Driving-behavior-aware stochastic model predictive control for plug-in hybrid electric buses
Driving-behavior-aware stochastic model predictive control for plug-in hybrid electric buses
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DOI：
10.1016/j.apenergy.2015.10.152
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发表时间：
2016-01
期刊：
影响因子：
11.2
通讯作者：
Liang Li;Sixiong You;Chao Yang;Bingjie Yan;Jian Song;Zheng Chen
中科院分区：
文献类型：
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作者：
Liang Li;Sixiong You;Chao Yang;Bingjie Yan;Jian Song;Zheng Chen
城市公交车的行驶循环具有一定的重复性，这使得预测性能量管理策略能够获得近似最优的插电式混合动力公交车燃油经济性。但是，如何处理复杂的交通条件，并找到一个近似的全局最优策略，适用于插电式混合动力客车仍然是一个具有挑战性的技术。针对这一问题，提出了一种新的基于驾驶行为感知的改进随机模型预测控制方法。首先，利用K均值对驾驶行为进行分类，得到不同驾驶行为下基于马尔可夫链的驾驶员模型;虽然获得的驾驶员行为被视为随机干扰输入，局部最小燃料消耗可能会获得与传统的随机模型预测控制在每一步，考虑到在有限的预测范围内跟踪参考电池充电状态轨迹。然而，这种技术仍然伴随着一些具有降低/恶化的燃料经济性的工作点。因此，随机模型预测控制修改与等效消耗最小化策略，以消除这些不希望的工作点。在实际城市公交车上的运行结果表明，与目前流行的充电消耗-充电维持策略相比，所提出的能量管理策略能显著提高插电式混合动力公交车在整个行驶循环中的燃油经济性，为实现插电式混合动力汽车近似全局最优的能量管理提供了有益的启示.
Driving cycles of a city bus is statistically characterized by some repetitive features, which makes the predictive energy management strategy very desirable to obtain approximate optimal fuel economy of a plug-in hybrid electric bus. But dealing with the complicated traffic conditions and finding an approximated global optimal strategy which is applicable to the plug-in hybrid electric bus still remains a challenging technique. To solve this problem, a novel driving-behavior-aware modified stochastic model predictive control method is proposed for the plug-in hybrid electric bus. Firstly, theK-means is employed to classify driving behaviors, and the driver models based on Markov chains is obtained under different kinds of driving behaviors. While the obtained driver behaviors are regarded as stochastic disturbance inputs, the local minimum fuel consumption might be obtained with a traditional stochastic model predictive control at each step, taking tracking the reference battery state of charge trajectory into consideration in the finite predictive horizons. However, this technique is still accompanied by some working points with reduced/worsened fuel economy. Thus, the stochastic model predictive control is modified with the equivalent consumption minimization strategy to eliminate these undesirable working points. The results in real-world city bus routines show that the proposed energy management strategy could greatly improve the fuel economy of a plug-in hybrid electric bus in whole driving cycles, compared with the popular charge depleting–charge sustaining strategy and it may offer some useful insights for realizing the approximate global optimal energy management for the plug-in hybrid electric vehicles.