摘要
为了进一步优化提升增程式电动汽车经济性和动力性,设计了驱动模式下增程器需求功率稳态化功率跟随控制策略,使用Cruise软件建立整车模型并配置各部件参数,利用MATLAB/Simulink对控制策略进行建模,通过MATLAB-Cruise联合仿真。结果表明:实际车速可以在NEDC工况下跟随期望的速度曲线;车辆的动力性和经济性均优于设定的性能指标,纯电续航里程为88.86 km,汽车综合续航里程达到567.12 km,最高车速163.34 km/h,最大爬坡度32.37%,100 km加速时间为10.75 s。由此可知增程器需求功率稳态化功率跟随控制策略有效。选取主减速器传动比、风阻系数、迎风面积作为优化变量,以100 km加速时间和100 km油耗为目标函数,经过多岛遗传算法(MIGA)的迭代计算后得出优化后的参数数据。优化结果表明:优化后的最高车速降低了4.25%,100 km加速时间降低了2.05%,最大爬坡度增加了3.31%,综合油耗降低了6.09%。优化后的各参数不仅能够满足整车动力性要求,而且经济性也有一定程度的提升,使得整车综合性能得到改善。
To further optimize the economy and dynamic performance of extended-range electric vehicles,this study designed a steady-state power-following control strategy for the range-extender′s power demand in driving mode.A full-vehicle model was established using Cruise software with component parameters configured,and the control strategy was modeled in MATLAB/Simulink.Co-simulation results showed that the actual vehicle speed could follow the target NEDC cycle,with pure electric range reaching 88.86 km,combined range achieving 567.12 km,top speed of 163.34 km/h,maximum gradeability of 32.37%,and 0-100 km/h acceleration time of 10.75 s.The final drive ratio,drag coefficient,and frontal area were selected as optimization variables,with 0-100 km/h acceleration time and fuel consumption per 100 km as objective functions.After multi-island genetic algorithm(MIGA)iterations,optimized parameters showed 4.25%reduction in top speed,2.05%decrease in acceleration time,3.31%increase in maximum gradeability,and 6.09%reduction in combined fuel consumption,meeting vehicle dynamic requirements while improving overall economy.
作者
宋百玲
钱轶凡
胡思远
刘伟
SONG Bailing;QIAN Yifan;HU Siyuan;LIU Wei(College of Mechanical and Electrical Engineering,Northeast Forestry University,Harbin,Heilongjiang,150000,China)
出处
《小型内燃机与车辆技术》
2025年第5期1-10,共10页
Small Internal Combustion Engine and Vehicle Technique
基金
航空附件传动系统关键技术研究与示范应用,黑龙江省科学技术厅、黑龙江省“百千万工程”科技重大专项(2021ZX04A01)。
关键词
增程式汽车
功率跟随控制策略
多目标优化
多岛遗传算法
Extended-range electric vehicle
Power-following control strategy
Multi-objective optimization
Multi-island genetic algorithm
