摘要
针对高功率密度电机散热困难的问题,设计了一种端部绕组浸没式冷却的油冷散热结构,研究了端部绕组浸没式冷却电机的散热结构设计与优化方法。基于传热学及电磁学理论,分析了电机内部热源的分布情况,通过仿真模拟分析了极限工况下油冷电机的温度分布和流动特性;定量研究了油碗、油道结构参数对电机最高温度及油道压降的影响;基于响应面法进行多目标优化试验设计,利用带精英策略的非支配排序的遗传算法(NSGA-Ⅱ)得到最优解,并通过仿真模拟验证了优化结果的有效性和可行性。结果表明:优化后电机最高温度为139.7℃,比优化前的最高温度161.3℃降低了21.6℃,降幅为13.4%。同时,油道压降由65.6 kPa下降至39.3 kPa,降低了26.3 kPa,降幅为40.1%。进行优化设计后,油冷电机的散热性能显著提高,有利于提高电机的工作效率和寿命。本研究对于电机散热结构的设计与优化具有一定的理论指导和实际应用价值。
To address the difficulty in heat dissipation in high power density motors,this paper designs an oil-cooled heat dissipation structure with submerged cooling of the end winding and studies the design and optimization method of the heat dissipation structure of the motor with submerged cooling of the end winding.Firstly,based on the theory of heat transfer and electromagnetism,the distribution of heat sources inside the motor is analyzed,and the temperature distribution and flow characteristics of the oil-cooled motor under the extreme working condition are analyzed by simulation.Then,the effects of the structural parameters of the oil bowl and oil channel on the maximum temperature of the motor and the pressure drop of the oil channel are quantitatively investigated.Finally,the multi-objective optimization experiment is conducted based on the response surface method,and a non-dominated sorting genetic algorithm(NSGA-Ⅱ)with elite strategy is employed to obtain the optimal solution.The validity and feasibility of the optimization results are verified by simulation.Our results show the maximum temperature of the motor is 139.7℃after optimization,21.6℃or 13.4%lower than the maximum temperature of 161.3℃before optimization.Meanwhile,the pressure in the oil channel drops from 65.6 kPa to 39.3 kPa,a reduction of 26.3 kPa or 40.1%.After the optimized design,the thermal performance of the oil-cooled motor improves significantly,which is conducive to the improvement of the efficiency and lifespan of the motor.Our study may provide some references for the design and optimization of motor heat dissipation structure.
作者
张志刚
曾辉
ZHANG Zhigang;ZENG Hui(Key Laboratory of Advanced Manufacturing Technology of Automobile Parts Ministry of Education,Chongqing University of Technology,Chongqing 400054,China)
出处
《重庆理工大学学报（自然科学）》
CAS
北大核心
2024年第5期61-70,共10页
Journal of Chongqing University of Technology：Natural Science
基金
国家自然科学基金项目(52172355)
重庆市高校创新研究群体项目(CXQT21027)。
关键词
浸没式冷却
温度分布
NSGA-Ⅱ算法
多目标优化
immersion cooling
temperature distribution
NSGA-Ⅱalgorithm
multi-objective optimization
