Energy Management of Parallel Hybrid Electric Vehicles based on Stochastic Model Predictive Control
Energy Management of Parallel Hybrid Electric Vehicles based on Stochastic Model Predictive Control
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DOI：
10.3182/20140824-6-za-1003.01329
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Martina Josevski;D. Abel
中科院分区：
文献类型：
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作者：
Martina Josevski;D. Abel
摘要提出了一种基于随机模型预测控制（SMPC）的并联混合动力汽车能量管理控制方法。除了最大限度地减少燃料消耗，控制器还考虑了二氧化碳排放量.考虑到车辆的速度是时变的，混合动力车辆的两个推进机的限制被确定在多个预测时域。随机方法的优点在于，未来驾驶简档不必预先已知，而是基于驾驶员行为的基础随机模型来预测。在NEDC等标准驾驶循环中获得的仿真结果表明，与具有驾驶循环先验知识的MPC控制器相比，SMPC方法的潜力。
Abstract This paper proposes a control approach for the energy management of parallel hybrid electric vehicles based on stochastic model predictive control (SMPC). Apart from minimizing fuel consumption, the controller additionally accounts for CO 2 emissions. Considering the vehicle's velocity to be time-varying, the limits for both propulsion machines of the hybrid vehicle are determined over a multiple prediction horizon. The stochastic approach has the advantage that the future driving profile does not have to be known in advance but is predicted based on an underlying stochastic model of the driver behavior. Simulation results obtained on standard driving cycles such as NEDC demonstrate the potential of the SMPC approach compared to a MPC controller with a-priori knowledge of the driving cycle.