Modeling & Design of a ANN Controller for a BLDC Motor on Propulsion Application for Hybrid Electric Vehicle
KVNS Pavan Kumar1, S. Prakash2

1KVNS Pavan Kumar, Research Scholar, Department of EEE, Bharath Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
2Dr. S. Prakash, Professor, Department of EEE, Bharath Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
Manuscript received on 20 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 3994-4000 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B15430982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1543.0982S1119
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Abstract: This paper proposes the brushless direct current (BLDC) motor with high power density and high efficiency characteristics may be used to propulsion framework for electric vehicle. The progressive model for BLDC motor under rotor flux linkage route reference frame might have been providing. Here we analyzed the chart of ann vector and principal of ann control strategies and proposing the ann based reactive power with BLDC motor. To make ann based framework on active power, torque ripple, dc voltage, power factors can be used BLDC motor was designed. After designed simulation results was test the validity of field weakening based on reactive power with BLDC for electric vehicle application. In this research work will introduced artificial neural network (ANN) for non electrical input used. To control the BLDC motor speed it can using pulse width modulated control of the voltage source inverter (VLSI) using DC link voltage (Vdc) controller. To perform electronic commutation by hall signal sensing they are using PWM signal, to generate PWM signal inbuilt encoder can be used in this circuit. Analyze the BLDC motor performance driving propulsion framework is carried out under the MATLAB/Simulink software’s and efficiency of whole frame work is calculated under various source conditions.
Keywords: MATLAB/Simulink, BLDC Motor.
Scope of the Article: Low-power design