An Improved Current Control Charging Scheme Using Neuro-fuzzy and Fopid Based Mppt System for EV Charging
How to Cite?
Ravindra Panchariya, Dr. Poonam Syal, "An Improved Current Control Charging Scheme Using Neuro-fuzzy and Fopid Based Mppt System for EV Charging," International Journal of Engineering Trends and Technology, vol. 69, no. 10, pp. 251-257, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I10P232
In this paper, a novel and enhanced current control method is proposed that is based on the adaptive neuro-fuzzy inference system (ANFIS) and fractional order proportional integral derivative (FOPID) systems. The main contribution of this paper is to reduce the oscillations and increase the efficiency, response time, and lifespan of the battery by providing optimum current to the batteries. For this, an intelligent neuro-fuzzy system is utilized in the model that takes power & voltage error and power& voltage change in error as two inputs to give a single output of reference voltage. Any voltage below or above the reference voltage can damage the battery of the EV. To tackle this issue, MPPT and De-rating operations are performed in the proposed work when the output voltage is below and above the reference voltage, respectively. In addition to this, the FOPID controller produces control signals that improve response time and efficiency of the entire system. The efficacy of the suggested hybrid ANFIS-FOPID approach is analyzed and compared with the state of an art method in the MATLAB software. The simulated outcomes determine that the proposed ANFIS-FOPID model is more efficient and convenient for charging the batteries of EVs.
Electrical vehicles, Battery charging issues, FOPID controller, renewable energy, Intelligent systems, etc.
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