Incorporating drivability metrics into optimal energy management strategies for Hybrid Vehicles

Hybrid Vehicle fuel economy performance is highly sensitive to the energy management strategy used to select among multiple energy sources. Optimal solutions are easy to specify if the drive cycle is known a priori. It is very challenging to compute controllers that yield good fuel economy for a class of drive cycles representative of typical driver behavior. Additional challenges come in the form of constraints on powertrain activity, like shifting and starting the engine, which are commonly called ¿drivability¿ metrics. These constraints can adversely affect fuel economy. The benefits of including drivability restrictions in a Shortest Path Dynamic Programming (SPDP) formulation of the energy management problem are investigated for the first time. It is shown that this method yields up to 10% fuel economy improvement on a representative parallel electric hybrid when compared to a simpler instantaneous optimization formulation. This result is obtained by comparing a SPDP controller designed for drivability to a second SPDP controller, designed for fuel economy only, that uses an additional instantaneous optimization step for the incorporation of drivability. The results also quantify the tradeoff between drivability and fuel economy.