| DEVELOPMENT OF ALGORITHMS FOR COMMERCIAL VEHICLE MASS AND ROAD GRADE ESTIMATION |
| Seungki Kim1, Kyungsik Shin1, Changhee Yoo3, Kunsoo Huh1 |
1Hanyang University
3Sangsin Brake |
|
|
|
|
|
| ABSTRACT |
|
Estimation algorithms for road slope angle and vehicle mass are presented for commercial vehicles. It is well known that vehicle weight and road grade significantly affect the longitudinal motion of a commercial vehicle. However, it is very difficult to measure the weight and road slope angle in real time because of lack of sensor technology. In addition, the total weight of a commercial vehicles varies depending on the freight. In this study, the road grade and vehicle mass estimation algorithms are proposed using the RLS (Recursive Least Square) method and only the in-vehicle sensors. The proposed algorithms are verified in experiments using a commercial vehicle under various conditions. |
| Key Words:
Road grade, Vehicle mass, Kalman filter, Recursive least square, Forgetting factor |
|
|
|
Preview
Full text via DOI
Download Citation 
Print 
