基于公交客车智能云监控网络的插电式混合动力系统实时高效运行方法研究

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.

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。

插电式混合动力客车（PHEB）因其出色的燃油经济性，成为缓解当前城市公共交通系统能耗问题的关键技术。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。项目针对并联混合动力系统与运行工况深度耦合导致的整车燃油经济性难以达到其理论最优这一行业瓶颈难题，从挖掘并联混合动力系统节能机理入手，从以下三个方面展开了深入研究：1）针对并联混合动力系统多模式切换运行带来的整车传动效率与平顺性下降的问题，提出了电机起动发动机模式切换过渡模式及其高效平顺控制方法，拓展了并联混合动力系统运行模式，显著地提升了整车的传动效率与平顺性；2）针对现有混合动力汽车能量优化控制方法难以匹配复杂应用工况的难题，建立了工况信息流与机电系统能量流间的高效融合机制，采用模型预测控制等先进控制方法提出了PHEB高效运行控制技术，大幅提升整车燃油经济性的同时保证了特殊工况下的适应性；3）针对复杂城市工况信息难以实时预测的难题，借助智能网联汽车技术，提出了基于云监控后台优化的PHEB实时能量优化控制方法，探索未来智能交通环境下的PHEB队列能耗优化迭代体系，为项目研究成果的实际应用奠定了理论基础。在基金委的大力支持下，项目研究期间发表包括IEEE Transactions on Industrial Electronics、IEEE Transactions on Vehicular Technology、Mechanical Systems and Signal Processing、Applied Energy等顶级期刊论文在内的SCI/EI论文10篇；获授权发明专利1项，另有2项在实质审查中；培养硕士生6人，联合培养硕士生4人，协助合作导师培养博士生1人，博士后1人；基于上述成果，项目负责人杨超于2019获批了国家自然科学基金面上项目；项目关于并联混合动力系统模式切换机制与高效运行控制方法的研究成果，已部分应用在新能源汽车行业重大需求中，研制的混合动力汽车整车控制器，实车节油率达40%的国际领先水平，作为主要完成人参与的项目“商用车机械自动变速式混合动力系统总成关键技术及其产业化应用”获2019年国家科技进步奖二等奖，项目负责人排名第五。