Energy Management Optimization for Plug-In Hybrid Electric Vehicle

This study aims to develop a strategy for practical real-time applications in Plug-in Hybrid Electric Vehicles (PHEVs). The study combines a Blending Control Scheme (BCS) with an Equivalent Consumption Minimization Strategy (ECMS) for energy management. During the charge-depleting (CD) mode, a blending control scheme was employed, in which the electric motor served as the primary propulsion source while the engine was selectively engaged to share the load. Within this framework, ECMS was applied to determine the optimal power split between the engine and the electric motor in real time. The ECMS considers both the energy consumed by the electric motor and engine to achieve optimal energy consumption, converting the motor and generator consumed electrical energy into an equivalent fuel consumption and combining it with the internal combustion engine’s fuel consumption to determine the equivalent fuel consumption for each time step, then minimizes this equivalent fuel consumption. A backward, instead of forward, PHEV model was built in MATLAB/Simulink based on the THS. The results of combining BCS and ECMS were compared with those of the Rule-Based Control Strategy, which served as the baseline for comparison. The Toyota Hybrid System (THS) was used. The standard FTP-75 driving cycles, including urban and highway scenarios, were simulated. Results show that the Rule-Based strategy has an equivalent combined fuel economy of 50.7 miles per gallon (MPG-e). The proposed method, combining BCS and ECMS, achieves 56.33 MPG-e, representing an approximately 11.1% improvement over the Rule-Based strategy. BCS and ECMS allowed the engine to engage effectively at the adequate time in its high-efficiency region, as well as the motor throughout the drive cycle, and enabled more refined coordination of engine and electric power sources, and can provide high-efficiency computation to realize real-time optimization-based control.