Fuzzy/Neural Network based approach to enhance the performance of Electric Vehicle by effective utilization of Battery/Supercapacitor

  • B. Prasanth, B. Sanju Srivasthav, Y.S. Srinivas Reddy, K. Deepa

Abstract

The speed control of the Electric Vehicle (EV) based on Brushless direct Current (BLDC) motor has a significant on the performance and efficiency. BLDC motor is a nonlinear, multivariable system which is readily influenced by the variation in the parameters and disturbances. A non-linear controller like fuzzy logic controller is used to constantly control the speed of the EV based on BLDC motor. Further to improve the reliability and response time of the system, an Artificial Neural Network (ANN) based controller is designed. The paper also compares the controllers and concludes ANN based controllers to be the best reliable speed controller for EV. BLDC motor is powered by a battery and supercapacitor. To effectively utilize the complimentary features of battery and supercapacitor, a compound energy storage system (CESS) is been used. Thus, utilization of compound energy storage systems (CESS) outworths in many features like improved vehicle acceleration, efficient regenerative braking and battery safety. The simulation for EV based on BLDC motor for the aforementioned controllers is done in MATLAB/Simulink software.

Published
2020-07-01
How to Cite
B. Prasanth, B. Sanju Srivasthav, Y.S. Srinivas Reddy, K. Deepa. (2020). Fuzzy/Neural Network based approach to enhance the performance of Electric Vehicle by effective utilization of Battery/Supercapacitor. International Journal of Advanced Science and Technology, 29(7), 12422 - 12436. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/27937
Section
Articles