Multi-objective optimization of automobile body frame considering weight, rigidity, and frequency for conceptual design

Wang, Xiaoguang; Sun, Pengfei; Zuo, Wenjie; Bai, Jiantao

doi:10.1177/16878132221078495

Cited by 6 publications

(3 citation statements)

References 36 publications

(35 reference statements)

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“…The multi-objective evolutionary method may yield numerous optimum solutions in a single run, meeting the article's study requirements. At present, multi-objective evolutionary algorithms have become a hot area of research in perceptual engineering, especially NSGA-II [26,27] is more widely studied in the field of product perceptual imagery optimization. Scholars have used various methods to improve the traditional NSGA-II algorithm to obtain better product optimization models.…”

Section: Multi-objective Optimization Algorithm For Product Appearancementioning

confidence: 99%

Multi-Objective Image Optimization of Product Appearance Based on Improved NSGA-Ⅱ

Ao,

Lv,

Xie

et al. 2023

Computers, Materials &Amp; Continua

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A second-generation fast Non-dominated Sorting Genetic Algorithm product shape multi-objective imagery optimization model based on degradation (DNSGA-II) strategy is proposed to make the product appearance optimization scheme meet the complex emotional needs of users for the product. First, the semantic differential method and K-Means cluster analysis are applied to extract the multi-objective imagery of users; then, the product multidimensional scale analysis is applied to classify the research objects, and again the reference samples are screened by the semantic differential method, and the samples are parametrized in two dimensions by using elliptic Fourier analysis; finally, the fuzzy dynamic evaluation function is used as the objective function of the algorithm, and the coordinates of key points of product contours Finally, with the fuzzy dynamic evaluation function as the objective function of the algorithm and the coordinates of key points of the product profile as the decision variables, the optimal product profile solution set is solved by DNSGA-II. The validity of the model is verified by taking the optimization of the shape scheme of the hospital connection site as an example. For comparison with DNSGA-II, other multi-objective optimization algorithms are also presented. To evaluate the performance of each algorithm, the performance evaluation index values of the five multi-objective optimization algorithms are calculated in this paper. The results show that DNSGA-II is superior in improving individual diversity and has better overall performance.

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Section: Multi-objective Optimization Algorithm For Product Appearancementioning

confidence: 99%

Multi-Objective Image Optimization of Product Appearance Based on Improved NSGA-Ⅱ

Ao,

Lv,

Xie

et al. 2023

Computers, Materials &Amp; Continua

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show abstract

“…Ma et al [11] studied the fatigue damage caused by unreasonable layout of stiffeners and welding failure of the dump truck frame and optimized the position and quantity of stiffeners by using multi-island genetic algorithm without gradient information, which significantly improved the service life of the frame and reduced the quality of the frame. Xionguang et al [12] used the optimization method of a non-dominant ordering genetic algorithm (NSGA-II.) combined with an artificial neural network to carry out a multi-objective optimization design of automobile A-pillar.…”

Section: Introducementioning

confidence: 99%

Multi-condition stability analysis and lightweight research of mining wide-body dump truck compartment

Liu,

Tian

et al. 2024

Meas. Sci. Technol.

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This paper proposes a multi-condition optimization method based on single condition optimization and weight. This method analyzes and discusses various working states of the wide-body dump truck and optimize its structure. Firstly, the modal shape and natural frequency of the carriage under modal conditions are analyzed using the finite element method. Combined with the mechanic’s theory, the carriage's force, deformation, and stress are studied under the turning and partial load conditions. This part provides a basis for subsequent stability analysis and lightweight research. According to the filtering white noise method and differential equation method, the f-class road model and the vehicle system dynamics model are established in MATLAB to study the influence of road vibration on the stability of the dump truck during operation. The carriage vibration data prove that the road vibration causes the low order resonance of the carriage and affects the stability of the dump truck. This part provides a basis for the subsequent stability optimization. Based on the above analysis, a multi-objective genetic algorithm (MOGA) based on the response surface is used to optimize the structural parameters of the carriage under partial load conditions, turning conditions and modal conditions, to realize the optimization of stability, mass, stress and deformation of the carriage. Finally, the entropy weight method is used to fuse the optimization results of the three working conditions. The correctness of the comprehensive optimization results is verified, and the wide-body dump truck carriage optimization is realized, proving the feasibility of the proposed method.

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“…During the development of an impact, are developed three main phenomena, the impact of the vehicle versus another vehicle or an object, the impact of the driver or occupants with vehicle interiors and the impact of the organs with internal parts of the body. Because of this, after the first energy peak developed by the absorber, it is important to control the way energy is absorbed to attenuate the generation of peaks during the controlled deformation process [1,2]. Crashworthiness design criteria have even greater importance for structures that are designed to withstand impact conditions.…”

Section: Introductionmentioning

confidence: 99%

Energy Dissipation Enhancement of Thin-Walled 6063 T5 Aluminium Tubes by Combining a Triggering Mechanism and Heat Treatment

Jiménez-Armendáriz,

Jimenez-Martinez,

Varela-Soriano

et al. 2023

Metals

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It is necessary to reduce the weight of components while maintaining or improving their mechanical properties to withstand dynamic loads in lightweight structures. In this study, heat treatment and a trigger mechanism were implemented for a thin-walled tube of aluminium to increase energy absorption while reducing the peak crushing force. Different geometries and locations were proposed to trigger deformation in a controlled manner, in combination with heat treatments. Experimental designs for each energy absorption mechanism were performed, and designs were tested by quasi-static crushing. Data obtained from experiments were used to calculate energy absorption indicators that were used to compared designs with components without mechanism to analyse performance. By comparing proposed designs with tubes without modification, the best combination of design variables for each trigger mechanism were identified. It was determined that 160 mm from the upper side, 250 mm2 area and a rectangular trigger shape reduced peak crushing force by 22.03% and increased energy absorption by 37.76%. For heat treatment, the optimal combination was heating in a furnace at 175 ∘C for 1 h and cooling in water at 70 ∘C during 10 min while only soaking half of its length. This combination reduced peak crushing force by 19.02% and increased energy absorption 15.08%. When these mechanisms were combined on a single tube, peak crushing force was reduced by 21.63%, and energy absorption increased by 42.53%.

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Multi-objective optimization of automobile body frame considering weight, rigidity, and frequency for conceptual design

Cited by 6 publications

References 36 publications

Multi-Objective Image Optimization of Product Appearance Based on Improved NSGA-Ⅱ

Multi-Objective Image Optimization of Product Appearance Based on Improved NSGA-Ⅱ

Multi-condition stability analysis and lightweight research of mining wide-body dump truck compartment

Energy Dissipation Enhancement of Thin-Walled 6063 T5 Aluminium Tubes by Combining a Triggering Mechanism and Heat Treatment

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