Energy management strategy based on velocity prediction for parallel plug-in hybrid electric bus

P. Dong, Sihao Wu, Fusheng Wang, Yinshu Wang, X. Xu, Shuhan Wang, Yanfang Liu, Wei Guo
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Abstract

For plug-in hybrid electric vehicle, an optimal energy management strategy can maximize its potential to achieve high efficiency. However, energy management strategy without condition information cannot achieve optimal fuel economy in real-time. In order to obtain higher efficiency and adapt to unexpected situation, we develop an energy management strategy based on velocity prediction using digital map information. The detailed model of the hybrid powertrain system such as engine, battery pack and vehicle model are established. The typical driving cycles are constructed to minimize the fuel consumption with equivalent consumption minimization strategy. To adapt to sudden congestions, a realtime strategy based on velocity prediction is proposed. Results indicates that equivalent consumption minimization strategy with velocity prediction is more efficient than the traditional equivalent consumption minimization strategy.
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基于速度预测的并联插电式混合动力客车能量管理策略
对于插电式混合动力汽车,优化的能量管理策略可以最大限度地发挥其潜力,实现其高效率。然而,没有工况信息的能源管理策略无法实时实现最优的燃油经济性。为了获得更高的效率和适应突发情况,我们开发了一种基于数字地图信息的速度预测的能量管理策略。建立了混合动力系统的详细模型,包括发动机、电池组和整车模型。采用等效油耗最小化策略,构建典型行驶工况,使燃油消耗最小化。为了适应突发拥堵,提出了一种基于速度预测的实时交通策略。结果表明,结合速度预测的等效能耗最小化策略比传统的等效能耗最小化策略更有效。
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