Abstract

This paper focuses on the high-performance bidirectional DC-DC converter required in distributed electric propulsion (DEP) systems, with the dual active bridge (DAB) converter chosen as the subject of study. To achieve the goal of stabilizing the output voltage while improving the converter’s anti-interference ability and dynamic performance, this paper proposes a novel strategy. In particular, it combines the Linear Extended State Observer (LESO) with a sliding mode control (SMC), proposing a sliding mode control strategy based on the Linear Extended State Observer (LESO-SMC). Notably, this control strategy not only retains the fast dynamic performance of Linear Active Disturbance Rejection Control (LADRC) and the robustness of SMC but also addresses the significant chattering issue inherent in traditional SMC. Comparing the traditional PI, LADRC, and SMC strategies, the results show that when the load changes, the voltage fluctuation of the LESO-SMC strategy proposed in this paper is 0.165 V (0.25 V) in the Matlab/Simulink and RT-Lab platforms, and the average adjustment time is 4 ms (3.5 ms). In contrast, the average voltage fluctuations of PI and LADRC strategies were 3.7 V (4.9 V) and 0.55 V (1.35 V), and the average adjustment times were 99.5 ms (201 ms) and 71.5 ms (77.5 ms), respectively. When the input voltage changes, the proposed LESO-SMC strategy adjusts faster and has almost no voltage fluctuations, while the average voltage fluctuations of the PI and LADRC strategies in the simulation are 0.5 V and 0.1 V, and the average adjustment times are 89.5 ms and 35 ms, and the change in the input voltage in the RT-Lab platform has very little effect on the output voltage. Compared with SMC, the LESO-SMC strategy has no chattering problem. In summary, compared to the other three control strategies, the LESO-SMC strategy proposed in this paper exhibits superior performance in terms of voltage fluctuation and adjustment time during load changes and input voltage changes. It shows a robust anti-interference ability and a rapid dynamic response performance.

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