2008 - Sweden - Road Surface Effects on Rolling Resistance

The main objective of the ECPRD-project is to develop models and methods to minimize the sum of energy use for road construction, for road maintenance and for the traffic. In order to estimate energy use for road traffic the influence of road surface conditions on driving resistance and energy use is of main importance. This part of driving resistance effects have been categorized as rolling resistance.

The literature presents effects of road surface condition on rolling resistance in a wide range of values. The background to this wide range could be:

• different methods: fuel consumption; coast down; laboratory methods etc.
• a measuring problem in general isolating small additional forces
• use of different measures for characterizing a specific road condition
• a lack of control of other variables than for the road surface
• high correlations in the group of road surface variables
• high correlations between road surface and other variables depending on study design

When adding a new study of road surface rolling resistance effects to the long list of other studies it should be of big importance to prove that the accuracy is high. It is difficult to judge the level of accuracy in different studies. A possible criterion in such comparisons could be: which variables are under control. Another criterion could be if these variables are included or not into the analysis. If they have not been included, effects will still be there but may appear disguised in other variables like road roughness and macrotexture.
In this study the coastdown method is used to estimate driving resistance.

The reason for selecting this method is:
• the acceleration level gives a true measure of the driving resistance under real conditions
• the costs for equipment is comparatively low
• to avoid uncertainties caused by the engine and used fuel if compared to fuel consumption measurements
• there is a good potential for recording of all explanatory variables of importance.
Used explanatory variables in analyses:
• speed and acceleration
• gradient
• curvature
• crossfall
• roughness
• macrotexture
• ruts
• ambient temperature
• wind speed
• air pressure.

In total, 34 road strips have been used for the measurements. These strips have been selected in order to cover the main variation in roughness and macrotexture for Swedish roads with the extra requirement that there should be a low correlation.

Road surface conditions have been recorded with a Road Surface Tester (RST). The RST system reports roughness and macrotexture by several different measures.

In total three test vehicles have been used: a car; a van (RST) and a truck (RDT). The operating weights have approximately been 1700, 3300 and 14500 kg.

The literature points out that even small effects on rolling resistance should be possible to detect. This raises a high demand in registration of conditions with high accuracy or controlled conditions. One very important condition used should be: the same tyre pressure before measurements on each test strip.

Estimated effects per unit change of IRI and MPD for the car are depending on speed level:
• at 15 m/sec:
- IRI: increase in rolling resistance by 2.3%
- MPD: increase in rolling resistance by 5.5 %
• at 25 m/sec:
- IRI: increase in rolling resistance by 6.2 %
- MPD: increase in rolling resistance by 9.3 %

In the function used for regression an ambient temperature correction term is included. The presented effects then represent 25 °C.

The IRI and MPD results for the other two test vehicles are not proved speed dependent. For the RST the road surface effects are not proved different from zero. The RDT results in some cases having a wrong sign are judged being not reliable.
Compared to the literature, IRI effects are in the middle of the survey interval and MPD effects are in the upper part of the survey interval.

The analyses include tests with different road surface measures for roughness and macrotexture. Even if differences are small, IRI and MPD gives the best fit of measured coastdown data to the model function compared to other alternative measures.
The dynamic behaviour of a road vehicle on an uneven road is possible to simulate. The additional driving resistance from road roughness is then estimated based on damping losses in tyres and shock absorbers.

The coastdown measurements were used to validate such a simulation routine:
• the simulated additional resistances were far below those estimated by measurements
• the correlation between simulated and measured values was very good.

Simulations should at least be possible to use after calibration.
In ECRPD there is need for a general model representative for all type of vehicles and all models of tyre per vehicle type. Such a general model has been expressed based on the coastdown results and on literature.

The results of this ECRPD study should represent an important contribution to road surface rolling resistance effects both for methodology and for presented effects. Still there are several shortcomings:
• the quality in describing road conditions
• the importance of different aggregation levels
• the lack of data for other vehicle types than cars
• the lack of data for different tyre models
• the lack of data for different load conditions
• the lack of data for different load levels
• the discrepancy between simulations and measurements etc.

It should be of big importance for the future to reduce the mentioned shortcomings.