This presentation was held at the 2020 NAFEMS UK Conference "Inspiring Innovation through Engineering Simulation". The conference covered topics ranging from traditional FEA and CFD, to new and emerging areas including artificial intelligence, machine learning and EDA.

Resource Abstract

A necessity for the automotive industry to manufacture more efficient vehicles is a key driver for innovation, with strict emissions legislations set across the globe targeted at reducing the effects of greenhouse gas emissions. Looking at the behavior of consumers in European Union countries as an example, a significant shift in market share for buying passenger cars with lower emissions can be observed over the last decade with new technologies such as hybrid, electric and fuel cell powered vehicles emerging into the market. Recent reports from the European Union show that they believe the hybrid and pure internal combustion engine market share for passenger vehicles in 2050 will still be over 90%.

The reduction of frictional losses within the tribological components in powertrain systems such as bearings, pistons, gears and clutches contribute towards an overall increase in efficiency of a vehicle. This can lead to several key benefits, for example, a reduction in overall fuel consumption, engine power output increases, reduced oil consumption, reduction in harmful emissions from the exhaust, improved lifetime durability for components and systems as well as the whole engine, which in turn can lead to longer service intervals and reduced maintenance costs for consumers. The simulation of computational tribology often plays a key role, where high fidelity models are used to replicate real-world engineering problems and phenomena, allowing multiple new and enhanced design iterations to be made in a short period of time.

This paper presents a system level multi-scale approach to modelling a single piston-cylinder assembly for a 4-stroke C segment passenger vehicle. The principle focus is on the micro-geometry within the piston skirt-liner tribological conjunction. The simulation is performed using AVL EXCITETM.

The investigation considers the use of optically measured topographical data to enhance the accuracy of the simulation algorithm by incorporating experimental data into the model. The model considers the effects of the measured local surface roughness and orientation parameters as well as cavitation. These characteristics are then utilized to calculate flow factors which can be used in the averaged Reynolds equation for simulation of the mixed lubrication regime effects. The system dynamics are also taken into account by the simulation model. A design of experiments for optimization is then carried out for the conjunction with the aim to reduce the friction caused by the asperity interaction when not enough oil film is within the contact. Results show that by optimizing the micro-geometry within the piston skirt-liner conjunction that the effects of asperity friction are reduced; thus, less wear will occur during the lifetime of the components being studied. Using this approach allows engineers to freely explore their ideas, incorporate them into a simulation model and optimize their powertrain solutions before going into prototype production and testing.