Data-Driven 차량 횡방향 모델 정확도 개선open accessData-driven Based Accuracy Improvement for Vehicle Lateral Model
- Other Titles
- Data-driven Based Accuracy Improvement for Vehicle Lateral Model
- Authors
- 조건희; 김좌헌; 이형철; 유승한; 조완기
- Issue Date
- Feb-2022
- Publisher
- Korean Society of Automotive Engineers
- Keywords
- Cornering stiffhess; Model accuracy; Parameter optimization; Vehicle lateral control; Vehicle lateral model; 차량 횡방향 모델, 모델 정확도, 차량 횡방향 제어, 파라미터 최적화 이 키워드로 연구동향 분석 이 키워드로 논문 검색 , 코너링 강성
- Citation
- Transactions of the Korean Society of Automotive Engineers, v.30, no.2, pp.133 - 142
- Indexed
- SCOPUS
KCI
- Journal Title
- Transactions of the Korean Society of Automotive Engineers
- Volume
- 30
- Number
- 2
- Start Page
- 133
- End Page
- 142
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/139586
- DOI
- 10.7467/KSAE.2022.30.2.133
- ISSN
- 1225-6382
- Abstract
- In mis paper, a data-driven based method was proposed to improve the accuracy of the vehicle lateral model, hi the derivation of the conventional single-track model, several error factors occurred as a result of the simplification of the model. Among them, front and rear tire cornering stiffriess was the factor mat was most related to the accuracy of the vehicle lateral model. In general, the conventional model uses nominal cornering stiffness without considering its nonlinearity and the effect of lateral load transfer. The proposed method was developed to compensate sufficiently for the error factors in cornering stiffriess with a nonlinear map, which was designed by the parameter optimization method through the measurement data from real vehicle tests. This method was designed and validated with real vehicle experiments under various driving scenarios.
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