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Analysis in crankshaft design

Crankshafts are at the heart of any race engine (apart from a handful of examples of successful Wankel rotary units). As we strive to obtain more from our race engines – whether it be more performance, faster transient response or improved fuel economy – there is pressure for the existing crankshaft to perform at higher speed, under extra load, or for a new design to be conceived that is lighter and has lower inertia.

There are a number of ways to optimise any engine component. The traditional way is to run ever more highly stressed components in an engine until one breaks. Running engines on dynamometers, no matter how sophisticated, is unlikely to find all the problems – failures will inevitably occur at the track, which is the only real test of a race engine. However, developing components simply by building lots of engines and running them on the track or dyno is extremely costly in terms of time, effort, money and reputation.

Simulation and data analysis is one way in which we can do much of the development of a crankshaft without committing to cutting any metal or building any engines. By examining previous successful and unsuccessful designs we can arrive at some design allowables, and this is a good basis to begin using finite element stress analysis. Ideally we need to compare fatigue safety factors to be sure of a good design, but many people find reasonable success in improving designs by staying within known maximum stress limits.

Simulation of torsional behaviour is very important – we don’t want to build an expensive engine that fails because of a major torsional resonance in the running range, especially if it coincides with an almost constant engine speed as we might find on high-speed circuits. To simulate torsional behaviour we need to model the behaviour of all those parts of the engine that affect on cranktrain torsional vibration, which means not only the crankshaft and adjacent rotating/reciprocating components but possibly also the valvetrain.

The use of CFD in crankshaft analysis is important when looking to optimise the oil system. There are definitely gains to be had from looking at the interaction of the crankshaft with the bearings – for example, a number of clever developments have resulted from the use of CFD in relation to oil feeds.

Equally important is using CFD to model the two-phase behaviour of the oil-air mixture entering the crankshaft. As much as we like to think that we are pumping pure oil through the engine, it is a fact of life that there is likely to be some air in it (you may be surprised how much), no matter how well designed the oil tank may be. For nose-feed crankshafts especially there are a number of ‘tricks’ that can be developed using CFD to decrease the proportion of air in the oil.

We can also simulate the effect of oil ‘depletion’ along the crankshaft. The crankshaft acts like a centrifuge, as the dense oil naturally tends to be flung to the largest radius. As the oil flows along the crankshaft there can be a tendency for the proportion of air to increase as the oil in the galleries is consumed. CFD can give the cranktrain engineer an early warning about how close they are to having a real problem.

Written by Wayne Ward

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