Performance Analysis of PI and DMRAC Algorithm in Buck–Boost Converter for Voltage Tracking in Electric Vehicle Using Simulation

This study introduces a Direct Model Reference Adaptive Control (DMRAC) algorithm in a buck–boost converter in the power distribution of an electric vehicle. In this study, DMRAC was used in order to overcome the system nonlinearity due to load demand variation, in case of different driving modes (such as acceleration, stable and regenerative braking system mode), and the presence of disturbances in the system. DMRAC receives popularity because of its robustness in the presence of nonlinearity and ensuring system stability. To evaluate the efficacy of DMRAC in the current system, its performance was compared with a PI controller in the MATLAB/Simulink environment. The simulation results show the superiority of DMRAC over a conventional PI control approach, in both variable load demand and disturbed system cases that were measured by tracking error. The improvement was seen in the DMRAC response, with smaller tracking error and faster transient and disturbance rejection. The main contribution of this work is in introducing DMRAC, particularly in a buck–boost converter, and its efficacy with a DC–DC converter for an electric vehicle, which has not been studied before