机动车尾气排放测算行驶周期的自动建立方法

Automatic approach to develop driving cycles for estimation of vehicle emissions

为了建立用于机动车尾气排放测算的行驶周期,利用便携车载尾气采集装置(PEMS)系统和GPS装置进行了大量的机动车尾气排放和驾驶活动数据采集,并对数据进行了预处理,提出了短行程的评价标准,给出了最优短行程自动搜索的2种启发式算法(遗传算法(GA)和离散同步扰动随机逼近(DSPSA)),对建立的行驶周期进行了预测尾气排放总量的有效性验证。结果表明:2种启发式算法均能有效地解决行驶周期自动建立问题,GA算法优化得到的行驶周期更有代表性,该行驶周期能以相对较小的误差预测尾气排放总量。建议将GA算法作为开发其他城市的行驶周期的算法工具。

In order to generate a driving cycle for evaluation of vehicles emissions,extensive emission data and driving activity data are collected by using a Portable Emission Measurement System（PEMS）and a GPS device.The collected data are preprocessed and the evaluation criterion for microtrips is proposed.Two heuristic algorithms, Genetic Algorithm（GA）and Discrete Simultaneous Perturbation Stochastic Approximation（DSPSA）are given to search the best microtrips automatically.The prediction of vehicle emissions using generated driving cycle is validated.Research results show that both heuristic algorithms are able to solve the problem of automatic generation of driving cycles.The driving cycle developed by GA is more representable and it can predict the total vehicle emissions with a relatively small error.Therefore,GA is recommended for the generation of driving cycles in other cities.