Numerical Modelling of Coolant Filling and De-aeration in a Battery Electric Vehicle Cooling System

Event
WCX SAE World Congress Experience
Authors Abstract
Content
Trapped air bubbles inside coolant systems have adverse effect on the cooling performance. Hence, it is imperative to ensure an effective filling and de-aeration of the coolant system in order to have less air left before the operation of the coolant system. In the present work, a coolant/air multiphase VOF method was utilized using the commercial CFD software SimericsMP+® to study the coolant filling and subsequent de-aeration process in a Battery Electric Vehicle (BEV) cooling system. First, validations of the numerical simulations against experiments were performed for a simplified coolant recirculation system. This system uses a tequila bottle for de-aeration and the validations were performed for different coolant flow rates to examine the de-aeration efficiency. A similar trend of de-aeration was captured between simulation and experimental measurement. Next, the same numerical techniques were further applied to a BEV cooling system to evaluate the efficiency of de-aeration processes. The first step of the process involved a vacuum filling simulation. After the filling process, the air remained in the system is about 10% of total system volume. Different combinations of a multi-position valve and pump on/off cycles strategies were explored to decrease trapped air in the system. It is found that the opening/closing strategy of the multi-position valve plays a crucial role for an effective de-aeration. The devised methodology is observed to be numerically robust and accurate, while having good computational efficiency for modelling the coolant filling and de-aeration process that takes large physical time.
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DOI
https://doi.org/10.4271/2022-01-0775
Pages
9
Citation
Tao, M., Slike, J., Bhagat, M., Srinivasan, C. et al., "Numerical Modelling of Coolant Filling and De-aeration in a Battery Electric Vehicle Cooling System," SAE Int. J. Adv. & Curr. Prac. in Mobility 5(1):75-83, 2023, https://doi.org/10.4271/2022-01-0775.
Additional Details
Publisher
Published
Mar 29, 2022
Product Code
2022-01-0775
Content Type
Journal Article
Language
English