航空活塞式发动机空燃比实时控制算法

黎艺华; 胡东宁; 胡春明; 刘娜

航空活塞式发动机空燃比实时控制算法

1. 柳州职业技术学院, 广西柳州 545006;
2. 天津大学天津内燃机研究所, 天津 300072

基金项目:

天津市科技计划（13ZCZDGX04400）；天津市科技计划项目科技支撑重点项目（12ZCZDGX03800）；2013年度广西教育厅科研项目（2013LX2222）

详细信息

作者简介:
黎艺华（1963- ），女，广西阳朔人，副教授，研究方向为电子技术. 通讯作者：

通讯作者:
胡春明 cmhu@tju.edu.cn

中图分类号: V233.7
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出版历程
- 收稿日期: 2014-01-03
- 刊出日期: 2014-05-28

Real time control algorithm of aviation piston engine air-fuel ratio

1. Liuzhou Vocational and Technical College, Liuzhou Guangxi 545006, China;
2. Tianjin Internal Combustion Engine Research Institute, Tianjin University, Tianjin 300072, China

摘要

摘要: 采用比例-积分-微分神经网络（PIDNN）的控制算法，集合了传统PID控制及神经网络各自的优点，控制发动机在不同工况下的空燃比，实现发动机在不同工况间切换时，能够快速地控制空燃比至目标值.在AMESim软件中建立发动机模型，在MATLAB软件中建立PIDNN控制算法，进行模型在环仿真，仿真结果表明：在不同海拔高度下，PIDNN控制算法都能够准确地把空燃比控制在目标值，当发动机在不同工况间切换时，PIDNN能够在0.5s内把发动机空燃比控制至目标值，并且保证过量空气系数超调量在0.2之内，改善了发动机的动力性、经济性，提高了发动机的响应能力.
- PID神经网络 /
- 活塞式发动机 /
- 过渡工况空燃比 /
- 模型在环仿真 /
- 仿真模型
Abstract: Adopting the proportion-integration-differentiation neural network (PIDNN) control algorithm, the advantages of both the tradition PID and neural network were combined. It was used to control the engine air-fuel ratio under different operating conditions, and when the condition changed, it could control the air-fuel ratio to the target value. An engine model was built in software AMESim. The PIDNN control algorithm was built in software MATLAB. Through the model-in-the-loop, the simulation results show that: at different altitudes, the PIDNN could control the air-fuel ratio to the targets accurately. When the engine operating condition changes, the PIDNN could control the air-fuel ratio to the target within 0.5s and ensure the overshoot under 0.2, which results in the improvements of the engine dynamic property, fuel economy and rapid responsibility.
- PID neural network /
- piston engine /
- transient air-fuel ratio /
- model-in-the-loop simulation /
- simulation model

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参考文献(18)

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