根据其城市公交车的运营线路、运行类型及线路覆盖区域,选取20条代表性公交线路上对应的20辆公交车,采集一个月的行驶数据,利用短行程分析法结合主成分分析及优化的K均值聚类算法实现各片段的合理分类,从而拟合出反映这一城市公交车运行特点的行驶工况.利用AVL-Cruise整车仿真平台验证该工况合成的有效性和必要性,同时引入Isight优化平台实现针对该城市公交车整车控制策略关键参数的优化标定.结果表明,控制参数优化后整车综合油耗降低8.7%,与RCP测试的仿真结果相对误差仅为2%,验证了优化后的控制策略的有效性.%According to the operation types and operation line,the city bus coverage area,20 rep-resentative bus lines on the 20 bus driving data acquisition for a month were selected,a reasonable classification analysis method combined with the K mean clustering algorithm of principal component analysis and optimization of the implementation of each segment of the short stroke,thus the driving cycle that reflects the running characteristics of the city bus was fitted.The effectiveness and necessity of the Isight simulation platform was verified by the AVL-Cruise simulation platform,and the optimi-zation of the key parameters of the vehicle control strategy for the city bus was introduced.The results show that the overall fuel consumptions of the vehicles are reduced by 8.7% and the relative errors of the simulation results with the RCP tests are only 2%,which verifies the effectiveness of the optimized control strategy.
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