Simultaneous-Level Energy Management Optimization Considering Specific Urban Driving Cycles for PHEBs

Hybrid electric vehicles, as an important means of vehicle development for new energy, have received a lot of research in structure and control in the last decades. However, the coupling between the parameters of structure level and control level is seldom considered leading to only local optimal solutions. To obtain the global driving performance, in this article, a simultaneous-level optimization method is proposed. The study mainly focuses on the optimization design of transmission and energy management control for a plug-in hybrid electric bus (PHEB), with the energy management control utilizing the fuzzy logic control (FLC) strategy. First, the driving data of the local bus routes is collected, processed, clustered, and synthesized into local driving cycles. Then, a hierarchical optimization framework is presented which considers the sizing and control parameters simultaneously. In each layer, the Kriging model and NSGA II algorithm are used to improve optimization efficiency. The results show that the proposed method can reduce emissions and fuel consumption. Compared to the initial value, the optimized fuel consumption decreased by 10.09% and carbon monoxide (CO) emissions decreased.