Optimizing the beam-like structure of a vehicle body using the grey–fuzzy–Taguchi method

Yao, Weimin; Cai, Kefang; Xu, Yuan

doi:10.1080/0305215x.2019.1698033

Cited by 13 publications

(9 citation statements)

References 30 publications

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“…Apply constraints and loads to the BIW according to the standard, as shown in Fig 5 . Through the interval sampling of the lower surface of the front rail, sill beam and rear rail of the BIW, the maximum vertical displacement D Lmax and D Rmax of the measuring points on the left and right sides are extracted, and the static bending stiffness of the BIW is calculated by equation (12).…”

Section: ) Bending Stiffness Simulation Analysis and Test Verificationmentioning

confidence: 99%

“…Wang and Lv et al [11] proposed a new front-end submodule lightweight optimization method, constructed the implicit parametric coupling model of BIW, and the concept of analysis-oriented design was realized by comprehensively considering the construction efficiency and car performance of the BIW. Yao et al [12] optimized the beam structure parameters and improved the static and dynamic performance of the body by establishing the implicit parametric model of the typical body-in-prime structure.…”

Section: Introductionmentioning

confidence: 99%

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Multiobjective Optimization Design for Lightweight and Crash Safety of Body-in-White Based on Entropy Weighted Grey Relational Analysis and MNSGA-II

et al. 2022

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In order to improve the lightweight level, crash safety performance and optimization design efficiency of body-in-white (BIW), this article proposes a lightweight multi-objective optimization design method for mixed-material body. The implicit parametric model of the BIW is created by using SFE-CONCEPT software, and the validity and correctness of the model are verified by tests. Material, shape and dimension parameters are introduced as design variables for design of experiments (DOEs), and 26 important design variables are screened out by combining contribution analysis with nonlinear main effects analysis. The approximate model method is used to fit the Kriging surrogate model and the RBF surrogate model, and it is found that the RBF surrogate model can better reflect the relationship between nonlinear crash performance and optimization variables. A hybrid method combined entropy weighted grey relational analysis (EGRA) with modified non-dominated sorting genetic algorithm (MNSGA-Ⅱ) is proposed to carry out the lightweight multi-objective optimization of BIW in front crash and side impact, which improves the population diversity of multi-objective optimization problems and quantifies the comprehensive performance of each scheme. Comparing and analyzing the optimization platform recommending scheme, the technique for order preference by similarity to an ideal solution (TOPSIS) method preferring scheme and the EGRA method optimum scheme, it is found that EGRA method can obtain the optimal compromise scheme, and the performance improvement of the BIW are more obvious and the improvement rates are also more balanced. The results verify the feasibility of the ranking method, avoid the blindness of optimal solution selection, and establish an objective evaluation method of multiobjective optimization results. The optimization results show that the improvement rates of the BIW lightweight coefficient, the average value of the maximum acceleration of the B-pillars on both sides during the front crash, and the maximum intrusion displacement of the B-pillar chest during the side impact have reached 11.5%, 6.5%, and 6.8%, respectively. Other performance response improvement rates are also above 3.3%, the lightweight and crash safety performance are significantly improved.INDEX TERMS Entropy weighted grey relational analysis, Front crash and side impact safety, Implicit parametric body-in-white, Lightweight and multi-objective optimization, MNSGA-II

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Section: ) Bending Stiffness Simulation Analysis and Test Verificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multiobjective Optimization Design for Lightweight and Crash Safety of Body-in-White Based on Entropy Weighted Grey Relational Analysis and MNSGA-II

et al. 2022

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“…Therefore, a method combining GRA and Taguchi design was proposed by researchers 31 , 32 , which can not only overcome the defect that Taguchi method cannot solve multi-objective optimization 33 , but also mine the information of the whole parameter space with limited sample size as much as possible. However, the GRA cannot provide an optimal solution of highly robust for a given multi-objective optimization problem, because this method cannot quantitatively or qualitatively distinguish the ideal case of foraging problem with no solution (black) and unique solution (white) 34 . In detail, different normalized formulas are applied on the basis of target characteristics, and then the grey relational coefficient and GRG are calculated, which leads to the uncertainty of the optimal solution of GRA 35 , 36 .…”

