【摘要】 【目的】解决单输入多输出无线电能传输(SIMO-WPT)系统在多负载电压约束下全局效率优化难题。【方法】本文构建了包含线圈损耗、二极管损耗的全链路传输效率模型，分析了发射侧移相与接收侧Buck-Boost的控制机制，提出了一种遗传—内点协同优化算法。该算法结合了遗传算法的全局寻优和内点法的快速收敛，避免了局部最优和初始点敏感问题。【结果】仿真与实物试验结果表明，本文所提遗传—内点协同优化算法相较于传统方案寻优速度更快，且严格收敛于全局效率最优点。【结论】本文所建效率模型覆盖WPT系统关键损耗环节，能适配不同负载数量、电压约束及线圈参数场景，具备较强推广价值。本文所提遗传—内点协同优化算法有效解决了负载电压约束下SIMO-WPT系统的全局高效优化难题，为同类WPT系统的效率设计提供了可行参考。更多还原

【Abstract】 [Objective] The challenge of achieving global efficiency optimization in a single-input multiple-output wireless power transfer(SIMO-WPT) system under multiple load voltage constraints is addressed. [Methods] A full-link transmission efficiency model, including coil and diode losses, was constructed. The control mechanisms of phase-shifting on the transmitter side and Buck-Boost regulation on the receiver side were analyzed. A genetic-interior point collaborative optimization algorithm was proposed. This algorithm combined the global optimization capability of the genetic algorithm with the rapid convergence of the interior point method, thereby avoiding the issues of local optima and initial point sensitivity. [Results] The simulation and experimental results demonstrated that the proposed genetic-interior point collaborative optimization algorithm achieved faster convergence compared to traditional approaches and strictly converged to the global efficiency optimum. [Conclusion] The efficiency model developed in this study covers the key loss components of WPT systems, making it adaptable to scenarios with varying load numbers, voltage constraints, and coil parameters, thus demonstrating strong generalizability. The proposed genetic-interior point collaborative optimization algorithm effectively addresses the challenge of global efficiency optimization in SIMO-WPT systems under load voltage constraints, providing a feasible reference for the efficiency design of similar WPT systems.更多还原