具有执行延迟和决策滞后的混合系统的随机动力学原理

K. Aouchiche, J. Bonnans, Giovanni Granato, H. Zidani
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引用次数: 2

摘要

本文提出了一种随机动态规划(SDP)算法,该算法旨在最小化基于增程式电动汽车(REEV)总能耗的经济标准。该算法整合了REEV导航系统的信息,以获得未来预期车速的一些信息。将以高压蓄电池为主要能源,内燃机为辅助能源的汽车能量系统模型写成混合动力系统,并在混合最优控制框架下求解相应的优化问题。混合最优控制问题包括两个重要的ICE物理约束,即激活延迟和决策滞后。研究了包含此类物理约束的三种方法。在介绍了SDP算法的公式后,我们对随机算法和确定性算法的数值结果进行了评论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A stochastic dynamic principle for hybrid systems with execution delay and decision lags
This work presents a stochastic dynamic programming (SDP) algorithm that aims at minimizing an economic criteria based on the total energy consumption of a range extender electric vehicle (REEV). This algorithm integrates information from the REEV's navigation system in order to obtain some information about future expected vehicle speed. The model of the vehicle's energetic system, which consists of a high-voltage (HV) battery, the main energy source, and an internal combustion engine (ICE), working as an auxiliary energy source), is written as a hybrid dynamical system and the associated optimization problem in the hybrid optimal control framework. The hybrid optimal control problem includes two important physical constraints on the ICE, namely, an activation delay and a decision lag. Three methods for the inclusion of such physical constraints are studied. After introducing the SDP algorithm formulation we comment on numerical results of the stochastic algorithm and its deterministic counterpart.
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