面向人-车-路协同的混合动力公交车能量管理策略研究

A new energy optimization methodology for the hybrid electric vehicle (HEV) bus was proposed to solve the adaption problem resulted in the difference of driver behavior and the variability of real world driving cycle based on the driver-vehicle-road interaction.The relationship between the difference of driver behavior and energy consumption was investigated specifically and it was focused to improve the practical endurance mileage based on the optimization of driver torque demand and the design of battery discharge curve as well as matching the power allocation which changed the engine operating path to the high efficiency area which the key problem is the prediction of driving cycle and the database of typical driver behavior characteristics.This new energy management methodology was strongly practicable and had great potentiality to improve the efficiency of the HEV bus through decreasing the influence to the energy consumption duo to the inappropriate driver behaviors as well as overcoming the mismatching problem between the control variables and the real world driving cycles.The results of this study will provide important scientific significance of enriching and developing HEV bus control theory which also have important reference value to other power-train vehicle.

为了解决司机驾驶特性和实际道路工况差异导致的混合动力公交车（Hybrid Electric Vehicle,HEV）能耗表现恶化的问题，本研究提出了面向人-车-路协同控制的混合动力公交车能量管理思想。该思想通过研究司机驾驶特性对HEV公交车能耗的作用机理，建立典型司机驾驶特性样本库，在司机特性实时辨识和道路工况预测的基础上，优化设计全历程电池能量曲线，匹配整车扭矩分配比，最终引导发动机运行工况点向燃油经济性高的区域趋近，以降低整车运行能耗。这种综合能量管理思想可以降低司机驾驶操作以及道路工况因素对HEV公交车能耗的影响，并改善HEV公交车的燃油经济性，具有很强的实用价值。研究成果将完善和补充HEV公交车控制策略理论，具有重要的科学意义，对于其他动力类型车辆同样有重要参考价值。

混合动力电动技术由于可以显著降低发动机油耗，已成为汽车领域的研究热点。由于混合动力电动汽车存在能量分配和制动能量回收问题，使得其节能效果对道路工况和司机驾驶行为非常敏感。混合动力公交车由于其运行线路和司机相对固定，道路工况具有一定的复现性，有利于开展混合动力汽车能量策略工况适应性的研究。本研究通过工况数据分析、动力台架试验、仿真研究和实车测试等方法，对司机驾驶行为差异对混合动力公交能耗的作用机理以及道路工况预测等问题开展研究。研究发现：司机驾驶行为差异主要体现在进出站方式上，应通过降低平均车速，限制加速度分布的离散程度改善混动公交能耗。基于踏板、加速度及变化率等参数可实现司机驾驶特性的辨识评价。在此基础上，可以实现未来窗口期的司机扭矩预测，对司机行为进行主动管理，改善混合动力公交对司机行为的适应程度。公交运行载荷是构建典型公交工况的重要参数。基于公交的运行工况数据和线路地理特征信息，可以预测公交未来行车工况，并构建典型运行工况，优化混合动力公交能量策略参数，提升其对道路工况的适应性。在基金项目的支持下，培养了2名博士、2名硕士生和1名博士后，目前已经发表SCI刊物论文1篇，在审3篇。EI及其他论文发表8篇，录用3篇，2项发明专利进入审查阶段。