Real time Advisory System for Fuel Economy Improvement in a Hybrid Electric Vehicle

In this paper, we present an improved version of the advisory system for fuel economy improvement in a hybrid electric vehicle [11]. We address the competing requirements for improved fuel economy, while maintaining performance that is close to the current driving style and driver behavior. This is done by introducing a multiple-input, multiple-output rule base with a fuzzy reasoning mechanism that decomposes the space of the main factors that affect vehicle fuel economy and performance - instantaneous fuel consumption, acceleration, speed, and accelerator pedal position. This approach allows us to properly assign the boundaries of the desired accelerator pedal position that correspond to each of the specific areas, which are defined by the rules´ antecedents. The system was developed and validated on the Ford (INSERT YEAR and make like SE) HEV Escape vehicle.