围绕eVTOL/eSTOL等分布式电推进飞行器功率负载变化剧烈、复杂输电系统损耗大等带来的动力能源系统难以准确评估的问题，本文提出一种适用于无人机全飞行过程的高精度动力能源系统建模评估方法。论文首先建立基于二阶RC电池模型的能源系统模型，结合电池放电实验数据通过粒子群算法辨识获取模型关键参数，并构建了包括螺旋桨、电机、电调和输电线缆的推进系统模型。接下来，论文首次基于隐函数方程组搭建了适用于全过程高精度模型的无人机动力能源系统工作状态计算框架，并与实验数据进行对比验证。最后，针对某项目的分布式电推进无人机开展动力能源系统仿真评估，并完成了输电线缆布局优化设计。结果显示，能源系统的电压预测误差以及系统状态计算框架误差均小于2%，模型可准确反映全飞行过程各部件工作状态变化，优化后的输电线缆布局电压损失减少了17.2%，平均功率损失减少了16.36%，验证了本文方法的准确性和有效性。

Addressing the challenges posed by drastic power load variations and high losses in complex transmission systems for distributed electric propulsion aircraft such as eVTOL/eSTOL, this paper proposes a high-precision power and en-ergy system modeling and evaluation method applicable to the entire flight process of unmanned aerial vehicles (UAVs). The paper first establishes an energy system model based on a second-order RC battery model, identifying key parameters through a particle swarm algorithm using battery discharge experimental data, and constructs a pro-pulsion system model that includes propellers, motors, electronic speed controllers (ESCs), and transmission cables. Subsequently, this study introduces a working state calculation framework for the UAV power and energy system based on an implicit function equation system, which is validated against experimental data. Finally, a simulation as-sessment of the power and energy system is conducted for a specific project involving a distributed electric pro