PHEV Power Management Optimization Using Trajectory Forecasting and Fuzzy Logic

Author(s): Garcia, Joseph Augusto | Advisor(s): Washington, Gregory | Abstract: In hopes of lessening the reliance on fossil fuels, Plug-in Hybrid Electric Vehicles (PHEVs) have become an attractive option as an alternative fuel vehicle due to their larger electric motors and energy storage systems (ESS). To improve their fuel efficiency, many studies have been done to investigate the use of a priori route information to optimize the use of a PHEV’s ICE and ESS. This study introduces a new control strategy that uses a priori knowledge of a PHEV’s pre-planned route to develop a battery charge usage plan that determines when the vehicle will use its different forms of propulsion. The PHEV can propel itself relying solely on its internal combustion engine (ICE), electric motor (EM), and or a hybrid of both. The strategy uses a route’s speed limits and states of traffic to estimate the consumption of charge and resulting decrease in SOC, and determine the optimal method of propulsion for the PHEV along its route. Fuzzy logic is then used to ensure that battery use during the times of hybrid propulsion is optimized. The control strategy is evaluated and compared to common PHEV control strategies such as Charge Sustaining (CS) and Charge Depletion (CD) using National Renewable Energy Laboratory’s vehicle simulator ADVISOR, with results showing possible increases fuel efficiency starting at about 1%-10% over long traffic heavy routes within this study.