Path dependent receding horizon control policies for Hybrid Electric Vehicles

Georgia-Evangelia Katsargyri, I. Kolmanovsky, J. Michelini, M. Kuang, A. Phillips, M. Rinehart, M. Dahleh
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引用次数: 19

Abstract

Future Hybrid Electric Vehicles (HEVs) may use path-dependent operating policies to improve fuel economy. In our previous work, we developed a dynamic programming (DP) algorithm for prescribing the battery State of Charge (SoC) set-point, which in combination with a novel approach of route decomposition, has been shown to reduce fuel consumption over selected routes. In this paper, we propose and illustrate a receding horizon control (RHC) strategy for the on-board optimization of the fuel consumption. As compared to the DP approach, the computational requirements of the RHC strategy are lower. In addition, the RHC strategy is capable of correcting for differences between characteristics of a predicted route and a route actually traveled. Our numerical results indicate that the fuel economy potential of the RHC solution can approach that of the DP solution.
基于路径的混合动力汽车后退水平控制策略
未来的混合动力电动汽车(hev)可能会采用路径依赖的操作策略来提高燃油经济性。在我们之前的工作中,我们开发了一种动态规划(DP)算法,用于规定电池充电状态(SoC)设定点,该算法与一种新的路线分解方法相结合,已被证明可以减少选定路线上的燃油消耗。在本文中,我们提出并说明了一种用于优化燃油消耗的后退水平控制策略。与DP方法相比,RHC策略的计算需求更低。此外,RHC策略能够纠正预测路线和实际行驶路线特征之间的差异。数值结果表明,RHC方案的燃油经济性潜力接近DP方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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