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Online Optimal Control Strategy Methodology for Power-Split Hybrid Electric Bus Based on Historical Data

机译:基于历史数据的电力分流混合动力电动总线在线最优控制策略方法

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摘要

An online optimal control strategy methodology on the basis of historical data for a power-split hybrid electric bus (HEB) is proposed in this study. This approach aims to fully utilize the fuel-saving capability of power-split HEB under real operating cycles and provide an effective way for solving the optimal calibration problem in the application promotion. Firstly, a procedure for synthesizing real-world driving cycles based on cluster analysis and Markov chain method is constructed. Subsequently, dynamic programming (DP) control algorithm is performed to explore the fuel economy potential. Moreover, a DP-based rule control strategy with an automated implementation foundation is introduced to achieve online approximate optimal effect. Finally, offline simulation and hardware-in-the-loop test are conducted. Simulation results validate that the proposed online optimal control strategy methodology has similar fuel-saving performance to DP optimal results and good real-time application conditions.
机译:在本研究中提出了基于用于电力分流混合动力电动总线(HEB)的历史数据的在线最佳控制策略方法。这种方法旨在充分利用实际操作周期下的功率分裂HEB的节省能力,并提供一种解决应用促销中最佳校准问题的有效途径。首先,构建了一种基于集群分析和马尔可夫链方法来合成真实驾驶循环的过程。随后,执行动态编程(DP)控制算法以探索燃料经济性潜力。此外,引入了具有自动实施基础的基于DP的规则控制策略,以实现在线近似最佳效果。最后,进行了离线模拟和硬件循环测试。仿真结果验证了所提出的在线最优控制策略方法与DP最佳结果和良好的实时应用条件具有相似的燃料节能性能。

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