基于神经网络的混凝土泵车发动机万有特性建模与工况优化

Modeling of universal characteristics and optimization of operating conditions of concrete pump truck based on neural network

将底盘传动系纳入发动机动力系统,提出混凝土泵车发动机万有特性模型的现场测试方法。利用BP神经网络建立某型号混凝土泵车发动机的万有特性模型,并以此为依据对该型号混凝土泵车工况进行优化,获得4种工况下与液压系统最佳匹配的发动机转速。试验结果表明:利用BP神经网络建立的某型号混凝土泵车发动机万有特性模型最大相对误差仅为2.31%;建模方法简单、精度高,以该模型为依据优化后的发动机工况节油效果明显,最大可节油11.67%。

Combining the transmission system with engine,a new on-site test method of universal characteristics of power system for concrete pump was put forward.With BP artificial neural network,the model of universal characteristics of a concrete pump truck engine was established,and the optimal matched speed between engine and hydraulic system of a concrete pump truck was acquired in four different working conditions.The experimental results show that the maximum relative error of specific fuel consumption between expected value and measured value is about 2.31%.The neural network is a simple and accurate method for modeling universal characteristics of engine.The maximum percentage of fuel consumption saving is 11.67% under optimal operating conditions.