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Simulation output and interpretation 397<br />

Z<br />

Yaw rate<br />

Roll angle<br />

Lateral<br />

acceleration (A y )<br />

Y<br />

PLANE Y–O<br />

X<br />

PLANE X–O<br />

Forward speed (V x )<br />

PLANE Z–O<br />

Fig. 7.1 Typical lateral responses measured in one of several possible vehicle<br />

co-ordinate frames<br />

Modern satellite-based instrumentation has improved on this somewhat.<br />

For each handling manoeuvre, or simulation, it is necessary for vehicle<br />

engineers to decide which responses are to be measured during the testing<br />

process.<br />

All test and analytical activities are directed at understanding and improving<br />

the overall dynamic behaviour of the vehicle. As discussed in Chapter<br />

1, the difficulty with the vehicle dynamics field is not the complexity of the<br />

effects in play but the level of interaction between them. A further difficulty<br />

is the level of change in behaviour required for a vehicle to be usefully<br />

‘improved’. Typically, strong impressions of change are made with<br />

only modest variations of physical measures. When the difficulty of repeatable<br />

testing and the variation of impression with individual testers are both<br />

thrown in, the vehicle dynamics process lacks ‘capability’ – in the sense of<br />

quality control – compared to the task it is set. To explain this further, consider<br />

the following example.<br />

7.2 Case study 8 – Variation in measured data<br />

Several attempts have been made to define single number measures for<br />

vehicle dynamic performance. A popular measure in the USA is limiting<br />

lateral acceleration – frequently referred to as ‘grip’. Table 7.1 shows data<br />

that might be recorded during a steady state test, using a stopwatch to time<br />

a lap of a marked 200 m diameter circle.<br />

If an honest error estimation is made in the recorded data then the results<br />

with the stopwatch are probably accurate to 0.1 second. Thus the raw<br />

data would appear as shown in Figure 7.2, with error bars on the figure as<br />

shown. This is a typical set of data for such a test; prolonging the test further<br />

might well degrade the tyres on the vehicle and lead to a ‘skewed’<br />

result favouring the first test configuration with fresher tyres. It could be<br />

argued that tests should be repeated on fresh tyres for each different configuration<br />

to be examined but while academically sound, this argument<br />

neglects the commercial and temporal pressures placed on vehicle testing,

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