Multi-time scale model predictive control framework for energy management of hybrid electric vehicles
Multi-time scale model predictive control framework for energy management of hybrid electric vehicles
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DOI：
10.1109/cdc.2014.7039774
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发表时间：
2014-12
期刊：
影响因子：
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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
本文提出了一种多时间尺度模型预测控制框架，并将其应用于混合动力汽车的效率和驾驶性能优化。多层模型预测控制概念同时实现了长预测范围内的静态优化和瞬态系统响应的优化，这导致更好的驾驶性能。建议的控制架构进行评估的标准驾驶循环和并联混合动力电动汽车配置的例子。仿真结果表明，与采用单层模型预测控制策略优化混合动力汽车燃油经济性的情况相比，两层能量管理策略具有更好的性能。虽然这个概念已经在并联混合动力电动汽车的例子中得到了证明，但它也适用于任何其他混合动力配置。
In this paper a multi-time scale model predictive control framework is proposed and applied in the efficiency and drivability optimization of hybrid electric vehicles. A multi-layer model predictive control concept simultaneously enables a static optimization over a long prediction horizon and the optimization of the transient system response which leads to better drivability. The proposed control architecture is evaluated on a standard driving cycle and on the example of a parallel hybrid electric vehicle configuration. The obtained simulation results indicate an improved performance of the two layer energy management strategy compared to the case when a single layer model predictive control scheme is applied to optimize the fuel economy of a hybrid electric vehicle. Although the concept has been proven on the example of parallel hybrid electric vehicle it holds in general for any other hybrid configuration as well.