基于神经网络的供油提前角脉谱研究

Study on Injection Timing MAP Based on Neural Network

根据供油提前角控制精度的要求,确定了BP神经网络结构,选取不同实验数据为训练样本,获取了供油提前角脉谱;引入随机误差合成方法,以模型的计算总误差为指标,讨论了满足控制精度要求的样本数范围和最少样本数,并进行了由最少样本数获取最佳供油提前角实验,验证了具有最佳供油提前角的柴油机,其性能指标最优.实践表明,该方法能满足供油提前角控制要求,减轻供油提前角实验量.

Based on the demand of precision in injection timing control, BP neural networks structure is established and several groups of experimental data are used as the training sample, an injection timing MAP is concluded. Using the sum calculation error as the measure indexes, the scope of sample number and minimum training-sample number meeting the control demand are discussed by quoting the random error synthetic method. Optimal injection timing test derived from minimum training-sample number is made, and it is proved that the diesel engine performance levels under the optimal injection timing are optimum. Practices prove that this method can meet the precision demand of the control system and release the injection timing experimental quantity.