| STATISTICAL ANALYSIS OF THE IMPACT OF VEHICLE RUNNING-IN DISTANCE ON MECHANICAL RESISTANCE |
| Charyung Kim1, 2, Kangjin Kim2, Sungbok Eom1, Kihyeon Ryu1, Kwangbum Lee1, Dojeong Ryu1, Cha-Lee Myung2, Simsoo Park2 |
1Korea Automobile Testing & Research Institute
2Korea University |
|
|
|
|
|
|
|
| ABSTRACT |
|
Certified testing of motor vehicle driving resistance, fuel economy and emissions requires that the vehicle has reached the target distance specified for each country through running-in. In general, motor vehicles experience different tire wear and internal resistance profiles from their moving parts, including the brake, hub bearing, drive shaft and transmission, depending on how they have performed running-in over what range. This means that such differences can result in a discrepancy in the level of mechanical resistance that consists of tire rolling resistance and internal resistance. There is thus a potential impact on the fuel economy and emissions as tested by the chassis dynamometer. In this study, the nomenclatures define where the running-in testing takes place (“Location”), how the testing is performed (“Mode”) and over which distance the testing takes place (“Distance”) as the factors having the major impact on the mechanical resistance of a motor vehicle. Then the mechanical resistance was measured under different running-in distances using a chassis dynamometer and the determination was made on how the resistance decrease over the range to understand statistically how Location and Mode affect the reduction in mechanical resistance under different Distances. This study was also evaluated on which running-in test mode is the best for fuel economy and emissions certification through total cost analysis over the 6,500 km running-in distance. In addition, the process to identify the impact of vehicle running-in test conditions on the reduction in the mechanical resistance of the vehicle was suggested. |
| Key Words:
Running-in distance, Mechanical resistance, Driving mode, Chassis dynamometer, Regression model |
|
|
|
Corresponding Author.
Simsoo Park , Email. 
Preview
Full text via DOI
Download Citation 
Print 
