Research on Key Issues of Consistency Analysis of Vehicle Steering Characteristics
Tóm tắt
Given the global lack of effective analysis methods for the impact of design parameter tolerance on performance deviation in the vehicle proof-of-concept stage, it is difficult to decompose performance tolerance to design parameter tolerance. This study proposes a set of consistency analysis methods for vehicle steering performance. The process of consistency analysis and control of automotive performance in the conceptual design phase is proposed for the first time. A vehicle dynamics model is constructed, and the multi-objective optimization software Isight is used to optimize the steering performance of the car. Sensitivity analysis is used to optimize the design performance value. The tolerance interval of the performance is obtained by comparing the original car performance value with the optimized value. With the help of layer-by-layer decomposition theory and interval mathematics, automotive performance tolerance has been decomposed into design parameter tolerance. Through simulation and real vehicle experiments, the validity of the consistency analysis and control method presented in this paper are verified. The decomposition from parameter tolerance to performance tolerance can be achieved at the conceptual design stage.
Tài liệu tham khảo
X Guan. Research progress of vehicle dynamics modeling and simulation in national key laboratory of vehicle dynamics. Changchun: Academic Report of National Key Laboratory of Automobile Dynamic Simulation of Jilin University, 2009.
L X Zhang, J Q Liu, F Q Pan, et al. Multi-objective optimization study of vehicle suspension based on minimum time handling and stability. Proceedings of the Institution of Mechanical Engineers, 2020, 234(9): 2355-2363.
H Xu, Y Q Zhao, C Ye, et al. Integrated optimization for mechanical elastic wheel and suspension based on an improved artificial fish swarm algorithm. Advances in Engineering Software, 2019: 137.
Q Shi, C W Peng, Y K Chen, et al. Robust kinematics design of MacPherson suspension based on a double-loop multi-objective particle swarm optimization algorithm. Journal of Automobile Engineering, 2019, 233(12): 3263-3278.
X Guan, S Y Feng, J Zhan, et al. Solve the Angle and position of the spindle axis based on steering geometry. Engineering Science and Technology, 2009, 9(21): 6593-6596.
J J Hu, Z B He, P Ge, et al. Modeling and simulation of electric power steering system based on multi-body dynamics. Applied Mechanics and Materials, 2012, 1498: 2091-2097.
H Spencer, R X Ning. Virtual product development technology. Beijing: China Machine Press, 2002.
X M Shi. Automobile chassis innovation research and development and computer simulation. Changchun: Academic Report of National Key Laboratory of Automobile Dynamic Simulation of Jilin University, 2006.
T D Kim, J H Kim, J H Kim. Sensitivity analysis and optimum design of energy harvesting suspension system according to vehicle driving conditions. Journal of the Korean Society for Precision Engineering, 2019, 36(12): 1173-1181.
E Sert, P Boyraz. Optimization of suspension system and sensitivity analysis for improvement of stability in a midsize heavy vehicle. Engineering Science and Technology, an International Journal, 2017, 20(3): 997-1012.
M Sandim, A Paiva, L H D Figueiredo. Simple and reliable boundary detection for mesh free particle methods using interval analysis. Journal of Computational Physics, 2020, 420.
Y H Ma, Y F Wang, C Wang, et al. Interval analysis of rotor dynamic response based on Chebyshev polynomials. Chinese Journal of Aeronautics, 2020, 9: 2342–2356.
L M Tang, Y Xiao, J W Xie. Fatigue cracking checking of cement stabilized macadam based on measurement uncertainty and interval analysis. Construction and Building Materials, 2020, 250.
J W Fan, H H Tao, R Pan, et al. An approach for accuracy enhancement of five-axis machine tools based on quantitative interval sensitivity analysis. Mechanism and Machine Theory, 2020, 148: 103806.
H B Huang, J H Wu, X R Huang, et al. A novel interval analysis method to identify and reduce pure electric vehicle structure-borne noise. Journal of Sound and Vibration, 2020, 475: 115258.
Z Li, L Zheng. Integrated design of active suspension parameters for solving negative vibration effects of switched reluctance-in-wheel motor electrical vehicles based on multi-objective particle swarm optimization. Journal of Vibration and Control, 2019, 25(3): 639-654.
