Optimal Control of Efficiency and Dynamic Performance for DAB Converter in Electric Vehicle

ABSTRACT To improve the efficiency of the electric vehicle motor drive system, a dual active bridge (DAB) converter can be added between the power battery and the motor inverter to regulate the DC bus voltage based on the real‐time speed of the motor. However, the DAB converter inherently introduces certain losses. To reduce the overall system losses, the DAB converter is required to operate with high efficiency. Firstly, the principle of triple phase shift (TPS) modulation is analyzed, whose three degrees of freedom can be used to optimize the efficiency of the converter. Secondly, the various losses of the DAB converter are calculated, and a comprehensive loss model for the converter is established. Then the traversal algorithm is used to obtain the phase shift angle combination with the minimum comprehensive loss, thereby improving system efficiency. Meanwhile, an adaptive model predictive control (AMPC) strategy is proposed by combining model predictive control (MPC) and extended state observer (ESO). This strategy can improve the dynamic performance of the system while also addressing the parameter sensitivity issue of MPC. AMPC uses virtual current to describe the difference between the actual circuit and the prediction model and uses an ESO to estimate the virtual current. The model parameters can be updated in real time based on the virtual current, thus improving the dynamic performance and robustness of the system. Finally, a low‐power prototype of the DAB converter has been built to verify the feasibility and superiority of the proposed control strategy.