Development of a Fuzzy Logic Controller for Real-time Energy Optimization of a Hybrid vehicle

The ability to combine positive features of an internal combustion engine with those of an electric motor has been fundamental to the advancement of the high-performance energy-optimized hybrid vehicles. However, due to a lack of reliable and realistic hybrid vehicle models, much of the hybrid vehicle controller research has been limited to computer simulations. To overcome this shortcoming, this paper utilizes a highly reliable vehicle model (Autonomie) for simulation. A state-of-the-art fuzzy logic controller was developed that considers the battery state of charge, wheel torque demand and vehicle speed as the input variables. An ARM Cortex M3 microcontroller-based control hardware prototype was developed and the processor in loop simulation was performed to verify the feasibility of the developed controller in an embedded real-time application. The results of this study indicate that the developed fuzzy logic controller significantly improved the performance (up to 48%) of the hybrid vehicle in a real-time application compared to Autonomie's built-in controller. The processor in loop test results provide evidence of the effectiveness of the developed control algorithm in the embedded real-time form