随着航空全电技术的发展，以电作动器为代表的脉冲性、非线性、大功率负载应用日趋广泛，对全电飞机机载电力系统的功率平衡带来了巨大挑战。现有机载电力系统的源-荷分立式控制思路，在电源侧和负载侧间缺乏协同机制，使得电源侧对负载侧的不确定性突发需求缺乏主动的预测和适应能力，从而因功率失衡造成电网失稳与供电品质问题。对此，提出一种全电飞机机载电力系统源-荷协同模型预测控制策略，构建基于三级式发电机、储能电池系统动态模型的模型预测控制优化控制器，及基于机器学习的电作动设备负荷预测模型。在负荷预测基础上，动态调整三级式发电机的励磁电压、储能电池系统中双向DC/DC变换器的占空比等控制指令，赋予机载电力系统对负载侧突发不确定需求的主动预测和适应能力，实现源-荷协同优化控制。构建基于Saber的软件在环嵌入式仿真验证环境，对所提控制策略进行仿真验证。结果表明，所提控制策略可显著抑制突发不确定负载条件下机载电力系统母线电压的波动，减小扰动后母线电压的恢复时间，有效提升母线电压的动态稳定性与响应速度。

With the advancement of all-electric aircraft technologies, impulsive, nonlinear, and high-power loads typified by electro-hydrostatic actuators and electromechanical actuators are being increasingly deployed, posing substantial challenges to power balance in onboard electrical power systems of all-electric aircraft. The prevailing source-load decoupled control paradigm lacks an effective coordination mechanism between the generation side and the load side, leaving the power source unable to proactively predict and accommodate uncertain, abrupt load demands. Consequently, power imbalance may induce grid instability and degrade power quality. To address these issues, a source–load coordinated model predictive control (MPC) strategy for the all-electric aircraft onboard electrical power system is proposed. An MPC-based optimal controller is developed based on dynamic models of a three-stage generator and an energy storage battery system, together with a machine-learning-based load forecasting model for electromechanical actuators. Based on the predicted load demand, control commands including the excitation voltage of the three-stage generator and the duty ratio of the bidirectional DC/DC converter in the battery energy storage system are updated online, there-by endowing the onboard power system with proactive prediction and adaptation capabilities against sudden and uncertain load-side demand variations and enabling coordinated source–load optimal control. A Saber-based software-in-the-loop embedded simulation platform is established to validate the proposed strategy. Simulation results demonstrate that the proposed control strategy significantly suppresses bus voltage fluctuations under abrupt and uncertain load conditions, shortens the post-disturbance bus-voltage recovery time, and effectively improves the dynamic stability and response speed of the DC bus voltage.