1. On-Road Fuel Consumption Testing to Determine the Sensitivity Coefficient Relating Changes in Fuel Consumption to Changes in Tire Rolling Resistance
Calvin Bradley & Arnaud Delaval
Presented at the 2011 meeting of the Tire Society

2. Agenda Environmental and regulatory context Rolling resistance basics
Previous results
Derivation of sensitivity coefficient
On-road testing
General procedure
Methods to monitor fuel consumption
Data Analysis
Results
Conclusions

3. Rolling resistance role in production of greenhouse gases
Rolling resistance contribution to over the road transport
Passenger vehicles: 20% of forces opposing motion
Heavy duty trucks: 30% of forces opposing motion
United States transportation
Transportation accounts for 29% of CO2 production
The majority comes from over the road vehicles
Passenger Vehicle: 59%
Heavy Truck: 19%
In the U.S. alone 337 million metric tons (MMT) of CO2 are produced to overcome rolling resistance
1 MMT of CO2 is 200,000 Hot air balloons by volume
1 MMT of CO2 requires almost 800,000 acres of Pine forest to offset
Standard conditions

4. Tire Efficiency Labeling Around the World
Final Label TBD
NHTSA plans an on-line calculator to help consumers valorize low rolling resistance tires on their vehicle

5. Tire Deformations
As a tire is deformed to carry the load three types of deformations are occurring
Bending
Compression
Shearing
Is any of this different for heavy truck tires? Then why wouldn’t the same concepts apply?

6. Definition of Tire’s Rolling Resistance
Tire’s rolling resistance is defined as the energy dissipated by a tire per unit of distance traveled
Ztire
Driving with 10kg/t tires is as if the vehicle was climbing a permanent 1% slope
Tire’s rolling resistance is characterized by a rolling resistance coefficient :
7-12 kg/t
4-8 kg/t

7. Previous results
J. Barrand and J. Bokar established a first order estimate for predicting differences in fuel consumption
The sensitivity coefficient α was further demonstrated to be relatively independent to drive cycle
Empirical prediction
Simulations
Closed circuit stabilized speed testing

8. Rolling Resistance & Resistance to Movement
A vehicle requires energy to move forward and improve the driving comfort
Resistance to Movement characterizes the effort to be overcome
Rolling Resistance is one of the force acting on the vehicle
aerodynamic drag
accessories
inertia
internal friction α
gravity
rolling resistance
Example of accessories : air conditioning, power steering, on-board entertainment…

9. Derivation of Sensitivity Coefficient
Fuel consumption for at a given moment can be described by;
From previous discussion we know
Engine efficiency is a function of required torque
So efficiency η is also a function of CRR
Force Resisting Motion
Fuel Consumption (volume per distance)
Engine Efficiency
Energy Density of Fuel

10. Derivation of Sensitivity Coefficient
Taking the derivative of fuel consumption with respect to CRR and simplifying we obtain
Relating this to previous publications then we see
If the change in efficiency with respect to CRR is very small
However, this approximation proves to be insufficient and the second term for α cannot be neglected

11. Fuel Consumption Testing

12. Test Overview
All tires were machine tested to determine their coefficient of rolling resistance
The impact of these tires on fuel consumption is measured
Real world conditions
Drive cycle with both urban and city portions
Typical E10 gasoline
3 different vehicle segments tested
Compact: Toyota Corolla
Midsize: Chevrolet Impala
Light Truck: Chevrolet Silverado
Wide range of tires evaluated
30 tire sets
10 different brands
Approximate range rolling resistance: 7 to 13 kg/t

13. Test Overview Significant variation can occur during testing
Sources of variation are controlled for consistency as much as possible
Fueling procedures
Vehicle factors such as alignment, AC, windows, lights, weight
Other sources of variation are permutated through all tire sets
Convoy position
Driver
Vehicle
Fuel consumption is measured by multiple independent methods
Test length must be sufficient to provide enough data for significant differences between tire sets
Duration of each test ranged from 12,500 km to 23,500 km
Results come from approximately 587,000 vehicle kilometers of testing

14. Methods to monitor fuel consumption
Fuel pump records
Defines what the consumer actually pays for
Measures volume of fuel at ground temperature
Data cannot be taken as frequently as other methods
Requires a precise fueling procedure
Fuel injector information
Measures fuel by injector pulse frequency and duration
Vehicle on board fuel economy displays
Injector data is calibrated by vehicle manufacturer
Can include error from tire diameter variations
Scan Gauge II OBD tool
Injector data must be calibrated for each vehicle
Independent of tire diameter
Inline volumetric flow meters
Significant cost
Requires cutting of fuel lines for install
Measures volume of fuel at fuel line temperatures

15. Methods Summary Injector Data (Vehicle display & Scan Gauge)
Cost: Low
Complexity: Low or Medium
Precision: High
Accuracy: Low
Fuel Meter (fuel line volumetric meter)
Cost: High
Complexity: High
Accuracy: High
Fuel Pump (Service Station Records)
Complexity: Medium
Precision: Low
Accuracy: Highest

16. Results
ANOVA analysis was used to correct for driver and vehicle effects
All methods were normalized to fuel pump levels
Results demonstrate agreement between methods

17. Results
ANOVA revealed within a test, fuel consumption changes greater than 1.2% were critically different at 95% confidence
Repeats of testing on each vehicle show similar relationship to CRR

18. Results
Testing did not reveal significant differences between sensitivity coefficients for each vehicle
Thus a single value for α was determined sufficient for all tested vehicles
Value of α confirms that is not small enough to be completely neglected
∆FC with lowest RR tire set as reference
Measured FC for all testing

19. Conclusion
Tire rolling resistance has a significant impact on vehicle fuel consumption
Changes in fuel consumption can be predicted by the linear empirical model
The sensitivity coefficient α primarily depends on fuel energy density and effective engine efficiency
The sensitivity coefficient α is not strongly a function of vehicle (outside of vehicle weight) or drive cycle
For typical American usage with E10 gasoline fuel savings can be predicted with:
α = with ∆FC in L/100km, CRR in kg/t, and Mg in metric tons
α = 1.58E-5 with ∆FC in gal/100miles, CRR in kg/t, and Mg in lbs