瞬态(计算机编程)
润滑
热的
功率(物理)
工作温度
稳态(化学)
控制理论(社会学)
动力传输
工程类
人工神经网络
电力系统
机械
计算机科学
机械工程
电气工程
热力学
人工智能
机器学习
操作系统
化学
物理
控制(管理)
物理化学
作者
Matteo Autiero,Marco Cirelli,Giovanni Paoli,Pier Paolo Valentini
出处
期刊:Lubricants
[Multidisciplinary Digital Publishing Institute]
日期:2023-07-20
卷期号:11 (7): 303-303
被引量:6
标识
DOI:10.3390/lubricants11070303
摘要
This paper proposes an innovative methodology to estimate the thermal behaviour of the cylindrical gearbox system, considering, as a thermal source, the power loss calculated under transient operating conditions. The power loss of the system in transient conditions is computed through several approaches: a partial elasto-hydrodynamic lubrication model (EHL) is adopted to estimate the friction coefficients of the gears, while analytical and semiempirical models are used to compute other power loss sources. Furthermore, considering a limited set of operating condition points as a training set, a reduced-order model for the evaluation of the power loss based on a neural network is developed. Using this method, it is possible to simulate thermal behaviour with high accuracy through a thermal network approach in all steady-state and transient operating conditions, reducing computational time. The results obtained by means of the proposed method have been compared and validated with the experimental results available in the literature. This methodology has been tested with the FZG rig test gearbox but can be extended to any transmission layout to predict the overall efficiency and component temperatures with a low computational burden.
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