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가상차량 벨지안 주행해석을 통한 CTBA 내구하중 민감도 연구
유근수(Geunsoo Ryu),전재욱(Jae-Wook Jeon),김준엽(June-Yeop Kim) 한국자동차공학회 2011 한국자동차공학회 부문종합 학술대회 Vol.2011 No.5
With recent trends of the vehicle company reducing the number of making prototype and reliability test to reduce vehicle developing cost and time, VPG (Virtual Proving Ground) is a very useful and effective method to evaluate the vehicle performances such as Ride & Handling, NVH and durability in the concept design stage without vehicle prototype. This paper proposes the prediction method of the fatigue load changing with respect to the vehicle design variables such as body mass and inertia, ride height, wheel tread/base and tire aspect ratio/size using a VPG correlated with wheel input load of test results. This study also presents an application example of the developing vehicle shared same platform with base model without real vehicle prototype test using these parameter studies.
4POST 가진 시험을 통한 가상차량 벨지안 주행 해석의 시험 상관성 개선연구
유근수(Geunsoo Ryu),김준엽(Jun-Yeop Kim),신재광(Jaekwang Shin) 한국자동차공학회 2012 한국자동차공학회 학술대회 및 전시회 Vol.2012 No.11
The main advantages of virtual testing approach using multi-body dynamics analysis include that the design can be evaluated and easily validated by subsequent physical testing before a prototype. It is hard to get accurate simulation results with full vehicle dynamics model on the rough road surfaces such as Belgian road and to get accurate components model such as tire, road profile, vehicle model. This paper describes the correlation method of full vehicle model using 4 post excitation tests and evaluates the sprung, unsprung mass response and each wheel force of selected vehicles to cyclical vertical accelerations over a range of frequencies.
전재욱(Jaewook Jeon),유근수(Geunsoo Ryu),민준홍(Junhong Min) 한국자동차공학회 2013 한국자동차공학회 부문종합 학술대회 Vol.2013 No.5
Numerical simulation is now routinely used to predict the behavior and response of complex systems. But uncertainties enter into a numerical simulation from a variety of source, such as variability in input parameters due to inherent scatter in data, lack of or insufficient input information, modeling assumptions, and human error. In durability problems there will be a number of input uncertainties associated with the model, such as material properties, loadings, geometry, boundary conditions, etc. This research proposes a probabilistic prediction process of durability load distribution. In early design stage, virtual proving ground simulation is essential to estimate vehicle durability using vehicle, tire and road model. Previous researches have used deterministic approach to predict various performances using constant mean factors, and considered uncertainties through safety factor. This paper includes process of durability load prediction and considering uncertainties to consider diversity of region and specification, tuning properties for other performance and test conditions. In addition process integration is developed to execute probabilistic analysis efficiently.