动力总成驾驶性客观评价的工况优选方法与试验验证

针对动力总成驾驶性评价工况选择缺乏合理性的问题,提出一种基于组合权重和改进TOPSIS法的动力总成驾驶性客观评价工况优选方法。首先,根据动力总成工作原理分析驾驶性客观评价指标并搭建测试与分析软硬件平台。然后,基于组合赋权思想,采用层次分析法(AHP)和变异系数法(CV)确定主客观权重,运用最小相对信息熵原理获得AHP-CV模型的最优权重。接着用加权马氏距离替代欧氏距离的改进逼近理想排序(TOPSIS)搭建车辆驾驶性评价工况优选模型。最后,以静态换挡工况为例进行研究,得出10个细分工况的加权指标值,并对细分工况进行综合排序。试验结果表明,提出的改进AHP-CV-TOPSIS模型对于车辆驾驶性评价的工况选择具有较好的适用性,可揭示各细分工况对驾驶性评价的重要程度,为车辆驾驶性主客观评价工况选取提供科学指导。

Optimum Condition Selection Method and Test Verification for Objective Evaluation of Powertrain Drivability

In view of the poor rationality in selecting the working conditions for powertrain drivability evaluation,an optimum condition selection method is proposed for powertrain drivability evaluation based on combined weight and improved TOPSIS method.Firstly,the objective evaluation indicators of drivability are analyzed according to the working principle of powertrain with the software and hardware for testing and analysis developed.Then,based on the idea of combined weighting and adopting analytic hierarchy process(AHP)and coefficient of variation(CV)methods,the subjective and objective weights are determined,and the principle of minimum relative information entropy is applied to obtaining the optimum weights of AHP-CV model.Furthermore,the improved TOPSIS method with weighted Mahalanobis distance instead of Euclidean distance is used to build the optimum selection model for vehicle drivability evaluation conditions.Finally,the static gear shifting conditions are studied as an example,and the values of weighted indicators of 10 sub-conditions are obtained,with the sub-conditions comprehensively sorted.The test results show that the proposed improved AHP-CV-TOPSIS model has good suitability in condition selection for vehicle drivability evaluation,and can reveal the degree of importance of each sub-condition for drivability evaluation,providing scientific guidance in condition selection for subjective and objective evaluations of vehicle drivability.