Hierarchical Control-based Real-time Energy Management Strategy for Hybrid Electric Vehicles

A real-time energy management strategy based on hierarchical control is proposed for the coordinated control of multiple power sources and low fuel economy of hybrid electric vehicles (HEVs). The mathematical models of different power sources are established by analyzing the topology of whole vehicle and the component characteristics of hybrid electric system. The wavelet filter layer is used to divide the full load power into high and low parts, and the high-frequency power is allocated to power-type power sources such as supercapacitors. The low-frequency power is used as the reference input of the model predictive control (MPC) layer. The fuel economy, power battery state of charge (SOC), and DC bus voltage are the optimization items to obtain the optimal control instructions of energy-type power sources such as diesel engine-generator sets and power battery packs. Some representative simulation experiments were performed on dSPACE and RTLAB hardware-in-loop (HIL) simulation platform to verify the effectiveness of the proposed energy management strategy. The results show that, under the condition of CUEDC cycle driving, the fuel economy of the proposed hierarchical energy management strategy is increased by 13.05% compared with the energy management strategy based on fuzzy rules, and the fuel economy is improved by 5.79% compared with the energy management strategy based on a single MPC. Besides, the target power of each energy-type power source under the hierarchical energy management strategy changes more gently, while the power-type power source is involved in the power adjustment process more frequently, which proves the effectiveness of the proposed energy management strategy in improving fuel economy and exerting power source characteristics. © 2021, Editorial Board of Acta Armamentarii. All right reserved.