本文選題：轎車 + 參數(shù)化�。� 參考：《吉林大學(xué)》2016年博士論文

【摘要】：隨著汽車保有量的快速增長(zhǎng),能源過度消耗、環(huán)境污染等一系列社會(huì)問題隨之出現(xiàn)。汽車輕量化是減少能源消耗和污染物排放的重要途徑。白車身質(zhì)量占汽車總質(zhì)量的30%~40%,制造成本約占整車成本的60%,空載情況下大約70%的燃油被白車身消耗。因此白車身輕量化是汽車輕量化重要的組成部分。正面碰撞無論是發(fā)生率還是人員受到傷害和死亡率都較高,正碰被動(dòng)安全性能是汽車最重要的性能之一。白車身前端結(jié)構(gòu)質(zhì)量大約為白車身整體質(zhì)量的30%,吸能量大約為白車身總體吸能量的80%,白車身前端質(zhì)量對(duì)正碰安全性具有非常重要的作用。因此專門針對(duì)白車身前端結(jié)構(gòu)的輕量化優(yōu)化設(shè)計(jì)顯得更加重要。白車身前端結(jié)構(gòu)輕量化設(shè)計(jì)是一項(xiàng)多參數(shù)、多約束系統(tǒng)的復(fù)雜工程,涉及到動(dòng)、靜態(tài)剛度、NVH、耐撞性和制造成本等多項(xiàng)性能指標(biāo)。本文基于現(xiàn)有的白車身有限元模型,利用SFE-CONCEPT軟件建立了隱式參數(shù)化的白車身前端結(jié)構(gòu)模型,并與白車身后端有限元模型耦合在一起。以白車身耦合為基準(zhǔn),在保證白車身靜態(tài)彎扭剛度、一階扭轉(zhuǎn)、彎曲模態(tài)頻率、正面100%碰撞安全性不明顯降低和制造成本不顯著增加的前提下,綜合考慮部件的材料、厚度、斷面形狀、部件曲率等設(shè)計(jì)因素對(duì)白車身前端進(jìn)行結(jié)構(gòu)-材料-性能一體化輕量化多目標(biāo)優(yōu)化設(shè)計(jì)。本文主要開展了以下幾個(gè)方面的研究?jī)?nèi)容并得出了相關(guān)結(jié)論:(1)仿真分析白車身有限元模型的靜態(tài)彎扭剛度、低階模態(tài),通過與試驗(yàn)結(jié)果對(duì)比驗(yàn)證白車身有限元模型在靜態(tài)彎扭剛度、低階模態(tài)性能方面滿足建立參數(shù)化白車身前端的要求。再將白車身有限元模型與底盤、發(fā)動(dòng)機(jī)等有限元模型連接在一起,并進(jìn)行相關(guān)設(shè)置,按照新車評(píng)價(jià)程序(C-NCAP)進(jìn)行100%正碰、側(cè)碰安全性仿真分析,通過與試驗(yàn)結(jié)果對(duì)比驗(yàn)證白車身有限元模型在正碰安全性方面滿足建立參數(shù)化白車身前端的要求。(2)以白車身有限元模型為基準(zhǔn),用隱式參數(shù)化建模方法創(chuàng)建白車身前端結(jié)構(gòu)參數(shù)化模型,并將其與白車身后端有限元模型連接在一起構(gòu)成白車身耦合模型。在耦合模型的基礎(chǔ)上進(jìn)行靜態(tài)彎扭剛度、低階模態(tài)和正碰、側(cè)碰安全性仿真分析。隨后將相關(guān)性能與有限元模型的性能進(jìn)行對(duì)比從而驗(yàn)證耦合模型的有效性。(3)采用近似模型優(yōu)化方法對(duì)白車身耦合模型的參數(shù)化前端結(jié)構(gòu)進(jìn)行一體化輕量化多目標(biāo)優(yōu)化設(shè)計(jì),為了減少進(jìn)行試驗(yàn)優(yōu)化設(shè)計(jì)(DOE)過程中大量的重復(fù)工作,本文采用模塊化方法。根據(jù)模塊化分類原則將參數(shù)化白車身前端、白車身后端有限元模型分別設(shè)置為單獨(dú)的子模塊。試驗(yàn)設(shè)計(jì)中對(duì)白車身靜態(tài)彎扭剛度、低階模態(tài)和正碰安全性仿真分析時(shí),通過改變參數(shù)化白車身前端結(jié)構(gòu),再結(jié)合各自的子模塊文件,可方便的運(yùn)行試驗(yàn)設(shè)計(jì)樣本點(diǎn)。(4)在對(duì)白車身耦合模型的參數(shù)化前端進(jìn)行一體化輕量化多目標(biāo)優(yōu)化設(shè)計(jì)時(shí),合理的選取設(shè)計(jì)變量可以減少計(jì)算工作量,提高優(yōu)化效率。因此本文分析常用篩選變量方法之間的聯(lián)系與區(qū)別,在此基礎(chǔ)上提出綜合靈敏度分析方法,并證實(shí)該方法具有較高的優(yōu)化效率。利用該方法從23個(gè)初始設(shè)計(jì)變量中篩選出14個(gè)設(shè)計(jì)變量。以篩選出的14個(gè)設(shè)計(jì)變量為基準(zhǔn)構(gòu)建二階響應(yīng)面(Quadratic Response Surface Methodology,QRSM)、克里格(Kriging)和徑向基神經(jīng)網(wǎng)絡(luò)(Radial Basis Functions Neural Network,RBF)三種常用的近似模型,在第二代非劣排序遺傳算法(NSGA-Ⅱ)的基礎(chǔ)上計(jì)算出各性能響應(yīng),并比較響應(yīng)與仿真響應(yīng)之間的相對(duì)誤差,結(jié)果表明Kriging近似模型得到的響應(yīng)誤差最小。(5)為進(jìn)一步提高耦合模型的參數(shù)化前端減重效果,將前防撞梁、吸能盒的鋼質(zhì)材料替換為鋁合金。材料替換后對(duì)前防撞梁、吸能盒進(jìn)行拓?fù)鋬?yōu)化并得到相應(yīng)的主斷面結(jié)構(gòu)。隨后在SFE-CONCEPT軟件中建立前防撞梁、吸能盒的參數(shù)化模型,并與參數(shù)化白車身前端其他部件連接在一起,構(gòu)成多種材料的參數(shù)化白車身前端模型,鋁合金吸能盒與鋼質(zhì)前縱梁之間通過帶螺栓的法蘭盤實(shí)現(xiàn)連接。為得到前防撞梁、吸能盒和法蘭盤的尺寸、厚度、材料參數(shù),本文在篩選出的14個(gè)設(shè)計(jì)變量基礎(chǔ)上增加表征鋁合金前防撞梁等部件尺寸、厚度、材料的12個(gè)設(shè)計(jì)變量。同時(shí)本文還提出計(jì)算車身部件材料成本的方法,考慮車身前端在一體化輕量化多目標(biāo)優(yōu)化設(shè)計(jì)時(shí)帶來的材料成本變化。(6)選用Kriging近似模型優(yōu)化方法對(duì)耦合模型的參數(shù)化前端進(jìn)行一體化輕量化多目標(biāo)優(yōu)化設(shè)計(jì),優(yōu)化中以前端質(zhì)量最小、白車身靜態(tài)扭轉(zhuǎn)剛度最大和材料成本最低為目標(biāo),同時(shí)約束白車身靜態(tài)彎曲剛度,一階扭轉(zhuǎn)、彎曲模態(tài)頻率和正面100%碰撞安全性能不明顯降低,綜合考慮部件厚度、斷面形狀、曲率、不同材料的26個(gè)設(shè)計(jì)變量,利用NSGA-Ⅱ算法在設(shè)計(jì)空間搜索優(yōu)化妥協(xié)解集。以質(zhì)量最小的妥協(xié)解為參數(shù)化前端模型一體化輕量化優(yōu)化的設(shè)計(jì)方案,對(duì)該方案仿真分析后發(fā)現(xiàn),白車身前端質(zhì)量減少5.81Kg,減重率達(dá)7.01%,且白車身靜態(tài)彎扭剛度、低階模態(tài)和正碰安全性能沒有明顯變化,材料成本僅增加3.30%。另外經(jīng)仿真分析表明優(yōu)化后的白車身前端對(duì)側(cè)碰安全性能也幾乎沒有影響。
[Abstract]:With the rapid growth of car ownership, a series of social problems such as excessive energy consumption and environmental pollution, automobile lightweight is an important way to reduce energy consumption and pollutant emission. The quality of body white accounts for 30%~40% of the total vehicle quality, and the manufacturing cost accounts for about 60% of the total vehicle cost, and about 70% of the fuel is white in the case of empty load. Light weight is an important part of the vehicle lightweight. The front impact is one of the most important performance of the car, whether it is the occurrence rate, the injury and the death rate, and the