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作 者:郑清香 寇桂岳[2] 黄强 茶映鹏 ZHENG Qingxiang;KOU Guiyue;HUANG Qiang;CHA Yingpeng(School of Information and Electronic Engineering,Liming Vocational University,Quanzhou 362000,China;School of Mechanical Engineering,Nanchang Institute of Technology,Nanchang 330000,China;School of Mechanical Engineering and Automation,Fuzhou University,Fuzhou 350002,China)
机构地区:[1]黎明职业大学信息与电子工程学院,福建泉州362000 [2]南昌工程学院机械工程学院,江西南昌330000 [3]福州大学机械工程及自动化学院,福建福州350002
出 处:《南昌工程学院学报》2024年第1期71-75,共5页Journal of Nanchang Institute of Technology
基 金:福建省中青年教师教育科研项目(JAT201314);黎明职业大学校级一般课题(LT202117);江西省教育厅科学技术研究项目(GJJ211912,GJJ211911);南昌工程学院校级教改课题(2021JG011)。
摘 要:为了优化上坡工况下的车辆性能,提出了一种考虑坡度工况的混合动力系统多目标优化策略。利用电机对转矩快速准确的响应特性,引入电机转矩优化系数作为控制变量,采用NSGA-Ⅱ算法实现平顺性与经济性的权衡优化。在Matlab/simulink平台上搭建整车模型,并在坡度工况下进行仿真试验,发现在坡度为5%的工况下,优化前的最大冲击度为19.6 m·s^(-3),优化后的最大冲击度为10.6 m·s^(-3),降低了45.91%;优化前的等效燃油消耗为0.5688 L,优化后的等效燃油消耗为0.6087 L,增加了7.01%。上述结果表明优化后的混合动力系统尽管经济性略有降低,但平顺性得到了大幅提高,验证了考虑坡度工况的混合动力系统多目标优化策略的有效性。In order to optimize vehicle performance in slope conditions,a multi-objective optimization strategy for hybrid power system considering slope conditions was proposed in this paper.To solve the torque instability problem caused by engine response lag and demand torque fluctuation in the climbing process,the motor torque optimization coefficient was introduced as the control variable by using the fast and accurate response characteristics of the motor to the torque,and the NSGA-Ⅱ algorithm was adopted to realize the trade-off optimization of ride comfort and economy.The vehicle model was built on the Matlab/simulink platform,and the simulation verification was carried out under the slope condition.The results show that under the working condition of a slope of 5%,the maximum jerk without optimization is 19.6 m·s^(-3),and the maximum jerk after optimization is 10.6 m·s^(-3),which decreases by 45.91%.The equivalent fuel consumption without optimization is 0.5688 L,while the equivalent fuel consumption after optimization is 0.6087 L,which increases by 7.01%.The above results indicate that the stability of the optimized hybrid system has been greatly improved,while the economy has only slightly decreased,thus verifying the effectiveness of the multi-objective optimization strategy for the hybrid system considering slope conditions.
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