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Air spring systems gain more and more popularity in the automotive industry and with the ever growing demand for comfort nowadays they are almost inevitable. Some significant advantages over conventional steel springs are appealing for commercial vehicles as well as for the modern passenger vehicles in the luxury class. Current production air spring systems exist in combination with hydraulic shock absorbers (integrated or resolved). An alternative is to use the medium air not only as a spring but also as a damper: a so-called air spring air damper. Air spring air dampers are force elements which could be a great step for the chassis technology due to their functionality (frequency selectivity, load levelling, load independent vibration behaviour, load dependent damping). Some of their design which avoid dynamic seals by the using of rubber bellows contribute to a better ride comfort.

For the investigation of the tribological behavior of lubricated contacts, the choice and the calibration of the adopted asperity contact model is fundamental, in order to properly mimic the mixed lubrication conditions. The Greenwood/Tripp model is extensively adopted by the commercial software commonly employed to simulate lubricated contacts. This model, based on a statistic evaluation of the number of asperities in contact and on the Hertzian contact theory, has the advantage of introducing a simple relationship between oil film thickness and asperity contact pressure, considerably reducing the simulation time. However, in order to calibrate the model, some non-standard roughness parameters are required, that are not available from commercial roughness measuring equipment. Standard values, based on some limited experiences, are typically used, and a limited literature can be found focusing on how to evaluate them, thus reducing the predictivity of the model.

The reduction of fuel consumption as well as the rising demands of customers regarding a vehicle’s driving dynamic and the legislator’s continually rising demands are a current issue in vehicle development. Hybrid vehicles offer a possibility to rise to this challenge. Realistic driving cycles are of utmost importance for the calibration of a hybrid vehicle’s operational strategy. Deriving replacement speed cycles from extensive customer data sets seems to be an approach for solving these problems. The contribution at hand describes the derivation of replacement cycles by using stochastic models, probabilistic (weighted) drawings and a combinatorial optimisation. The novelty value is that the characteristic influences of all drivers are being considered in the generation due to the stochastic modelling.

In order to offer a wide range of driving experiences to their customers, original equipment manufacturers implement different driving programs. The driver is capable of manually switching between these programs which alter drivability parameters in the engine control unit. As a result, acceleration forces and gradients are modified, changing the perceived driving experience. Nowadays, drivability is calibrated iteratively through road testing. Hence, the resulting set of parameters incorporated within the engine control unit is strongly dependent on the individual sentiments and decisions of the test engineers. It is shown, that implementing a set of objective criteria offers a way to reduce the influences of personal preferences and sentiments in the drivability calibration process. In combination with the expertise of the test engineers, the desired vehicle behavior can be formalized into a transient set point sequence to give final shape to the acceleration behavior.

Bearings represent one of the main causes of friction losses in internal combustion engines, and their lubrication performance has a crucial influence on the operating condition of the engine. In particular, the conrod small-end bearing is one of the most critical engine parts from a tribological point of view since limited contact surfaces have to support high inertial and combustion forces. In this contribution an analysis is performed of the tribological behavior of the lubricated contact between the piston pin and the conrod small-end of a high performance motorbike engine. A mass-conserving algorithm is employed to solve the Reynolds equation based on a complementarity formulation of the cavitation problem. The analysis of the asperity contact problem is addressed in detail. A comparison between two different approaches is presented, the former based on the standard Greenwood/Tripp theory and the latter based on a complementarity formulation of the asperity contact problem.

This article presents strategies for evaluating the mean, variance, and failure probability of a response variable given measurements subject to both epistemic and aleatory uncertainties. We focus on a case in which standard sensor calibration techniques cannot be used to eliminate measurement error since the uncertainties affecting the metrology system depend upon the measurement itself (e.g., the sensor bias is not constant and the measurement noise is colored). To this end, we first characterize all possible realizations of the true response that might have led to each of such measurements. This process yields a surrogate of the data for the unobservable true response taking the form of a random variable. Each of these variables, called a Random Datum Model (RDM), is manufactured according to a measurement and to the underlying structure of the uncertainty.