Browse > Article

An Application of DoE Methodology in WAVE Simulation to Identify the Effectiveness of Variables on Engine Performance and to Optimize Responses  

Jeong, Dong-Won (Graduate Department of Mechanical and Automotive Engineering, Ulsan University)
Lim, Ock-Taeck (Department of Mechanical and Automotive Engineering, Ulsan University)
Publication Information
Transactions of the Korean Society of Automotive Engineers / v.17, no.5, 2009 , pp. 16-25 More about this Journal
Abstract
Testing engine performance using an engine dynamometer requires high technical researchers and many facilities. Nowadays, different variables of CAE program are used for identifying the engine performance instead of engine dynamometer test. This is more convenience, as it does not necessitate an abundance of engine dynamometer experiments and, in addition, produces better results. However, CAE programs also contain various variables which can affect engine performance. Those are coupled with each other, thus making it difficult to determine the effectiveness of different variables on engines. DoE (Design of Experiments) methodology is an efficient way to verify the magnitude of effectiveness on engine performance as well as making responses to be optimized at once without trial & error. This study used data from WAVE simulations, which modeled the DOHC SI engine with in-line 4 cylinders at 1500, 3000 and 4500rpm. DoE methodology is designed properly to determine the effectiveness of five variables on power, BSFC, and volumetric efficiency, as well as to find the optimal response conditions at each rpm through a minimized number of experiments. After finishing DoE process, all the results are examined concerning the reliability of test through a verification experiment.
Keywords
Design of experiments; WAVE; Response; Variable; Effectiveness; Optimization;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Ricardo, WAVE Software User Manual and Tutorial, RICARDO, 2006
2 X. P. Liu and S. y, Jiang, "A DOE Based Approach to Multi-Response Optimization," SAE 2003-01-0880, 2003
3 D. H, Kim, D, Diganta, T. Ganbold and O. T. Lim, "A Simulation for Identifying Influence of The VVT Effect on the SI Engine Performance using WAVE," Fall Conference Proceedings, KSAE, pp.164-169, 2008
4 J. F, O'Connor, C, L. White and M. R, Charnley, "Optimizing CFD Prediction of Diesel Engine Combustion and Emissions Using Design of Experiments: Comparison with Engine Measurements," SAE 982458, 1998
5 S.B.Lee, 미니탭 15버전을 활용한 예제 중심의 실험계획법, 이레테크, pp.195-318, 2008
6 E. R. Moen, R. D, Moen and T. R. Young, "DOE for Accelerated Learning and Better Vehicle Performance," SAE 983021,1998
7 S. H. Lee, Minitabg을 이용한 공학 통계 자료분석, 이레테크, pp.647-778, 2008
8 D. B, Jeong, J. H. Bang and K. D. Min, "A Study on the Optimization of Operating Variables in a Diesel Engine by Design of Experiments," Spring Conference Proceedings, Vol.1, KSAE, pp,292-297, 2008