Optimal power management of plug-in HEV with intelligent transportation system
Optimal power management of plug-in HEV with intelligent transportation system
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DOI：
10.1109/aim.2007.4412579
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发表时间：
2007-12
期刊：
影响因子：
--
通讯作者：
Q. Gong;Yaoyu Li;Z. Peng
中科院分区：
文献类型：
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作者：
Q. Gong;Yaoyu Li;Z. Peng
混合动力电动汽车（HEV）已经证明了其改善燃油经济性和排放的能力。插电式混合动力汽车（Plug-in HEV，PHEV）利用更多的电池能量，成为混合动力汽车更有吸引力的升级换代产品。充电耗尽模式更适合于PHEV的功率管理，即当车辆到达行程目的地时，充电状态（SOC）预计会下降到低阈值。在过去，行程信息被认为是用于车辆操作的未来信息，因此先验地不可用。这种情况可以通过目前基于车载地理信息系统（GIS）、全球定位系统（GPS）和先进的交通流建模技术的智能交通系统（ITS）的进步而改变。提出了一种基于历史交通信息的PHEV行驶循环建模方法，实现PHEV在充电耗尽模式下的最优功率管理。应用动态规划（DP）算法来加强电荷耗尽控制，使得SOC在循环的最后时间下降到特定的终端值。该车型基于混合动力SUV。本研究阶段仅考虑燃料消耗。仿真结果表明，与基于规则的功率管理相比，燃油经济性有显着改善。此外，几个驾驶循环的模拟使用所提出的方法相比，基于规则的控制显示出更好的一致性，在燃油经济性。
Hybrid electric vehicles (HEV) have demonstrated their capability of improving the fuel economy and emission. The plug-in HEV (PHEV), utilizing more battery power, has become a more attractive upgrade of HEV. The charge-depletion mode is more appropriate for the power management of PHEV, i.e. the state of charge (SOC) is expected to drop to a low threshold when the vehicle reaches the destination of the trip. In the past, the trip information has been considered as future information for vehicle operation and thus unavailable a priori. This situation can be changed by the current advancement of intelligent transportation systems (ITS) based on the use of on-board geographical information systems (GIS), global positioning systems (GPS) and advanced traffic flow modeling techniques. In this paper, a new approach of optimal power management of PHEV in the charge-depletion mode is proposed with driving cycle modeling based on the historic traffic information. A dynamic programming (DP) algorithm is applied to reinforce the charge-depletion control such that the SOC drops to a specific terminal value at the final time of the cycle. The vehicle model was based on a hybrid SUV. Only fuel consumption is considered for the current stage of study. Simulation results showed significant improvement in fuel economy compared with rule-based power management. Furthermore, simulations on several driving cycles using the proposed method showed much better consistency in fuel economy compared to the rule-based control.