Route Preview in Energy Management of Plug-in Hybrid Vehicles
Route Preview in Energy Management of Plug-in Hybrid Vehicles
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DOI：
10.1109/tcst.2011.2115242
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发表时间：
2012-03
影响因子：
4.8
通讯作者：
Chen Zhang;A. Vahidi
中科院分区：
文献类型：
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作者：
Chen Zhang;A. Vahidi
这简要评估使用地形，车速和行程距离的预览，以提高燃油经济性的插电式混合动力汽车。对未来信息的访问被分类为完整的，部分的，或没有未来的信息，并为每种情况下的能源管理策略，提出了一个实时实施的潜力。动态规划（DP）充分了解未来的驾驶条件，提供了一个最佳可实现的基准。部分预览级别可以访问未来的行程地形，并需要速度估计。等效消耗最小化策略（ECMS）被部署为一个瞬时的实时最小化策略，其参数由估计的未来驾驶条件进行调整，并从DP或从ECMS的后向解获得。为了减少对未来速度和详细地形信息的需求，另一个部分预览级别仅假设到下一个充电站的已知行程距离和海拔变化（如果可用）。在该级别中，实时ECMS的参数基于剩余行程距离、电池的充电状态和海拔变化（如果包括的话）来估计。根据没有预览的情况评估结果。大量的仿真案例研究表明，只有部分预瞄，燃油经济性可以大大提高。
This brief evaluates the use of terrain, vehicle speed, and trip distance preview to increase the fuel economy of plug-in hybrid vehicles. Access to future information is classified into full, partial, or no future information and for each case an energy management strategy with the potential for a real-time implementation is proposed. With full knowledge of future driving conditions, dynamic programming (DP) provides a best-achievable benchmark. A partial preview level has access to future trip terrain and requires velocity estimation. Equivalent consumption minimization strategy (ECMS) is deployed as an instantaneous real-time minimization strategy with parameters adjusted by estimated future driving conditions and obtained either from DP or from a backward solution of ECMS. To reduce the requirement for future velocity and detailed terrain information, another partial preview level only assumes known trip distance to the next charging station and elevation changes (if available). In this level, the parameter of the real-time ECMS is estimated based on the remaining trip distance, the battery's state-of-charge, and elevation changes if included. The results are evaluated against cases with no preview. Results from a number of simulation case studies indicate that the fuel economy can be substantially enhanced with only partial preview.