结合试验,详细考察了不同油温下机油冷却器的流量特性,并利用BP神经网络建立了描述机油冷却器流量特性的仿真模型。研究结果表明:随着流量的增加,机油流经机油冷却器所产生的压降也明显增加;在较低油温和高压降情况下,流经机油冷却器的机油流量与其所产生的压降均有很好的线性关系,而在高温、低压降时存在明显的非线性关系;流量—压降关系比流量—温度关系的线性度更好。利用BP神经网络建立的流量特性模型取得了很好的性能仿真效果,最大误差不超过5%。
Based on th test, the flow characteristic of oil cooler under different temperatures was analyzed and its simulation model was built by the BP neural network. The results show that the pressure drop will distinctly increase with the increase of flow. Under low temperature and high pressure drop conditions, there is the linear relationship between pressure drop and flow. Oppositely, there is the nonlinear relationship. Therefore, compared with the flow and temperature, the flow and pressure drop has better linear relationship. Accordingly, the model has better simulation effects, whose maximum error is no more than 5%.