Comparison Analysis Between PI and Adaptive Controllers for DC-DC Converter of Hybrid Energy Storage Systems in Electric Vehicles

Abstract

A power converter is one of the important components in a hybrid electric vehicle (HEV), where it has a strong nonlinear dynamic due to the variation of load demand from different driving modes, namely acceleration, braking and cruising. To adapt with the nonlinearities, this work proposes the use of direct model reference adaptive control (DMRAC) to regulate its operation in tracking the load and current demand of the HEV. To validate the response, the control performance is benchmarked with the commonly used traditional PI controller. The system model includes a battery with a supercapacitor, and its controller was constructed using the MATLAB Simulink platform. Simulation results show that DMRAC provides better performance as compared to the PI controller in two cases, which are tracking the current and load demands according to the root mean square error (RMSE) analysis. Nevertheless, in the presence of disturbance, it is noted that DMRAC is only effective in tracking the current demand while requiring some time to adapt and surpass the PI controller in tracking the load demand. Based on these findings, it can be justified that the DMRAC has the potential to become a good alternative approach to control the HEV power converters, specifically in the presence of disturbance.