Analytical simulation of influential parameters affecting grooved wet clutches performance underdisengagement condition

Nasiri, Hossein; Delprete, Cristiana; Brusa, Eugenio; Razavykia, Abbas; Esmaeilzadeh, Alireza

doi:10.1177/13506501211047783

Cited by 3 publications

(1 citation statement)

References 22 publications

(35 reference statements)

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“…Analytical models [22,[39][40][41][42][43][44][45][46][47] represent a further option to estimate the drag losses. The analytical models presented in the literature are typically based on the Navier-Stokes equations, often assuming major simplifications.…”

Section: Calculation Methodsmentioning

confidence: 99%

A methodology for data-driven modeling and prediction of the drag losses of wet clutches

Pointner-Gabriel

Voelkel

Pflaum

et al. 2023

Forsch Ingenieurwes

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In wet clutches, load-independent drag losses occur in the disengaged state and under differential speed due to fluid shearing. The drag torque of a wet clutch can be determined accurately and reliably by means of costly and time-consuming measurements. As an alternative, the drag losses can already be precisely calculated in the early development phase using computing-intensive CFD models. In contrast, simple analytical calculation models allow a rough but non-time-consuming estimation. Therefore, the aim of this study was to develop a methodology that can be used to build a data-driven model for the prediction of the drag losses of wet clutches with low computational effort and, at the same time, sufficient accuracy under consideration of a high number of influencing parameters. For building the model, we use supervised machine learning algorithms. The methodology covers all relevant steps, from data generation to the validated prediction model as well as its usage. The methodology comprises six main steps. In Step 1, the data is generated on a suitable test rig. In Step 2, characteristic values of each measurement are evaluated to quantify the drag loss behavior. The characteristic values serve as target values to train the model. In Step 3, the structure and quality of the dataset are analyzed and, subsequently, the model input parameters are defined. In Step 4, the relationships between the investigated influencing parameters (model input) and the characteristic values (model output) are determined. Symbolic regression and Gaussian process regression have both been proven to be suitable for this task. Lastly, the model is used in Step 5 to predict the characteristic values. Based on the predictions, the drag torque can be predicted as a function of differential speed in Step 6, using an approximation function. The model allows a user-oriented prediction of the drag torque even for a high number of parameters with low computational effort and sufficient accuracy at the same time.

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Section: Calculation Methodsmentioning

confidence: 99%

A methodology for data-driven modeling and prediction of the drag losses of wet clutches

Pointner-Gabriel

Voelkel

Pflaum

et al. 2023

Forsch Ingenieurwes

View full text Add to dashboard Cite

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Experimental investigation of drag loss behavior of dip-lubricated wet clutches for building a data-driven prediction model

Pointner-Gabriel,

Menzel,

Voelkel

et al. 2024

Sci Rep

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Fundamental knowledge of wet clutches’ drag loss behavior is essential for designing low-loss clutch systems. In contrast to the widely investigated injection lubrication, more comprehensive knowledge is needed on the drag loss behavior of dip-lubricated wet clutches. In the development phase, data-driven models allow drag loss predictions with low computational effort and, at the same time, sufficient accuracy. Therefore, this study aimed to deepen and expand knowledge of the drag loss behavior of dip-lubricated wet clutches based on experimental investigations. Moreover, the investigations were designed and conducted so that the generated data and findings can be used in further research for building data-driven prediction models. The investigations were conducted on two clutch systems from automotive and industrial applications. The practice-relevant parameters of clearance, oil level, oil viscosity, and plate shape were investigated based on a mixed-level full factorial design. The evaluation shows that a reduction in drag loss can be achieved primarily by increasing the clearance, reducing the oil viscosity, and choosing waved plates. The obtained drag loss behavior can be traced back to the form of oil displacement from the gaps. The displacement process, in turn, is influenced by the operating and geometry parameters. Although the flow in the gaps develops differently for dip and injection lubrication over differential speed, the study shows comparable integral effects of the influencing parameters for both types of lubrication. The generated datasets contain the investigated parameters as features and characteristic drag loss values as targets. The findings can support the selection and configuration of the machine learning algorithm and the validation of the trained models. The described procedure can serve as a template for generating and analyzing datasets for data-driven modeling of wet clutches’ drag losses.

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Study on drag torque characteristics of wet multiplate clutch under high-speed operating condition

Li,

Ma,

Wang

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part D:

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In order to study the characteristics of the drag torque of wet multi-plate clutches at high speed, a mathematic model of the drag torque considering oil-gas two-phase flow was established. Based on the VOF two-phase flow model, the oil-film fluid simulation of the flow field was finished, and the distribution law of the volume fraction of the oil-gas phase changing with the speed was analyzed. The analysis results of the model and simulation show that under high speed condition, the oil and gas two-phase flow occupies most of the area in the flow field gap, and leads to the rebound trend of the high speed drag torque. Finally, the variation of the drag torque under different working conditions is studied through experiments, and the influence of lubricant temperature, flow rate, friction plate speed and clearance of friction pairs on the drag torque is analyzed. The improved drag torque model was compared with the experimental results. When the speed is greater than 2000 r/min, the average relative error of the drag torque is less than 15%, which significantly improves the accuracy of the drag torque prediction model, and lays a theoretical foundation for further research on the structure design and optimization of wet multi-plate clutch.

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Analytical simulation of influential parameters affecting grooved wet clutches performance underdisengagement condition

Cited by 3 publications

References 22 publications

A methodology for data-driven modeling and prediction of the drag losses of wet clutches

A methodology for data-driven modeling and prediction of the drag losses of wet clutches

Experimental investigation of drag loss behavior of dip-lubricated wet clutches for building a data-driven prediction model

Study on drag torque characteristics of wet multiplate clutch under high-speed operating condition

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