Analysis and Optimization of Oil Cooling Structure for Electric Vehicle Power Motor

Abstract Efficient thermal management constitutes the key to guarantee the power output of electric vehicle power motors under high temperature environments and high load conditions. This study presents an oil cooling structure design aimed at ensuring the efficient operation of motors. The design concept was founded on five cooling structures, namely Parallel Channel (PC), Series Channel (SC), and Composite Series Channel (CSC) with 2, 3, and 4 branches in each pass respectively, and an optimization study was carried out on the external embedded oil cooling structure of stator for automotive permanent magnet synchronous motor (PMSM). The cooling performance and pressure drop from inlet to outlet were analyzed and compared among different oil cooling structures, based on which the CSC with 4 branches was determined as the basis for further optimization. The Performance Evaluation Criteria (PEC) was introduced in the structure evaluation to analyze the impact of channel form and channel dimension on cooling effect. The results of the study demonstrated that Case III (a composite series channel with height of 4 mm and width of 10 mm) was the best structure. Under rated condition, when the flow rate of coolant is 5 lpm, Case III reduces the average temperature of motor to 82.47 °C and the pressure drop to 57.442 kPa, which results in a 2.98% reduction in average temperature and a 19.77% reduction in pressure drop compared with CSC4. The cooling effect under peak power and peak torque conditions was analyzed, and the effectiveness of the structure was validated.

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Publication Details

Journal
Journal of Thermal Science and Engineering Applications
Published
2025-03-06
DOI
https://doi.org/10.1115/1.4068123
Citations
1
Primary Topic
Real-time simulation and control systems
Type
article
Field-Weighted Citation Impact
1.21

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article

Analysis and Optimization of Oil Cooling Structure for Electric Vehicle Power Motor

Shichun Yang, Tianshi Zhang, Haibo Chen, Yupeng Sun et al.
1 citations
Journal of Thermal Science and Engineering Applications
Real-time simulation and control systems
1.21
article

Analysis and Optimization of Oil Cooling Structure for Electric Vehicle Power Motor

Shichun Yang, Tianshi Zhang, Haibo Chen, Yupeng Sun, Haizhen Huang, Xiaoyan Liu
article en
1 citations

Abstract

Abstract Efficient thermal management constitutes the key to guarantee the power output of electric vehicle power motors under high temperature environments and high load conditions. This study presents an oil cooling structure design aimed at ensuring the efficient operation of motors. The design concept was founded on five cooling structures, namely Parallel Channel (PC), Series Channel (SC), and Composite Series Channel (CSC) with 2, 3, and 4 branches in each pass respectively, and an optimization study was carried out on the external embedded oil cooling structure of stator for automotive permanent magnet synchronous motor (PMSM). The cooling performance and pressure drop from inlet to outlet were analyzed and compared among different oil cooling structures, based on which the CSC with 4 branches was determined as the basis for further optimization. The Performance Evaluation Criteria (PEC) was introduced in the structure evaluation to analyze the impact of channel form and channel dimension on cooling effect. The results of the study demonstrated that Case III (a composite series channel with height of 4 mm and width of 10 mm) was the best structure. Under rated condition, when the flow rate of coolant is 5 lpm, Case III reduces the average temperature of motor to 82.47 °C and the pressure drop to 57.442 kPa, which results in a 2.98% reduction in average temperature and a 19.77% reduction in pressure drop compared with CSC4. The cooling effect under peak power and peak torque conditions was analyzed, and the effectiveness of the structure was validated.

Journal of Thermal Science and Engineering ApplicationsVol. 17(6)
Jilin University (CN), Changchun Observatory (CN), First Automotive Works (China) (CN), Beijing Haidian Hospital (CN), Beihang University (CN), Volkswagen Group (United States) (US)
Natural Science Foundation of Jilin Province
Openalex Percentile: Top 24%
Real-time simulation and control systems
1.21
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