|
|||||
|
|
| 基于BP神经网络的车用汽油机过渡工况空燃比多步预测模型 | |
| 引用本文： | 侯志祥,申群太,吴义虎.基于BP神经网络的车用汽油机过渡工况空燃比多步预测模型[J].汽车工程,2006,28(9):809-811,843. |
| 作者姓名： | 侯志祥 申群太 吴义虎 |
| 作者单位： | 1. 中南大学信息科学与工程学院,长沙,410083;长沙理工大学汽车与机械工程学院,长沙,410076 2. 中南大学信息科学与工程学院,长沙,410083 3. 长沙理工大学汽车与机械工程学院,长沙,410076 |
| 基金项目： | 国家自然科学基金项目(50276005)资助 |
| 摘 要： | 为克服车用汽油机空燃比传输延迟对空燃比控制精度的影响,提出了一种基于BP神经网络的空燃比多步预测模型。通过对空燃比数学模型的分析,确定神经网络空燃比多步预测模型的输入向量,同时为提高空燃比预测精度,在神经网络输入向量中增加反映空燃比变化趋势的导数信息。以HL495发动机过渡工况试验数据进行仿真,结果表明该方法能精确预测过渡工况空燃比。 |
| 关 键 词： | 汽油机 过渡工况 空燃比 神经网络 多步预测 |
| 收稿时间： | 2006-01-11 |
| 修稿时间： | 2006-01-112006-04-03 |
Multi-step Predictive Model for Air/Fuel Ratio of Gasoline Engine at Transient Conditions Based on Back Propagation Neural Network |
|
| Hou Zhixiang,Shen Quntai,Wu Yihu.Multi-step Predictive Model for Air/Fuel Ratio of Gasoline Engine at Transient Conditions Based on Back Propagation Neural Network[J].Automotive Engineering,2006,28(9):809-811,843. | |
| Authors: | Hou Zhixiang Shen Quntai Wu Yihu |
| Institution: | 1. School of Information Science and Engineering, Central South University, Changsha 410083; 2. College of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410076 |
| Abstract: | A multi-step predictive model for air/fuel ratio of gasoline engine at transient conditions is presented.By analyzing the model,the input vectors for neural network-based multi-step predictive model are determined.Meanwhile,the input vectors include the derivatives of air/fuel ratio for increasing the prediction accuracy of air/fuel ratio.The results well agree with experiment data at transient conditions of HL495 engine,showing high accuracy of prediction model. |
| Keywords: | Gasoline engine Transient conditions Air fuel ratio Neural networks Multi-step prediction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |