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446 Multibody Systems Approach to Vehicle Dynamics<br />

0.8 1<br />

0.6<br />

0.4<br />

0.2<br />

0.2 0<br />

0.4<br />

0.6<br />

0.8<br />

1<br />

0 1 2 3 4 5 6 7 8 9 10<br />

Fig. 8.4 Two-pole Butterworth filter described in equation (8.5) applied to<br />

signal in equation (8.6) (solid) – resulting signal in dashed line<br />

arrived at using some external filter design tool. Particular caution is<br />

needed since some software environments use descending order for the<br />

terms in the transfer function while some use ascending order, as illustrated<br />

in equation (8.5), which represents a 1 Hz second order Butterworth filter<br />

in the Laplace domain as used in Matlab and MSC.ADAMS:<br />

39.884<br />

39.884<br />

gs () <br />

2<br />

<br />

s 8.8869 s <br />

2<br />

39.884 39.884 8.8869<br />

ss<br />

Matlab description MSC.ADAMS Description<br />

(8.5)<br />

More sophisticated filtering is possible using higher order transfer functions<br />

and using the more general state–space modelling methods, which are<br />

available in most multibody system environments. The interested reader is<br />

referred to Blinchikoff and Zverev (2001) for detailed discussion of filtering<br />

methods and their repercussions. The most important thing to recognize<br />

is that almost any form of real-time/run-time filtering introduces some<br />

form of phase delay. Using the example transfer function in equation (8.5),<br />

an input chirp signal in Matlab defined as:<br />

⎛<br />

x sin⎜2<br />

<br />

⎝<br />

2<br />

time ⎞<br />

⎟<br />

10 ⎠<br />

(8.6)<br />

produces an output as shown in Figure 8.4. Note that the amplitude attenuation<br />

is very gentle but that a phase delay has been introduced even at frequencies<br />

well below the notional cut-off frequency.<br />

The 2-pole Butterworth filter represents a linear second order mechanical<br />

system and so its intelligent use can be very helpful in avoiding modelling<br />

complexity. The interested reader is encouraged to study its formulation and<br />

implementation in different forms – pole/zero and Laplace polynomial –<br />

as a launchpad to a deeper understanding of real-time filtering issues and<br />

complexities.<br />

Adaptive damping logic can be implemented in a similar fashion to active<br />

suspension inside an MBS model, scaling a damper spline or adding a scaled<br />

‘damper variation’ spline to a ‘minimum damping’ spline according to a controller<br />

demand. The 1988 Lancia Thema 8.32 is believed by the authors to<br />

be the first production implementation of an adaptive damping system, with

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