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When Electric Vehicles Sleep: Investigating Lithium-Ion Battery Pack Precooling in Extreme Temperature Conditions University of Salento
- Format:
- Book
- Conference/Event
- Author/Creator:
- Darvish, Hossein, author.
- Conference Name:
- 17th International Conference on Engines and Vehicles (2025-09-14 : Capri, Italy)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2025
- Summary:
- Effective thermal management is essential for optimizing the performance and longevity of lithium-ion battery packs, particularly in electric vehicles facing extreme temperature conditions. This study investigates the performance of an indirect liquid cooling system used for pre-cooling stationary electric vehicle battery packs, focusing on scenarios such as vehicle sleep mode in high-temperature conditions. The cooling system, which utilizes a water-glycol mixture flowing at 1.2 L/min, was tested on a battery pack consisting of 36 prismatic battery cells in a thermally isolated chamber, subjected to initial temperatures of 50.0°C, 60.0°C, and 69.5°C. To assess the thermal behavior, 25 thermocouples were strategically positioned on the battery surface, and inlet coolant temperature was monitored via an additional thermocouple. An exponential cooling response was observed across all temperature cases, with maximum temperature difference between the hottest and coldest cells reaching 7.6°C, 10.5°C, and 12.7°C at approximately 15 minutes for initial temperatures of 50.0°C, 60.0°C, and 69.5°C, respectively. While higher initial temperatures led to longer cooling durations (37, 52, and 67 minutes for each case), the final temperature differences converged to similar values, indicating a stable cooling performance across various scenarios. The cooling behavior exhibited consistent thermal patterns, with the temperature differences slightly decreasing toward the end of the tests. Additionally, a resistance-capacitance model was calibrated to predict thermal behavior, achieving a low root mean square error and mean absolute error of 0.4°C and 0.3°C, respectively. These findings offer valuable insights for improving battery thermal management in electric vehicles, particularly during sleep periods, and contribute to the development of energy-efficient and reliable cooling strategies that ensure optimal performance and safety in extreme climates
- Notes:
- Vendor supplied data
- Publisher Number:
- 2025-24-0146
- Access Restriction:
- Restricted for use by site license
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