插电式混合动力客车（PHEB）因其出色的燃油经济性和排放性能，成为缓解当前城市公共交通系统能耗和排放问题的关键技术。但在应对复杂运行工况时，其整车节油率离理论最优上限仍有较大差距。主要原因有：并联混合动力系统与运行工况深度耦合，工况随机不确定性致使动力系统难以运行在高效区间；目前普遍采用的规则式调控方法因其分工况标定的控制参数库远未能覆盖复杂多变的公交工况，工况与控制参数的不解耦导致PHEB不具备全工况自适应高效运行的条件。当前城市公交监控网络日渐完善，为交通流特征统计和工况预测提供了数据支持，因此拟借助智能云监控网络开展如下研究：1）建立城市公交工况实时交通流云计算模型；2）揭示工况信息流与机电能量流高效融合机制；3）研究基于信息流-能量流融合的PHEB实时优化控制方法；4）探索借助智能云监控网络的PHEB公交线路全局优化实时控制体系。研究工作将为PHEB高效运行实时控制提供理论支撑。

Because of its excellent fuel economy and emission performance, plug-in hybrid electric bus (PHEB) is the key technology of reducing energy consumption and emission of public transportation system. However, in reality, the fuel saving ratio is still way off the theoretical optimum due to variable and complex driving condition. The main reason is that parallel hybrid powertrain is directly coupled with stochastic driving condition, which makes the hybrid powertrain system hardly working within the efficient range. The most common used control method, rule-based control method, of which control parameters are calibrating with different driving conditions, thus is not able to cover every piece of the complicated and varied public transportation driving conditions. The mismatch between driving condition and control data lead to the result that PHEB cannot work adaptively with high efficiency in every driving condition. The gradually improved public transportation monitoring system is the best data resource of getting traffic flow statistic and supporting driving condition prediction. Therefore, with the help of intelligent cloud monitoring network, the following research will be done in this project, 1) Cloud-based traffic flow calculation and prediction model of public transportation driving condition will be built for PHEB operation; 2) The efficiency integration mechanism between driving condition information flow and electro-mechanical energy flow of hybrid powertrain will be revealed; 3) the real-time optimal control method based on integration between information flow and energy flow will be researched for PHEB; 4) Global optimization real-time control framework based on intelligent cloud monitoring network will be explored for PHEB team in a specific bus route. Result of this research will provide theoretical support for real-time control of PHEB efficient operation.