摘要
针对卡车油耗影响因素多,无法简单进行对比的问题,设计一种基于机器学习的油耗模型。通过前期大量数据的训练和模拟,该模型可以利用车辆行驶参数(如发动机转速、转矩、车速)以及环境因素(如环境温度、环境压力)来计算实时油耗,并得到累计油耗,最终可将偏差控制在3%以内。该方法可为柴油机的油耗分析提供新的思路。
A machine learning based fuel consumption model was designed to address the issue that the truck fuel consumption was affected by multiple factors and can not be easily compared.Through the training and simulation of a large amount of data in the early stage,this model can calculate real-time fuel consumption using vehicle driving parameters(such as engine speed,torque,truck speed)and environmental factors(such as environmental temperature and pressure),and obtain cumulative fuel consumption.Ultimately,the deviation can be controlled within 3%.This method can provide new ideas for fuel consumption analysis of diesel engines.
作者
张绍荣
丁鹏
刘凤阳
李兴章
冯坦
ZHANG Shaorong;DING Peng;LIU Fengyang;LI Xingzhang;FENG Tan(Dong Feng Commercial Vehicle Technology Center,Wuhan 430056,China)
出处
《柴油机》
2024年第1期41-44,共4页
Diesel Engine
关键词
机器学习
柴油机
油耗模型
machine learning
diesel engine
fuel consumption model