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Fuzzy Tuned PI Speed Control of BLDC Motor in MATLAB

Fuzzy Tuned PI Speed Control of BLDC Motor in MATLAB


The simulation model comprises a solar PV array, an interleaved buck converter, and grid integration components. The solar PV array, consisting of 16 series-connected panels, generates a peak power of 4000 Watts under standard conditions. The voltage across a single panel is approximately 30.7 volts, which is then stepped down to 400 volts using an interleaved buck converter to maintain the DC bus voltage.

Control Algorithms:

The maximum power point tracking (MPPT) algorithm plays a crucial role in optimizing power extraction from the PV array by continuously adjusting the duty cycle of the interleaved buck converter based on PV voltage and current. Additionally, a voltage control method is employed to regulate the DC bus voltage at 400 volts, ensuring efficient power transfer and system stability.


Grid Integration:

The model incorporates grid integration through a bidirectional converter, enabling seamless interaction between the solar PV system, grid, and electric vehicle (EV) charging station. A sophisticated control logic determines power flow based on the availability of PV power and EV charging requirements. When PV power is sufficient, excess power is used to charge the EV battery, and any surplus power is stored in a stationary battery. Conversely, when PV power is insufficient, power is drawn from the grid to meet the load demand and charge the EV battery.


Dynamic Response Analysis:

Through simulated scenarios and real-time data visualization, stakeholders can observe the dynamic response of the system under varying conditions. The model accurately depicts power flow dynamics, battery charging behavior, and grid interaction, providing valuable insights into system performance and efficiency.


Conclusion:

The integration of solar PV EV charging stations with grid systems represents a significant step towards achieving sustainable energy goals. By harnessing renewable energy sources and leveraging advanced control algorithms, these systems offer a reliable and eco-friendly solution for electric vehicle charging. MATLAB simulation models serve as powerful tools for system analysis, optimization, and validation, paving the way for the widespread adoption of renewable energy technologies.


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