Digital full-automatic aircraft storage battery life prediction method

The invention discloses a digital full-automatic aircraft storage battery life prediction method which takes a storage battery as an airborne emergency standby power supply of an aircraft as an object, and aims to solve the problems that the storage battery is easy to break down in the flight process and the fault phenomenon is complex, life prediction is performed based on a standard BP neural network, a BP neural network optimized by a genetic algorithm and a support vector regression machine, and prediction results of the three prediction models are fused based on an L-M algorithm, so that life prediction of the aircraft storage battery is realized. 本发明公开了一种数字化全自动的飞机蓄电池寿命预测方法，以作为飞机机载应急备用电源的蓄电池为对象，针对其在飞行过程中易发生故障且故障现象复杂的问题，分别基于标准BP神经网络、遗传算法优化的BP神经网络、支持向量回归机进行寿命预测，并基于L-M算法对以上三种预测模型的预测结果进行融合，从而实现对飞机蓄电池的寿命预测。