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Position: Home > Articles > Calibration method for EUP diesel engine based on BP neural network Transactions of the Chinese Society of Agricultural Engineering 2012,28 (15) 21-26

基于BP神经网络的电控单体泵柴油机标定方法

作  者：
冯国胜;贾素梅;周玮
单  位：
北京理工大学机械与车辆工程学院;石家庄铁道大学河北省交通安全与控制实验室
关键词：
柴油机;神经网络;遗传算法;电控单体泵;离线标定
摘  要：
为了寻求电控单元与发动机的最佳匹配,该文开发了基于MPC555的HC4132UPS电控单体泵柴油机台架标定平台,借助台架标定正交试验获取样本数据。使用BP神经网络建立了柴油机稳态性能与控制参数间的数学模型,进行了柴油机功率、油耗和排放与控制参数间的线性回归,其输出响应的复相关系数都在0.94以上,表明该网络具有很好的泛化能力及预测性能。将神经网络建立的数学模型作为性能优化的约束条件和目标函数,采用遗传算法进行了优化。试验结果表明系统能完成标定数据的采集工作,基于神经网络建模和遗传算法优化的标定方法是高效和可行的。
译  名：
Calibration method for EUP diesel engine based on BP neural network
作  者：
Feng Guosheng 1 ,Jia Sumei 1 ,Zhou Wei 2 (1.Hebei Province Laboratory of Traffic Safety and Control,Shijiazhuang Tiedao University,Shijiazhuang 050043,China; 2.School of Mechanical and Vehicular Engineering,Beijing Institute of Technology,Beijing 100081,China)
关键词：
diesel engine,neural network,genetic algorithm,electronic unit pump,offline calibration
摘  要：
In order to seek the better match between ECU(electronic control unit)and engine,the calibration test bench of HC4132UPS was developed based on MPC555.The sampling data was obtained by orthogonal experiment in test bench calibration.Using BP neural network,the mathematical model between control parameters and steady-state performance was built.The linear regression between the control parameters and power,fuel consumption and emissions was processed.The multiple correlation coefficient of output response was large than 0.94.The results showed that the network had good generalization ability and forecast performance.Using the neural network mathematical model as the constraints and objective function of performance optimization,the calibration was optimized by genetic algorithm.The experiment results show that this system can complete the collection of calibration data,and the calibration method based on neural network model and genetic algorithm is efficient and feasible.

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