Shenghan Gao

This paper proposes a cyclic shift (CS) reconfiguration scheme and a two-stage MPPT (TS-MPPT) method to enhance the energy supply of solar-powered unmanned aerial vehicle (SPUAV) photovoltaic (PV) systems under partial shading conditions (PSCs). The proposed CS reconfiguration scheme disperses shadows by moving PV modules longitudinally and deduces the optimal movement distance. This scheme not only improves power delivery during PSCs, but also simplifies the maximum power point tracking (MPPT) method by aligning the global maximum power point (GMPP) with the right power point (RPP). Furthermore, the proposed TS-MPPT method takes the derivative of the P-V curve to position the maximum power point (MPP) on the x-axis, and the MPP is tracked by solving the intersection points of the linear equation. The proposed method significantly reduces the tracking time and eliminates the drift phenomenon. The proposed reconfiguration scheme and control method are simulated and experimentally verified under various PSCs. Results indicate that, compared to the total-cross-tied (TCT) scheme, the CS reconfiguration scheme enhances PV energy output by 25.65%. Compared to the P&O method, the TS-MPPT method reduced the start-up time and tracking time by 60.6% and 39.1%, respectively.

To address the issue of efficiency degradation and output power oscillation of photovoltaic (PV) arrays under partial shading conditions (PSCs), this article proposes a global maximum power point tracking (GMPPT) method based on an online data-driven hyperbolic function model. The proposed method utilizes real-time sampled data to establish a curve-fitting model for PV output estimation. By employing adaptive weighting factor, the online fitting model is dynamically combined with the conventional perturbation and observation (P&O) method. Compared to existing GMPPT algorithms, the proposed method achieves fast tracking speed and effectively narrows the search range, reducing the voltage trajectory during the search process. Therefore, the proposed GMPPT method is capable of adapting to complex PSCs with frequent environmental changes, thereby enhancing the overall performance of PV systems. The effectiveness of the proposed GMPPT method is validated through comparative experiments with existing approaches.

The switched-quasi-Z-source bidirectional dc–dc converter (SQBC) has the characteristics of wide voltage gain and low voltage stress, and is suitable for the power interface between the supercapacitors and the dc bus in the multisource system of electric vehicles. On the basis of the SQBC, an optimal design method for inductance parameters and variable switching frequency control strategy are proposed in this article. While remaining the wide voltage gain and low voltage stress characteristics of the topology, the soft-switching operation within the full voltage gain range is achieved without adding additional auxiliary devices. The variable switching frequency control strategy keeps the converter operating at the critical soft-switching point with the lowest switching losses per switching cycle, further improving the operation efficiency of the converter. Finally, an experimental prototype with a rated power of P = 300 W, input voltage of U _low = 50–150 V and output voltage of U _high = 300 V was built, and its maximum efficiency is 98.28%, which verified the correctness and effectiveness of the proposed method.