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DEVELOPMENT OF ALGORITHMS FOR COMMERCIAL VEHICLE MASS AND ROAD GRADE ESTIMATION
- Authors
- Kim, Seungki; Shin, Kyungsik; Yoo, Changhee; Huh, Kunsoo
- Issue Date
- Dec-2017
- Publisher
- KOREAN SOC AUTOMOTIVE ENGINEERS-KSAE
- Keywords
- Road grade; Vehicle mass; Kalman filter; Recursive least square; Forgetting factor
- Citation
- INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, v.18, no.6, pp.1077 - 1083
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY
- Volume
- 18
- Number
- 6
- Start Page
- 1077
- End Page
- 1083
- ISSN
- 1229-9138
- 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.
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Related Researcher
- Huh, Kunsoo
- COLLEGE OF ENGINEERING (DEPARTMENT OF AUTOMOTIVE ENGINEERING)