Study on the Influence of Flat Heat Pipe Structural Parameters in Battery Thermal Management System

Abstract

Battery performance and lifespan are greatly dependent on its temperature, and a good battery thermal system (BTMS) can make the battery work at its favorable temperature range, improve its electrical performance, and extend its lifespan. Due to the high heat conductivity and large surface area of flat heat pipe (FHP), the FHP-based BTMS can quickly remove the heat produced by the battery and improve the temperature homogeneity among cells in the pack. In this study, the FHP is applied to the BTMS, and the influence of its structure on the battery thermal dynamics is studied. Firstly, a coupled thermal model for the FHP-based BTMS is established and verified by the experiment. This model integrates the resistance-based thermal model of the battery and FHP model based on the thermal resistance network. Then, the effect of the structure parameters of FHP such as the thickness, porosity, and particle diameter of sintered wick on the thermal performance of the battery is investigated. According to the results, the temperature variation among battery cells rises significantly when the dimensionless thickness of the wick is greater than 0.7. Moreover, the change of the porosity and particle diameter of the wick results in a nonlinear development of the wick thermal resistance which finally changes the heat conductivity of the FHP and battery temperature. Finally, a neural network model (NNM) is used to establish the relationship between the FHP parameters and battery thermal performance for optimizing the BTMS structure. According to optimization result, the optimized FHP can keep the maximum battery temperature below 40°C at a discharge rate of 2C and reduce the temperature variation in the battery by 7.4%.

A novel heat dissipation structure based on flat heat pipe for battery thermal management system

“…R is the FHP thermal resistance which is calculated based on the thermal resistance model in our previous study in Ref. 29 For batteries under different discharge rates from 2C to 4C, the thermal conductivity of FHP is around 2000 (±20%) WÁm À1 ÁK À1 . So in this paper, the thermal conductivity is set 2000 WÁm À1 ÁK À1 .…”

“…l and S are the length and sectional area, respectively. R is the FHP thermal resistance which is calculated based on the thermal resistance model in our previous study in Ref 29 . For batteries under different discharge rates from 2C to 4C, the thermal conductivity of FHP is around 2000 (±20%) W·m −1 ·K −1 .…”

“…The flat heat pipe (FHP) can significantly increase the contact area with batteries compared to conventional one-dimensional heat pipes, efficiently flattening the battery temperature distribution and reducing thermal resistance. 29 Moreover, FHP can provide flexibility with the BTMS's compact structure suited for a flying car electric propulsion system. Zhao et al 30 designed an ultra-thin FHP and studied the thermal performance of four pouch batteries at high discharge rates.…”

A Hybrid Data-Driven Method to Predict Battery Capacity of Medical Devices and Analyze Component Effects

“…With the quick development of data science, artificial intelligence, and cloud platform, data-driven approaches have become a promising and powerful tool in the field of Li-ion battery management (Lucu et al, 2018;Li et al, 2019;Liu et al, 2022b). Specifically, lots of data-driven approaches are derived for estimating the internal states of batteries (Feng et al, 2020a;Feng et al, 2021;Shi et al, 2021;Tang et al, 2021), predicting battery aging trajectories (Hu et al, 2022a;Hu et al, 2022b;Liu et al, 2022c) and remaining useful life (Liu et al, 2020a;Ren et al, 2020;Hu et al, 2021), balancing battery cells (Feng et al, 2020b;Liu et al, 2020b), performing effective battery charging (Liu et al, 2017;Xie et al, 2020), and energy management Wang et al, 2022;Xie et al, 2022;Zhang et al, 2022). In summary, according to the well-designed data-driven approaches, reliable management could be achieved to improve battery operational performance.…”