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作 者:欧阳[1] 周舟[1] 唐国强[1] 孙瀚文[1] 张雪钊[1]
机构地区:[1]中国汽车工程研究院动力总成技术研究中心,重庆401122
出 处:《中国公路学报》2016年第9期152-158,共7页China Journal of Highway and Transport
基 金:"十二五"国家科技支撑计划项目(2015BAG17B00)
摘 要:为了在不牺牲油耗和行驶里程的条件下优化插电式混合动力汽车的能量分配过程,提升插电式混合动力汽车的节能潜力以及续航能力,提高插电式混合动力汽车能量管理策略的鲁棒性,以等效燃油消耗最小策略为基础,结合车辆对行驶路况变化的适应性研究,制定了相应的能量管理策略。以标准工况数据为基础开发车辆行驶路况识别器,在标准工况中选取相关的特征值参数,建立特征值参数矩阵。利用标准工况特征值参数矩阵训练BP神经网络识别器,使之能够完成对不同行驶路况的识别。将识别后的路况结果传递给以等效燃油消耗最小策略为基础的能量管理策略,针对不同的行驶路况给出能量流动的优化控制。研究结果表明:在完成对行驶路况的自适应识别之后,插电式混合动力汽车的发动机工作点更加集中在BSFC曲线附近,发动机工作在高效率区间的频率提升;使用自适应路况能量管理策略的插电式混合动力汽车,根据识别后的路况可灵活调整发动机和电池的能量输出,降低油耗并保护了电池的寿命。To optimize the energy management process of plug-in hybrid electric vehicle(PHEV)without sacrificing the fuel economy and driving mileage,increase the potential in saving energy and increasing cruising ability of PHEV,and raise the robust of PHEV's energy management strategies,corresponding energy management strategies were formulated based on the equivalent consumption minimize strategy(ECMS),combining with the self-adaptive researches of vehicle under the changing road condition.A road condition identifier based on standard cycle data was developed.Some related eigenvalues were chosen according to the standard cycle date,forming the eigenvalues matrixes.The BP neural network identifier was trained by using the eigenvalues matrixes,accomplishing the identifying processes for different road conditions.The identified road condition information was passed to the energy management strategy based on ECMS and optimal controls for energy flow under different road conditions were provided.The results show that after finishing the road condition identifying,more engine operating points of PHEV distribute around the BSFC curve,meaning that the engine would operate in high efficiency fieldmore frequently;the PHEV with road condition self-adaptive can adjust the output of engine and battery flexibly based on identified road condition,decreasing fuel consumption and protecting battery life.
关 键 词:汽车工程 插电式混合动力汽车 最优控制 等效燃油消耗最小策略 工况识别
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