说明：  针对LPG电喷发动机过渡工况空燃比难于精确控制的特点，提出了一种将改进Elman神经网络和常规 PI控制算法相结合的空燃比控制方法.其中Elman神经网络用于实现无传输延迟空然比信号的预测，常规PI控制器利用预测信号实现过渡工况下空然比的实时反馈控制.
(LPG EFI engine for transient air fuel ratio is difficult to precisely control the characteristics of the improved Elman proposed a neural network and conventional PI control algorithm combined air-fuel ratio control method. Elman neural network in which transmission delay-free air then forecasts than the signal, the conventional PI controller using the transition conditions predicted signal space than the real-time feedback control then.)