@article {10.3844/jmrsp.2020.236.253,
article_type = {journal},
title = {Development of a Fuzzy Logic Controller for Real-time Energy Optimization of a Hybrid vehicle},
author = {Hasan, Sk. Khairul and Dhingra, Anoop Kumar},
volume = {4},
year = {2020},
month = {Oct},
pages = {236-253},
doi = {10.3844/jmrsp.2020.236.253},
url = {https://thescipub.com/abstract/jmrsp.2020.236.253},
abstract = {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},
journal = {Journal of Mechatronics and Robotics},
publisher = {Science Publications}
}