positive impact is one of the most important performance of the car. The quality of the front end of the body in white is about 30% of the overall quality of the body in white, and the energy absorption is about the white body. With 80% of the total energy absorption, the front end quality of the body in white has a very important effect on the positive collision safety. Therefore, the lightweight optimization design of the front end structure of the body white is more important. The lightweight design of the front end structure of body white is a complex engineering of a multi parameter, multi constrained system, involving the dynamic, static stiffness, NVH, crashworthiness and Based on the existing finite element model of the body in white, this paper uses the SFE-CONCEPT software to establish an implicit parameterized front end structure model of the body in white and coupled with the finite element model of the back end of the body in white. The static bending stiffness, first torsion, bending die of the body in white body are guaranteed by the coupling of the body in white. On the condition of state frequency, the safety of frontal 100% collisions is not obviously reduced and the cost of manufacturing is not significantly increased, the design factors such as material, thickness, section shape, and component curvature are considered to integrate structure material performance integrated lightweight multi-objective optimization design on the front end of the body in white body. The following aspects are mainly carried out in this paper. The main contents are as follows: (1) simulation and analysis of the static bending and torsion stiffness of the finite element model of the body of white body and the low order mode. Through comparison with the experimental results, it is proved that the finite element model of the body in white can meet the requirements for the establishment of the parameterized front of the body in white, and then the finite element model and the chassis of the body in white. The finite element model of the engine is connected together, and the related setting is carried out. The 100% positive collision and the side collision safety simulation analysis are carried out according to the new car evaluation program (C-NCAP). By comparing with the test results, it is proved that the finite element model of the body in white meets the requirements of the establishment of the parameterized front end of the body in white. (2) the finite element model of the body in white. Based on the implicit parameterized modeling method, the parameterized model of the front end structure of the body in white is created. The model is connected with the finite element model of the back end of the body of the white body to form the coupling model of the body in white. The static bending stiffness, the low order mode and the positive collision and the side collision safety simulation analysis are carried out on the basis of the coupling model. The related performance and the related performance are then carried out. The performance of the finite element model is compared to verify the effectiveness of the coupling model. (3) an approximation model optimization method is used to integrate the parameterized front structure of the car body coupling model to the multi-objective optimization design. In order to reduce the repeated work in the process of experimental optimization design (DOE), the modular method is adopted in this paper. According to the modular classification principle, the front end of the white body is parameterized and the back end finite element model of the body in white is set to separate sub modules respectively. In the experiment design, the static bending and torsion stiffness, the low order mode and the positive collision safety of the body in white body are analyzed. By changing the parameters of the front structure of the body in white, it is convenient to combine the respective sub module files. (4) when integrating