Robust Collaborative Optimization Design of Plug-In Hybrid Electric Bus Based on 6 Sigma Theory

This article investigates the collaborative optimization of a plug-in hybrid electric bus (PHEB) under uncertainty. As a public transport vehicle, long-term stable fuel economy is important. However, many previous studies on PHEB started from deterministic frameworks and ignored the uncertainty in operation, leading to high driving cost. In view of the issues, this article considers the uncertainties from operation in practice such as fluctuation in resistance coefficient, passenger load and errors in power source efficiency. A robust simultaneous optimization framework based on 6 Sigma theory is studied in order to obtain the optimal economy under long-term operation. The electric machine, transmission ratio and equivalent factors (EFs) in segmented equivalent consumption minimization strategy (ECMS) are optimized within the same framework. In order to address the issue of efficiency mismatch in motor optimization and energy management control, a motor approximate efficiency model was established using the Kriging model. The robust solution is then compared to the solution from the associated deterministic optimization. The results show that considering uncertainty in practice has a significant impact on the optimization design of PHEB, and the long-term operation cost can be effectively reduced after robust optimization.