神经网络在电传动装甲车用发动机控制技术中的应用

Application of Neural Network in the Control of Electrical Drive System of Armored Car Engines

文中利用实测到的装甲车发动机试验数据作为学习样本,采用径向基函数(RBF)神经网络建立了发动机的辨识模型,根据该模型可以得到发动机的最佳燃油消耗率曲线。同时,采用神经网络训练、学习最佳燃油消耗率曲线,并将其存储到发动机控制器中,当发动机按该曲线工作时,可以保证发动机稳态时一直在最佳经济燃油状态下工作。

The identification model of engine of the armored car based on the Radial Basis Function network is set up by using the test data of the engine as learning stylebook. The optimal fuel consumption curves of the engine can be got based on the model. At the same time, neural network is adopted to train and study the optimal fuel consumption curves to be saved in the controller of the engine. When the engine works based on the optimal fuel consumption curves and in stable state, it can always work in the optimal fuel consumption states.