Section: Introductionmentioning

confidence: 99%

“…Tran et al employed the mothed of grey fuzzy reasoning grade analysis to execute optimization on carbon fiber–reinforced polymer 38 . Yao et al optimized the beam-like structure by applying the fuzzy decision method 34 . Saini et al proposed a novel forecast method by combining particle swarm optimization algorithm with fuzzy inference system tree 39 .…”

Section: Introductionmentioning

confidence: 99%

A new fuzzy rule based multi-objective optimization method for cross-scale injection molding of protein electrophoresis microfluidic chips

Shan

Lei

et al. 2022

Sci Rep

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Injection molding is one of the most promising technologies for the large-scale production and application of polymeric microfluidic chips. The multi-objective optimization of injection molding process for substrate and cover plate on protein electrophoresis microfluidic chip is performed to solve the problem that the forming precision is difficult to coordinate because of the cross-scale structure characteristics for chip in this paper. The innovation for this research is that an optimization approach and a detailed fuzzy rule determination method are proposed in multi-objective optimization for protein electrophoresis microfluidic chip. In more detail, firstly, according to the number and level of process parameters, the orthogonal experimental design is carried out. Then, the experiments are performed. Secondly, the grey relational analysis (GRA) approach is employed to process the response data to gain the grey relational coefficient (GRC). Thirdly, the grey fuzzy decision making method which combines triangular membership function and gaussian membership function is adopted to obtain the grey fuzzy grade (GFG). After that, the optimal scheme of process parameters was predicted by the grey fuzzy grade analysis. Finally, the superiority of Taguchi grey fuzzy decision making method are verified by comparing the results of original scheme, optimal scheme and prediction scheme. As a result, compared with the original design, the residual stress of substrate plate (RSS), residual stress of cover plate (RSC), warpage of substrate plate (WS), warpage of cover plate (WC) and replication fidelity of microchannel for substrate plate (RFM) on the prediction scheme for Taguchi grey fuzzy decision making method were reduced by 32.816%, 29.977%, 88.571%, 74.390% and 46.453%, respectively.

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“…27,28 Recently, GRA is gradually used to solve multiobjective decision-making problems. Yao et al 29 applied GRA with fuzzy logic to determine the optimal design parameters of beam-like structures. Lian et al 30 determined the satisfactory laser cladding processing parameters by utilizing multi-response GRA.…”

Section: Introductionmentioning

confidence: 99%

Collaborative optimization design of lightweight and crashworthiness of the front-end structures of automobile body using HW–GRA for Pareto mining

Wang

2021

Proceedings of the Institution of Mechanical Engineers, Part C:

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To collaboratively improve the lightweight and frontal collision safety performance of the automobile body, the material–structure–performance integrated multi-objective optimization design of the front-end structure was implemented in this study. The hybrid weight–grey relational analysis (HW–GRA) method was proposed to address the problem that the Pareto optimal compromise solution of multi-objective optimization cannot be easily selected. The design variables of the material and structural parameters were recorded through material type coding and model parameterization. To satisfy the basic static–dynamic performance constraints of the body, the RSM–Kriging surrogate model, design of experiments, and multi-objective particle swarm optimization algorithm were used to optimize the material and structural parameters to improve the lightweight and crashworthiness of the body. The Pareto optimal compromise solution was determined using the HW–GRA method. The decision result of the proposed method was more robust and rational than those of single weighting techniques combined with GRA and hybrid weighting approach combined with TOPSIS. After the multi-objective optimization and decision-making, the basic static–dynamic performance of the body demonstrated a change of less than 2.0%, which satisfied the constraint requirements. The mass of the body was reduced by 2.4 kg, and the frontal collision safety performance of the body was significantly improved.

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Optimizing the beam-like structure of a vehicle body using the grey–fuzzy–Taguchi method

Cited by 13 publications

References 30 publications

Multiobjective Optimization Design for Lightweight and Crash Safety of Body-in-White Based on Entropy Weighted Grey Relational Analysis and MNSGA-II

Multiobjective Optimization Design for Lightweight and Crash Safety of Body-in-White Based on Entropy Weighted Grey Relational Analysis and MNSGA-II

A new fuzzy rule based multi-objective optimization method for cross-scale injection molding of protein electrophoresis microfluidic chips

Collaborative optimization design of lightweight and crashworthiness of the front-end structures of automobile body using HW–GRA for Pareto mining

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