CAJ | 학술논문

采用自主行驶法采集北京市重型客车行驶数据. 利用自主研发的GPS车辆信息管理系统监控及采集配备行驶记录仪的400多辆试验车辆2个月的行驶数据. 利用小波变换法处理数据并进行短行程划分. 通过主成分分析法和L均值聚类分析法提取运动学片段的主成分进行分类. 结合"最佳增量法"与"组合法"构建速度变化曲线作为代表性行驶工况. 通过对特征参数和速度-加速度联合概率分布进行验证,得出构建的工况能综合反映北京市重型客车的行驶特点;通过与国内外代表性行驶工况进行对比,发现构建的北京市重型客车行驶工况有怠速时间较短,加减速段时间比例适中,匀速行驶时间比例高等特点,与北京市乘用车、公交车行驶工况以及欧洲等发达国家的交通模式相差较大.
채용자주행사법채집북경시중형객차행사수거. 이용자주연발적GPS차량신식관리계통감공급채집배비행사기록의적400다량시험차량2개월적행사수거. 이용소파변환법처리수거병진행단행정화분. 통과주성분분석법화L균치취류분석법제취운동학편단적주성분진행분류. 결합"최가증량법"여"조합법"구건속도변화곡선작위대표성행사공황. 통과대특정삼수화속도-가속도연합개솔분포진행험증,득출구건적공황능종합반영북경시중형객차적행사특점;통과여국내외대표성행사공황진행대비,발현구건적북경시중형객차행사공황유태속시간교단,가감속단시간비례괄중,균속행사시간비례고등특점,여북경시승용차、공교차행사공황이급구주등발체국가적교통모식상차교대.
The autonomous driving method was adopted to acquire the driving data of heavy coaches in Beijing city, and the wavelet transform method used to deal with data under short stroke classification.The self-developed GPS vehicle information management system was used to monitor and collect the driving data of 400 heavy coaches equipped with driving recorders for 2 months.Then the principal components of micro trips were classified through the method of principal component analysis and L clustering technology.The Best Incremental Method and Combined Method were integrated to establish a speed change curve as representative driving cycle.Through the validation of the characteristic parameters and the joint probability distribution of velocity and acceleration, it was shown that the constructed driving cycle could comprehensively reflect the driving characteristics of heavy coaches in Beijing city.By comparison with domestic and international representative driving cycles, it was found that the constructed heavy coach′s driving cycle in Beijing city has the characteristic of having short idle time, moderate acceleration and deceleration time, and long uniform driving time, which was very different from the driving cycle of passenger car and public transport in Beijing city and European countries in traffic pattern.This is an important supplement to the research of driving cycle of heavy coaches.