Identification and Validation of Linear Friction Models Using ANOVA and Stepwise Regression

Abstract

For wet disk clutches, the energy input is strongly influenced by its friction behavior. However, the friction behavior cannot be simulated and therefore is mostly derived from experimental data for specific clutch systems. This paper presents a new approach for the identification and validation of linear friction models using analysis of variance (ANOVA) and stepwise regression. Therefore, we use experimental data of three different friction systems with paper- and carbon-based friction lining. The designed experiments support an efficient parameter-based analysis of the friction behavior. The obtained models can be used as an input for thermal simulations, for example, but can also support a better understanding of the main influencing factors and are applicable to various friction systems. For validation, the obtained models are applied to measured data. A good correspondence between the simulated and measured friction behavior can be shown for speeds in the investigated operating range. The presented procedure can be easily adapted, for different factors and operation modes, as well as other applications.

Influence of Water Contamination, Iron Particles, and Energy Input on the NVH Behavior of Wet Clutches

“…An incremental encoder at the end of the shaft measures the rotational speed. Table 1 represents As shown in [29,30], the measurement accuracy of the KLP-260 is identified with regard to the rules of the Guide to the Expression of Uncertainty in Measurement (GUM) [31]. The determined uncertainty is illustrated in Table 2.…”

“…Measurement accuracy of relevant technical parameters on the KLP-260 component test rig according to Strobl[29] based on Baumgartner[30].…”

Статистичний Аналіз Результатів Дослідження Триботехнічних Характеристик Мастильних Матеріалів При Терті

“…Під час процедури скорочення кількості змінних, вони видаляються індивідуально, оскільки кожен крок скорочення призводить до зміни відхилення моделі, що призводить до нових значень F-крітерію та P-значення. Щоб зберегти цілісність моделі, змінні видаляються лише тоді, коли вони не з'являються у взаємодіях вищого порядку [15,16,17]. В табл.…”

Multi-Faceted Analysis of Airborne Noise Impact in the Port of Split (II)

“…The p-value outlines the probability of obtaining the F-value when the factor is not significant and quantifies the risk of incorrectly rejecting the null hypothesis and categorizing an evident effect when it is. The statistical significance threshold for the p-value is commonly set at 5% [45]. The ANOVA is generally used to test if the means of three or more independent groups of continuous data vary significantly concerning a single factor (one-way ANOVA) or two factors (two-way ANOVA).…”