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State Constrained Optimal Control Applied to Supervisory Control in HEVs

机译:状态约束最优控制在混合动力汽车监控中的应用

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The optimization of the supervisory control of hybrid electric vehicles over predetermined driving cycles has been used as a previous study for determining on-line strategies and also for design and sizing purposes. This problem may be posed as an optimal control problem, in which the energy in the bank of batteries is often the state variable, and the power from any of the system sources is, the control action. As both of these quantities are bounded, the optimal control problem has control constraints or state constraints or both. Usually, the charge-sustaining mode of operation is ensured just by imposing a transversality condition, i.e. a fixed final energy, or including an additional term in the cost functional that penalizes the moving away of the state variable from the nominal value. We considered the problem where the state is allowed to move freely within a band. This led to an optimal control problem with control and state constraints. In this work we describe the difficulties that arise while solving the equations given by the Pontryagin’s Maximum Principle and how these difficulties can be overcome by using the so-called Direct Transcription approach that consists of a programming tool to solve the resultant large-scale finite dimensional optimization problem.
机译:在预先确定的驾驶周期内对混合动力电动汽车的监督控制的优化已被用作先前的研究来确定在线策略以及用于设计和定型。这个问题可能是一个最优控制问题,其中电池组中的能量通常是状态变量,而来自任何系统源的功率就是控制行为。由于这两个量都是有界的,因此最优控制问题具有控制约束或状态约束或两者兼有。通常,仅通过施加横向条件,即固定的最终能量,或在成本函数中包括对状态变量偏离标称值的惩罚是附加的,来确保电荷维持操作模式。我们考虑了允许状态在频带内自由移动的问题。这导致具有控制和状态约束的最优控制问题。在这项工作中,我们描述了解决庞特里亚金最大原理给出的方程式时出现的困难,以及如何使用所谓的直接转录方法克服这些困难,该方法由一个编程工具组成,可以解决所得的大规模有限维优化问题。

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