基于重庆道路试验的车辆行驶工况影响因素分析

采用车辆道路试验方法，利用VBOX、尾气采集系统与陀螺仪对车辆行驶状况进行数据采集; 基于投影寻踪动态聚类的方法，结合带有精英控制策略的NSGA-Ⅱ对不同参数指标进行处理; 定量研究了参数指标对车辆燃油经济性和排放特性的影响程度，分析了特定工况下不同参数指标影响特性的变化规律。研究结果表明：在整个行驶工况中，加速度对车辆燃油经济性的影响权重为65.52%，对车辆比功率(VSP)特性的影响权重为35.03%，其中转弯半径对车辆VSP特性的影响权重为37.86%;在车速小于10 km·h^-1时，对车辆燃油经济性影响最大的是转弯半径，影响权重为80.74%，对车辆VSP特性影响最大的是加速度，影响权重为82.82%;车速为10~40 km·h^-1时，对车辆燃油经济性和VSP特性影响最大的是加速度，影响权重分别为34.01%和48.59%;当车速大于40 km·h^-1时，对车辆燃油经济性影响最大的是坡度，影响权重为75.59%，对车辆VSP特性影响最大的是速度，影响权重为80.17%;当车辆处于下坡工况时，坡度对车辆燃油经济性的影响权重为69.84%，车速对车辆VSP特性的影响权重为56.37%;当车辆处于上坡工况时，加速度对车辆燃油经济性和VSP特性的影响权重分别为54.62%和94.24%。定量分析不同因素对车辆燃油经济性和VSP特性影响权重，不仅为提高车辆燃油经济性和改善车辆VSP特性提供实践支撑，同时也为智能车辆控制算法提供了重要理论依据。

Analysis of factors affecting vehicle driving condition based on road test in Chongqing

The vehicle road test method was used, and the vehicle driving status data were collected through the VBOX, an exhaust gas collection system, and a gyroscope. Based on the method of projection pursuit dynamic clustering, combined with the NSGA-Ⅱ method with an elite control strategy, different parameter indexes were processed, and the influence degrees of parameters on automotive fuel economy and emission characteristics were quantitatively analyzed. The change rules of influencing characteristics of different parameters under specific working conditions were studied. Research result shows that in all driving conditions, the weight of the impact of acceleration on the fuel economy is 65.52%, the weight of the impact on the VSP characteristic is 35.03%, and the impact weight of the turning radius on the VSP characteristic is 37.86%. When the vehicle speed is less than 10 km·h-1, the turning radius has the greatest impact on the fuel economy, and its impact weight is 80.74%. The acceleration has the greatest impact on the VSP characteristic, and its impact weight is 82.82%. When the vehicle speed is 10-40 km·h-1, the acceleration has the greatest impact on the fuel economy and VSP characteristic, and its impact weights are 34.01% and 48.59%, respectively. When the vehicle speed is greater than 40 km·h-1, the slope has the greatest impact on the fuel economy, and its impact weight is 75.59%. Vehicle speed has the greatest impact on the VSP characteristic, with an impact weight of 80.17%. When the vehicle is in a downhill condition, the weight of the slope's impact on the fuel economy is 69.84%, and the weight of the speed's impact on the VSP characteristic is 56.37%. When the vehicle is in an uphill condition, the impact weights of acceleration on the fuel economy and VSP characteristic are 54.62% and 94.24%, respectively. A quantitative analysis of the impact weights of different factors on fuel economy and VSP characteristic not only provides practical support for improving them, but also provides an important theoretical basis for intelligent vehicle control algorithms. 11 figs, 31 refs.