摘要
机车柴油机台架实验成本高、调试周期长、不确定因素多,硬件在环仿真实验能够在实验室环境下完成控制系统基本功能和控制策略的验证,成为保证台架实验顺利进行的一种有效手段。结合神经网络模型和物理模型的优点,机车柴油机硬件在环仿真实验的主体部分采用神经网络训练实验数据建立模型,采用物理模型扩展系统的对外接口,对柴油机系统进行稳态工况和过渡工况仿真实验。结果表明,系统能够正确反映实际机车柴油机的运行情况。
In order to solve the problems such as high costs, long debugging periods and a large number of uncertain factors in the bench-test experiments of the locomotive diesel engine, we use the hardware-in-loop simulation to verify the basic function and control strategy of the electronic control unit. The debug process of ECU can be accomplished in the laboratory. Combining the neural network and physical models, we research the dy- namic and static characters on the hardware platform of virtual instruments. The simulation results prove the hardware-in-loop system can reflect real diesel running correctly. This system reduces the uncertain factors in the bench-test.
出处
《铁道学报》
EI
CAS
CSCD
北大核心
2009年第6期21-25,共5页
Journal of the China Railway Society
关键词
机车柴油机
硬件在环仿真
虚拟仪器
神经网络模型
locomotive diesel engine
hardware in-loop simulation
virtual instruments
neural network model