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.

提出了一种基于历史数据的动力分配混合电动客车（HEB）在线最优控制策略方法。该方法旨在充分利用动力分流式HEB在实际工作循环下的节油能力，并为解决应用推广中的最佳校准问题提供有效途径。首先，构建了一种基于聚类分析和马尔可夫链法的现实驾驶周期综合程序。随后，执行动态编程（DP）控制算法以探索燃油经济性潜力。此外，引入了具有自动化实现基础的基于DP的规则控制策略，以实现在线近似最佳效果。最后，进行了离线仿真和硬件在环测试。