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作 者:刘海江[1] 邢证 LIU Haijiang;XING Zheng(School of Mechanical Engineering,Tongji University,Shanghai 201804,China)
机构地区:[1]同济大学机械与能源工程学院,上海201804
出 处:《哈尔滨工业大学学报》2021年第7期164-170,共7页Journal of Harbin Institute of Technology
基 金:基金项目类别(U1764259)。
摘 要:针对DCT(dual clutch transmission,双离合自动变速器)车辆换挡品质客观评价,首先建立了DCT车辆换挡动力学模型,从体现车辆换挡品质平顺性和动力性两个评价维度,初步选取10个参数作为换挡品质评价指标;为了解决随着指标数量增长带来的指标之间存在冗余,以及现有换挡品质评价指标权重确定方法缺乏合理性的问题,在初选的评价指标基础之上,利用遗传算法优化的粗糙集知识约简方法对评价指标进行约简,并利用支持向量机分类模型对约简有效性进行验证;接着基于属性重要度的概念对约简后评价指标进行赋权。试验结果表明,该方法可以有效地删除冗余指标,同时对评价指标进行合理赋权,为DCT车辆换挡品质客观评价提供了基础。Aiming at the objective evaluation of shift quality of DCT(dual clutch transmission)vehicles,10 parameters are selected as the evaluation indexes of shifting quality from two evaluation dimensions of smoothness and power performance.In order to solve the problems of redundancy between indicators and the lack of rationality of the existing weighting methods,based on the primary evaluation indicators,the evaluation indicators are reduced by using the rough set knowledge reduction method optimized by genetic algorithm,and the effectiveness of the reduction is verified by using the classification model of support vector machine.Then,based on the concept of attribute importance,the reduced evaluation index is weighted.The test results show that the method can effectively delete redundant indicators,and reasonably weight the evaluation indexes,which provides a basis for objective evaluation of shift quality of DCT vehicles.
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