| 引用本文: | 刘伟,史文库,方德广,郭福祥,桂龙明.汽车动力学分析及悬架子系统优化设计[J].哈尔滨工业大学学报,2012,44(3):96.DOI:10.11918/j.issn.0367-6234.2012.03.019 |
| LIU Wei,SHI Wen-ku,FANG De-guang,GUO Fu-xiang,GUI Long-ming.Vehicle dynamics analysis and optimization of suspension design[J].Journal of Harbin Institute of Technology,2012,44(3):96.DOI:10.11918/j.issn.0367-6234.2012.03.019 |
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| 汽车动力学分析及悬架子系统优化设计 |
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刘伟1, 史文库1, 方德广2, 郭福祥2, 桂龙明2
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(1.吉林大学 汽车仿真与控制国家重点实验室, 130022 长春, jlulw@yahoo.com.cn; 2. 南京依维柯汽车有限公司 产品工程部,210028南京);1.吉林大学 汽车仿真与控制国家重点实验室, 130022 长春, jlulw@yahoo.com.cn;2.南京依维柯汽车有限公司 产品工程部,210028南京
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| 摘要: |
| 为提高汽车的行驶平顺性及操纵稳定性,在进行整车动力学分析的基础上建立汽车悬架系统多目标优化模型,并提出一种基于改进遗传算法的悬架参数多目标优化方法．该方法改进了传统遗传算法中的种群个体选择机制,锦标赛选择过程由外部非支配集和原种群同时参与,可使多次迭代所得父代种群与子代种群中的最优个体均有机会被选取,保证了新种群的多样性．以某轻型客车为研究对象,选取车身侧倾角、横摆角速度及振动加速度作为优化指标,对悬架系统的弹簧刚度、减振器阻尼系数及稳定杆扭转刚度进行多目标优化．实车实验结果表明:与悬架优化前相比,汽车行驶过程中的车身侧倾角、横摆角速度及质心振动加速度分别下降了12.3％、6.4％和9.8％．所提出的基于改进遗传算法多目标优化策略可合理匹配悬架系统各参数,改善汽车的行驶平顺性及操纵稳定性． |
| 关键词: 悬架系统 遗传算法 行驶平顺性 操纵稳定性 |
| DOI：10.11918/j.issn.0367-6234.2012.03.019 |
| 分类号:TG453 |
| 基金项目:国家高技术研究发展计划资助项目(2006AA110104). |
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| Vehicle dynamics analysis and optimization of suspension design |
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LIU Wei,SHI Wen-ku,FANG De-guang,GUO Fu-xiang,GUI Long-ming
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| Abstract: |
| To improve vehicle ride comfort and handling stability, a multi-objective optimization strategy based on improved genetic algorithm was designed for the suspension system. As the study of a light passenger bus, taken the vehicle body side angle, yaw rate and the amplitude of vibration acceleration as optimization index, a multi-objective optimization model of suspension system parameters was established. The method improved the selection mechanism in the individual populations, and the improvements would enable the parent population and offspring population of optimal individuals to have the same opportunity to be selected to ensure diversity of new species. The real vehicle experimental results showed that: compared with the suspension before optimization, the vehicle body side angle, yaw rate and the amplitude of vibration acceleration had been reduced by 12.3%, 6.4% and 9.8%. The new strategy could reasonably match the parameters of suspension system, and simultaneously improve the vehicle ride comfort and handling stability. |
| Key words: suspension system genetic algorithm ride comfort handing stability |
