Design and Analysis of Math Function Based Controller Combined with Fuzzy Logic Applied to the Solar-Powered Electric Vehicle
DOI:
https://doi.org/10.21664/2238-8869.2022v11i1.p315-332Keywords:
HESS, solar power, artificial neural network (ANN) controller, math unction based (MFB) controllerAbstract
The transition between the battery and ultracapacitor (UC) according to the driver requirements is the key obstacle that is related to the hybrid energy storage system (HESS) powered electric vehicles (EVs). In this effort, an innovative control scheme has been proposed, to switch the power sources corresponding to the vehicle dynamics. An MFB controller is considered with 4- math functions and programmed independently. Thereafter, a new hybrid controller has been formed by joining the designed MFB controller with an artificial neural network (ANN) to achieve the precise transition between battery and UC. The battery gets charged from the photovoltaic (PV) panel corresponding to the irradiance and temperature availability. The charging and discharging periods of battery mainly depending upon the control switches (CS) present in the circuit. From those two controllers, ANN generates required switching pulses whereas the MFB controller regulates the pulse depending upon the speed of the motor. Finally, the combination of MFB with ANN controller produces the required pulse signals to switches present in unidirectional (UDC) and bidirectional converter (BDC) related to the speed of the motor. The MATLAB/Simulink model of the system is done in four modes with different loads, and all results are discussed in the simulation and results section.
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