LAUSR

Abstract The excellent fuel economy of power-split hybrid electric bus has facilitated its extensive promotion for applications. However, a conventional rule-based energy management strategy for this bus involves large numbers of calibration, which considerably increases the application cost. To solve this problem, this study proposes an optimal rule design method that combines fixed thresholds with local working probability. This method effectively extracts control rules to obtain near-optimal result of global optimization and reduce calibration workload. In addition, a charge-sustaining strategy based on a linear quadratic regulator is designed to ensure the robustness of the energy management strategy based on rule design methodology. Finally, a simulation and hardware-in-loop (HIL) test are conducted on the Chinese city bus cycle. In comparison with the compared to rule-based engine optimal control, the proposed local probability-based instantaneous optimal control strategy is closer to the global optimization results, with oil savings of 10.6%. The comparison of the results between HIL and offline simulations show that they are largely coincident. Therefore, the proposed rule design methodology can serve as a theoretical reference for extraction rules in engineering practices.