Development of estimation algorithms for vehicle's mass and road grade
- Authors
- Kim, I.; Kim, H.; Bang, J.; HUH, KUN SOO
- Issue Date
- Dec-2013
- Publisher
- KOREAN SOC AUTOMOTIVE ENGINEERS-KSAE
- Keywords
- Mass estimation; Road grade; RLS(Recursive Least Square); Longitudinal/lateral dynamics
- Citation
- INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, v.14, no.6, pp.889 - 895
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY
- Volume
- 14
- Number
- 6
- Start Page
- 889
- End Page
- 895
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/161276
- DOI
- 10.1007/s12239-013-0097-9
- ISSN
- 1229-9138
- Abstract
- In controlling the longitudinal motion of electrified vehicles such as hybrid vehicles and PHEV (Plug-in Hybrid Electric Vehicles), the variation of the driving resistance loads (or driving loads) such as road grade and actual vehicle mass, is the most influential factor which limits the control performance. Measuring the driving load is not impossible, but it is costly since additional sensors have to be mounted on the vehicle. In this study, methods for estimating vehicle mass and road grade are designed to compensate for the driving loads. The proposed methods are verified using simulation tools and then evaluated experimentally.
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