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|Title:||Modeling of a brushless dc motor driven electric vehicle and its pid-fuzzy control with dSPACE||Authors:||Bahadir, A.
|Keywords:||Brushless DC (BLDC) Motor
Electric Vehicles (EV)
Fuzzy Logic Control
|Issue Date:||2023||Publisher:||Yildiz Technical University||Abstract:||In this study, a high power (75 kW) original driver and control algorithm has been developed for an electric passenger vehicle whose features can be used practically. It has been observed that some problems occur in the operation of the developed control algorithms in traction systems operating at high power. In this study, the solution methods of these problems are included. Firstly, the simulation model of an electrical vehicle was obtained by determining the basic parameters for a passenger electric vehicle. Then a brushless DC motor and drive system was determined for the electric vehicle and an original 75 kW DC-AC Converter (Inverter) in accordance with automotive standards has been designed and tested for the Brushless DC motor. Also, in the design and implementation phase, PID and Fuzzy control-based vehicle control software was developed in MATLAB/Simulink environment on the purpose of rapid prototyping and loaded on the DS1401 dSPACE based control system. It has been seen that through rapid prototyping, the appropriate controller development cycle time for the vehicle drastically reduced, which significantly has reduced the research and development costs. In the vehicle control algorithm, speed information is used as a reference input and brake information is used as feedback. The control signal generated by the controller is converted into PWM pulses for each phase and applied to the IGBT driver. These PWM pulses were used to switch the six IGBT power components used in the three-phase full-bridge DC-AC converter. Driving performance at the design stage has been studied for cases of starting, speed, reversal and load failure. Simulation and experimental results demonstrated the effectiveness of the driver and drive control system that were originally developed. When the system response was examined, it was revealed that the fuzzy logic control algorithm presented much better results than the PI and then the PID control algorithm. Simulation results and application results were consistent with each other and the system performance was successfully tested. Many protection circuits have been designed and configured in the system, with the control algorithms developed according to the problems arising in the operation of high-power systems, hardware add-ons for the operation of the high power (75kW) power-train. Safety Copyright 2021, Yıldız Technical University.||URI:||https://doi.org/10.14744/sigma.2023.00015
|Appears in Collections:||Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections|
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections
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checked on Sep 25, 2023
checked on Sep 25, 2023
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