Optimization of hybrid thermal management system in electric vehicle lithium-ion battery using mini-channel cooling and copper-foam-enhanced phase change material
Year: 2026
Type: article
Abstract: One of the most critical challenges in developing modern electric vehicles (EVs) is the thermal control and regulation of the lithium-ion batteries (LIBs). It is crucial for the batteries to operate in a safe temperature range, which prevents thermal runaway and battery degradation. Numerous studies have been conducted over the past decades in order to regulate the thermal performance of LIBs and stabilize their surface temperature (ST). The present study investigates three cases for the battery's cooling system which include passive, active, and hybrid systems. The deficiencies of each case are identified and in case 3, a novel, optimal hybrid battery thermal management system (BTMS) for a single 26,650 LIB is developed. The system integrates a helical mini-channel within a paraffin RT-35 phase change material which is enhanced with copper foam. The changes in geometrical parameters of the system affect the temperature reduction performance. Therefore, three geometrical parameters related to the helical mini-channel, PCM and copper foam were investigated with the goal of optimizing the cooling mechanism's design and minimize the ST. The numerical approach, genetic algorithm (GA) as well as artificial neural network (ANN) are employed in order to optimize the system's performance. The optimal hybrid design is then expanded to a battery pack comprising 9 batteries. The findings indicate that the combination of active and passive techniques significantly improves the efficiency of the BTMS. Out of the three cases, the hybrid thermal management system exhibited the lowest ST, and test 3 of the hybrid cooling system design achieved the highest efficiency in temperature reduction and proved to be the optimal hybrid BTMS, with a superior performance of 92.46% with respect to pure PCM and 22.5% compared to the liquid cooling system of case 2.
Source: Journal of Energy Storage
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,560
OpenAlex ID: W7203883744