperature distribution at discharging rate from 1 C to 6 C. According to the results, the theoretical model for thermal conductivity should be used at a discharging rate below 3 C, or a great prediction error is produced. To further improve the prediction accuracy of battery temperature field at high discharging rates, the error set of the thermal conductivity was built, and the threshold of the error was explored. The relative error of
kx
should vary between 15% and -15% and those of
ky
and
kz
should be below -45%. Moreover, the prediction error of the battery temperature is small, as the relative errors of
ky
and
kz
increase from 15% to 90%.
MoreTranslated text
Key words
Electric vehicles,lithium-ion battery,temperature simulation,thermal conductivity
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined