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.
Autiero, M., Cirelli, M., Paoli, G., Valentini, P.p. (2023). A Data-Driven Approach to Estimate the Power Loss and Thermal Behaviour of Cylindrical Gearboxes under Transient Operating Conditions. LUBRICANTS, 11(7) [10.3390/lubricants11070303].
A Data-Driven Approach to Estimate the Power Loss and Thermal Behaviour of Cylindrical Gearboxes under Transient Operating Conditions
Matteo Autiero
;Marco Cirelli;Giovanni Paoli;Pier Paolo ValentiniSupervision
2023-01-01
Abstract
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.File | Dimensione | Formato | |
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