M H Shojaeefard, A Khalkhali, S Yarmohammadisatri. An efficient sensitivity analysis method for modified geometry of Macpherson suspension based on Pearson correlation coefficient. Vehicle System Dynamics, 2017, 55(6): 827-852.
H Taghavifar, S Rakheja. Parametric analysis of the potential of energy harvesting from commercial vehicle suspension system. Journal of Automobile Engineering, 2019, 233(11): 2687-2700.
R K Ding, R C Wang, X P Meng, et al. Energy consumption sensitivity analysis and energy-reduction control of hybrid electromagnetic active suspension. Mechanical Systems and Signal Processing, 2019, 134(Dec.1): 106301.1-106301.20.
Y Q Zhao, H Xu, Y J Deng, et al. Multi-objective optimization for ride comfort of hydro-pneumatic suspension vehicles with mechanical elastic wheel. Journal of Automobile Engineering, 2019, 233(11): 2714-2728.
B R Fang, J D Zhou, Y M Li. Matrix theory. Beijing: Tsinghua University Press, 2004.
W B Guo, M S Wei. Singular value decomposition and its application in generalized inverse theory. Beijing: Science Press, 2008.
X B Ma, P K Wong, J Zhao. Practical multi-objective control for automotive semi-active suspension system with nonlinear hydraulic adjustable damper. Mechanical Systems and Signal Processing, 2019, 117: 667-688.
A Khadr, A Houidi, L Romdhane. Design and optimization of a semi-active suspension system for a two-wheeled vehicle using a full multibody model. Proceedings of the Institution of Mechanical Engineers. Part K, Journal of Multi-body Dynamics, 2017, 231(k4): 630-646.
A Seifi, R Hassannejad, M A Hamed. Use of nonlinear asymmetrical shock absorbers in multi-objective optimization of the suspension system in a variety of road excitations. Proceedings of the Institution of Mechanical Engineers. Part K, Journal of Multi-body Dynamics, 2017, 231(2): 372-387.
R Soon, L N B Gummadi, K Cao. Robustness considerations in the design of a stabilizer bar system. SAE Paper, 2005, 01: 1718.
J Zhou. Reliability and robustness mindset in automotive product development for global markets. SAE Paper, 2005, 01: 212.
Narasimhan K, Sharma A K. Multistage process optimization for manufacturing automotive component using finite element method. SAE Paper, 2005, 26: 332.
D J Ball, M G Zammit, G C Mitchell. Program optimization by robust design. SAE Paper, 2005, 01: 3849.
H An, S Chae, H Kim. Optimum design of exhaust system using the robust design. SAE Paper, 2006, 01: 0082.
E G Leaphart. Application of robust engineering methods to improve ECU software testing. SAE Paper, 2006, 01: 1600.
A Zutshi, B Avutapalli, D Stagner, et al. Applying six sigma tools to the rear driveline system for improved vehicle level NVH performance. SAE Paper, 2007, 01: 2286.
S Lee, W Ha, T Yeo. Robust design for occupant protection system using Taguchi’s method. SAE Paper, 2007, 01: 3724.
Y Q Zhang. The smoothness analysis and parameter selection of virtual prototype based on orthogonal test. Automotive Technology, 2005, 10.
M Yao, G L Wang, K K Zhou. Robust optimization design of structural parameters of vehicle drum brake. Journal of Agricultural Machinery, 2005, 36(121): 17-20.
M Q Wang. The application of Taguchi method in the optimization of vehicle body frame stiffness. Automotive Technology, 1998, 5: 5-7.
C Y Tang. The optimal design of vehicle dynamic stability characteristics. Wuhan: Huazhong University of Science and Technology, 2007.
J H Dong. Multi-objective optimization method and application research based on microgenetic algorithm. Changsha: Hunan University, 2010.
Fengli Huang, Jianping Lin, Meipeng Zhong, et al. Multi-objective robust design and optimum algorithm in injection molding processing. Journal of Tongji University, 2011, 39(2): 287-291+298.
K Guo, L Chen, Y H Wei. Optimization and its application. Beijing: Higher Education Press, 2007.
C Fu, Y Liu, Z Xiao. Interval differential evolution with dimension-reduction interval analysis method for uncertain optimization problems. Applied Mathematical Modelling, 2018, 69: 441-452.