An on-line energy management strategy for plug-in hybrid electric vehicles using an Estimation Distribution Algorithm

Plug-in hybrid vehicles (PHEVs) have great potential in reducing energy consumption and pollutant emissions, due to the use of electric batteries as another energy source. One of the critical considerations in PHEV development is the design of its energy management strategy, which determines how energy flows in a hybrid powertrain should be managed in response to a variety of system parameters. In this paper, we propose a generic framework of real-time energy management for PHEVs, where an Estimation Distribution Algorithm (EDA) is used for on-line (i.e., real-time) optimization of the power-split strategy. Different methods for controlling the battery pack's State of Charge (SOC) are proposed and sensitivity analyses are conducted to evaluate their performance. Study results validate the effectiveness of the proposed methods and show promise for further field implementation.