A system methodology for optimization design of the structural crashworthiness of a vehicle subjected to a high-speed frontal crash

ABSTRACT The structural crashworthiness design of vehicles has become an important research direction to ensure the safety of the occupants. To effectively improve the structural safety of a vehicle in a frontal crash, a system methodology is presented in this study. The surrogate model of Online support vector regression (Online-SVR) is adopted to approximate crashworthiness criteria and different kernel functions are selected to enhance the accuracy of the model. The Online-SVR model is demonstrated to have the advantages of solving highly nonlinear problems and saving training costs, and can effectively be applied for vehicle structural crashworthiness design. By combining the non-dominated sorting genetic algorithm II and Monte Carlo simulation, both deterministic optimization and reliability-based design optimization (RBDO) are conducted. The optimization solutions are further validated by finite element analysis, which shows the effectiveness of the RBDO solution in the structural crashworthiness design process. The results demonstrate the advantages of using RBDO, resulting in not only increased energy absorption and decreased structural weight from a baseline design, but also a significant improvement in the reliability of the design.

[1]  Wei Chen,et al.  Use of support vector regression in structural optimization: Application to vehicle crashworthiness design , 2012, Math. Comput. Simul..

[2]  Anoop K. Dhingra,et al.  Reliability-based design optimization with progressive surrogate models , 2014 .

[3]  Guangyao Li,et al.  Reliability-based multiobjective optimisation of vehicle bumper structure holes for the pedestrian flexible legform impact , 2016 .

[4]  Morteza Kiani,et al.  A Comparative Study of Non-traditional Methods for Vehicle Crashworthiness and NVH Optimization , 2016 .

[5]  Giovanni Montana,et al.  Learning to Trade with Incremental Support Vector Regression Experts , 2008, HAIS.

[6]  Kiran Solanki,et al.  Multi-objective optimization of vehicle crashworthiness using a new particle swarm based approach , 2012 .

[7]  Guangyao Li,et al.  Reliable optimisation design of vehicle structure crashworthiness under multiple impact cases , 2017 .

[8]  Ali Rıza Yıldız,et al.  OPTIMAL DESIGN OF VEHICLE COMPONENTS USING TOPOLOGY DESIGN AND OPTIMISATION , 2004 .

[9]  Kyung K. Choi,et al.  A NEW STUDY ON RELIABILITY-BASED DESIGN OPTIMIZATION , 1999 .

[10]  Kiran Solanki,et al.  System reliability based vehicle design for crashworthiness and effects of various uncertainty reduction measures , 2009 .

[11]  Qing Li,et al.  A Comparative study on multiobjective reliable and robust optimization for crashworthiness design of vehicle structure , 2013 .

[12]  Francesco Parrella Online Support Vector Regression , 2007 .

[13]  Ali Riza Yildiz,et al.  A new design optimization framework based on immune algorithm and Taguchi's method , 2009, Comput. Ind..

[14]  Necmettin Kaya,et al.  Hybrid multi-objective shape design optimization using Taguchi’s method and genetic algorithm , 2007 .

[15]  Yu Zhang,et al.  Metamodeling development for reliability-based design optimization of automotive body structure , 2011, Comput. Ind..

[16]  Marco Merlo,et al.  Acute Hemodynamic Response to Cardiac Resynchronization in Dilated Cardiomyopathy: Effect on Late Mitral Regurgitation , 2015, Pacing and clinical electrophysiology : PACE.

[17]  Ali Rıza Yıldız,et al.  Structural Damage Detection Using Modal Parameters and Particle Swarm Optimization , 2012 .

[18]  Necmettin Kaya,et al.  Neuro-Genetic Design Optimization Framework to Support the Integrated Robust Design Optimization Process in CE , 2006, Concurr. Eng. Res. Appl..

[19]  Ali R. Yildiz,et al.  A new hybrid artificial bee colony algorithm for robust optimal design and manufacturing , 2013, Appl. Soft Comput..

[20]  Karim Hamza,et al.  A framework for parallelized efficient global optimization with application to vehicle crashworthiness optimization , 2014 .

[21]  Qing Li,et al.  Crashworthiness design of multi-component tailor-welded blank (TWB) structures , 2013 .

[22]  Liu Weiguo,et al.  Reliability design optimization of vehicle front-end structure for pedestrian lower extremity protection under multiple impact cases , 2015 .

[23]  Si Wu,et al.  Improving support vector machine classifiers by modifying kernel functions , 1999, Neural Networks.

[24]  Pingfeng Wang,et al.  Dynamic reliability-based robust design optimization with time-variant probabilistic constraints , 2014 .

[25]  Zhen Hu,et al.  Reliability-based design optimization under stationary stochastic process loads , 2016 .

[26]  Lee D. Han,et al.  Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions , 2009, Expert Syst. Appl..

[27]  Roman M. Balabin,et al.  Support vector machine regression (SVR/LS-SVM)--an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data. , 2011, The Analyst.

[28]  Kaushik Sinha,et al.  Reliability-based multiobjective optimization for automotive crashworthiness and occupant safety , 2007 .

[29]  Ali R. Yildiz,et al.  Structural design of vehicle components using gravitational search and charged system search algorithms , 2015 .

[30]  S. Gabel,et al.  Using Neural Networks , 2003 .

[31]  Ali Rıza Yıldız,et al.  Optimal Structural Design of Vehicle Components Using Topology Design and Optimization , 2008 .

[32]  G. Gary Wang,et al.  ADAPTIVE RESPONSE SURFACE METHOD - A GLOBAL OPTIMIZATION SCHEME FOR APPROXIMATION-BASED DESIGN PROBLEMS , 2001 .

[33]  Guangyao Li,et al.  Crashworthiness design of vehicle by using multiobjective robust optimization , 2011 .

[34]  Jianwei Lu,et al.  Reliability-based robust assessment for multiobjective optimization design of improving occupant restraint system performance , 2014, Comput. Ind..

[35]  Zhong Wan,et al.  Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems , 2014 .

[36]  Xu Han,et al.  Multivariable crashworthiness optimization of vehicle body by unreplicated saturated factorial design , 2012 .

[37]  Ali Rıza Yıldız,et al.  Optimization of thin-wall structures using hybrid gravitational search and Nelder-Mead algorithm , 2015 .

[38]  Ping Zhu,et al.  Metamodel-based lightweight design of B-pillar with TWB structure via support vector regression , 2010 .

[39]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[40]  Ali R. Yildiz,et al.  A new hybrid particle swarm optimization approach for structural design optimization in the automotive industry , 2012 .

[41]  Ali R. Yildiz,et al.  Comparison of evolutionary-based optimization algorithms for structural design optimization , 2013, Eng. Appl. Artif. Intell..

[42]  Nong Zhang,et al.  Interval multi-objective optimisation of structures using adaptive Kriging approximations , 2013 .

[43]  Anoop K. Dhingra,et al.  An efficient approach for reliability-based topology optimization , 2016 .

[44]  Jian Liu,et al.  An efficient ensemble of radial basis functions method based on quadratic programming , 2016 .

[45]  Necmettin Kaya,et al.  Integrated optimal topology design and shape optimization using neural networks , 2003 .

[46]  Ren-Jye Yang,et al.  An adaptive response surface method for crashworthiness optimization , 2013 .

[47]  Manochehr Manteghi,et al.  The Automotive Industry , 2013 .