the parameterized front-end of the white body coupling model to the integrated lightweight multi-objective optimization design, the reasonable selection of the design variables can reduce the calculation work and improve the optimization efficiency. Therefore, this paper analyzes the relation and difference between the commonly used selection methods and proposes the comprehensive spirit on this basis. The method of sensitivity analysis proves that the method has high optimization efficiency. Using this method, 14 design variables are selected from 23 initial design variables. The two order response surface (Quadratic Response Surface Methodology, QRSM), Craig (Kriging) and radial basis neural network (Radial Basis) are constructed with selected 14 design variables. Functions Neural Network, RBF) three common approximate models, calculated the performance response on the basis of the second generation non inferior sorting genetic algorithm (NSGA- II), and compared the relative error between the response and the simulation response. The results show that the response error of the Kriging approximation model is the least. (5) to further improve the parameterization of the coupling model. The front end weight reduction effect is made by replacing the steel material of the front collision beam and the energy absorption box with the aluminum alloy. After the material is replaced, the front anti-collision beam, the energy absorption box is topologically optimized and the corresponding main section structure is obtained. Then, the pre collision beam, the energy absorption box's parameterized model is established in the SFE-CONCEPT software and connected with the other parts of the parameterized front end of the body of the body of the white body. Together, the parameterized front end model of the body in white is made up of a variety of materials. The aluminum alloy energy absorption box and the steel front longitudinal beam are connected through the flange plate with a bolt. In order to obtain the size, thickness and material parameters of the front collision avoidance beam, the energy absorption box and the flange plate, this paper increases the anticollision beam of the aluminum alloy on the basis of the selected 14 set variables. 12 design variables of component size, thickness and material, and the method of calculating the material cost of body parts is also proposed in this paper. The change of material cost brought by the body front end in integrated lightweight and multi-objective optimization design is considered. (6) the Kriging approximation model optimization method is used to integrate the parameterized front end of the coupled model. The objective optimization design is to minimize the front end quality, the maximum static torsional stiffness and the lowest material cost in the body of the body, while restraining the static bending stiffness of the body in white, first order torsion, the bending modal frequency and the 100% collision safety performance of the front face, and considering the thickness of the parts, the shape of the section, the curvature, and the 26 different materials. Design variables, using NSGA- II algorithm to optimize the compromise solution set in the design space search. With the minimum quality of the compromise solution to the parameterized front-end model integrated light quantization optimization design. After the simulation analysis, it is found that the front end quality of the body in white is reduced by 5.81Kg, the weight loss rate is 7.01%, and the static bending stiffness of the body in white, the lower order mode and the positive. There is no obvious change in the safety performance, the material cost is only increased by 3.30%. and the simulation analysis shows that the optimized front end of the body has little effect on the safety performance of the side impact.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：U463.82
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本文編號(hào)：1984686