摘要
针对润滑油黏度对后桥传动效率影响的问题,采用自适应神经网络模糊推理方法,设计了一种基于ANFIS结构的五维传动效率控制器,采用了模糊减法聚类方法,自适应生成完全具有语言属性的模糊规则;通过训练对ANFIS结构控制器中的各参数进行了优化;经测试该模糊控制器能够很好的预测不同种类油品在不同工况下的传动效率。根据曲面映射图分析,在后桥负载相同的条件下,黏度指数越大的油品对传动效率的贡献越大;在后桥负载较大时,润滑油对传动效率的效用更明显。
For the problem of the impact of the lubricant viscosity on the rear axle transmission efficiency,by using the adaptive neural- network fuzzy inference method,a five- dimensional transmission efficiency controller based on ANFIS structure is designed. By using the subtractive clustering method,a set of fuzzy rules with language property is generated adaptively. Through the training,the various parameters of the ANFIS controller are optimized. After the testing,the results show that the fuzzy controller can well predict the rear axle transmission efficiency of different types of lubricant at the different input speed and the input torque. According to the analysis of the surface map,when the rear axle load on the same condition,the lubricant which has the higher viscosity index has the greater contribution to the transmission efficiency. When the rear axle load is large,the effectiveness of the lubricant to the transmission efficiency is more apparent.
出处
《机械传动》
CSCD
北大核心
2015年第8期185-188,共4页
Journal of Mechanical Transmission
关键词
ANFIS
润滑油
传动效率
参考方案
ANFIS Lubricant Transmission efficiency Reference scheme
