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

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.