This brief evaluates the use of terrain, vehicle speed, and trip distance preview to increase the fuel economy of plug-in hybrid vehicles. Access to future information is classified into full, partial, or no future information and for each case an energy management strategy with the potential for a real-time implementation is proposed. With full knowledge of future driving conditions, dynamic programming (DP) provides a best-achievable benchmark. A partial preview level has access to future trip terrain and requires velocity estimation. Equivalent consumption minimization strategy (ECMS) is deployed as an instantaneous real-time minimization strategy with parameters adjusted by estimated future driving conditions and obtained either from DP or from a backward solution of ECMS. To reduce the requirement for future velocity and detailed terrain information, another partial preview level only assumes known trip distance to the next charging station and elevation changes (if available). In this level, the parameter of the real-time ECMS is estimated based on the remaining trip distance, the battery's state-of-charge, and elevation changes if included. The results are evaluated against cases with no preview. Results from a number of simulation case studies indicate that the fuel economy can be substantially enhanced with only partial preview.
Did you like this research project?
To get this research project Guidelines, Training and Code... Click Here