A Novel Supervisory Control and Analysis Approach for Hybrid Electric Vehicles

There are many methods developed over the past decade to solve the problem of energy management control for hybrid electric vehicles. A novel method is introduced in this paper to address the same problem which reduces the problem to a set of physical equations and maps. In simple terms, this method directly calculates the actual cost or savings in fuel energy from the generation or usage of electric energy. It also calculates the local optimum electric power that yields higher electric fuel savings (EFS) or lower electric fuel cost (EFC) in the fuel energy that is spent for driving the vehicle (which in general does not take the system to the lowest engine Brake Specific Fuel Consumption (BSFC)). Based on this approach, a control algorithm is developed which attempts to approach the global optimum over a drive cycle. The main objective of this paper is to introduce the theoretical background and mathematical formulation of EFX (EFS/EFC) metric and explain the development of EFX maps for a specific architecture. Later, these maps are used to develop a control strategy which is implemented to simulate a charge-sustaining WLTP drive-cycle. This novel method is also implemented in real-time in a BorgWarner demo vehicle with P0 mild-hybrid architecture. Fuel economy improvement, SOC sensitivity and test results are discussed.