Robust Energy Management Optimization for PHEB Considering Driving Uncertainties by Using Sequential Taguchi Method

Abstract

In this article, a robust optimization design method is presented to improve the energy management effect of plug-in hybrid electric buses (PHEBs). Various uncertain factors are taken into account, including passenger load, resistance, and efficiency. First, the deterministic design of the energy management strategy is conducted under a city bus route, which is divided into 20 segments according to bus stations. The segmented equivalent consumption minimization strategy (ECMS) is established, wherein the equivalent factors (EFs) undergo optimization by the dynamic programming (DP) algorithm. Then, the sequential Taguchi method is utilized to optimize the EFs based on deterministic results. Uncertain factors are designated as noise factors, while EFs serve as control factors. The total fuel consumption is chosen as the optimization objective, with consideration given to the final state of charge (SOC) limit. The simulation results demonstrate that the energy management system obtained by robust optimization achieves a 1.9% reduction in fuel consumption expectation compared to the deterministic optimization. The result proves the validity of the proposed robust optimization method.