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黑龍江工程學(xué)院本科生畢業(yè)設(shè)計
摘 要
本設(shè)計結(jié)合懸架設(shè)計知識，詳細分析了懸架結(jié)構(gòu)，對雙橫臂獨立懸架進行了設(shè)計計算。在此基礎(chǔ)上，應(yīng)用虛擬樣機技術(shù)，在ADAMS/View中對雙橫臂獨立懸架進行合理簡化并建模，并對模型進行了參數(shù)化，定制界面，即改變初始參數(shù)就能快速生成不同的懸架模型，提高了仿真分析以及優(yōu)化設(shè)計的效率，使平臺具有開放性。分析研究了所需優(yōu)化的變量（前輪外傾角、車輪側(cè)滑量）及其函數(shù)表達式。進行了懸架動力學(xué)仿真分析，研究懸架各性能參數(shù)在車輪跳動過程中的變化趨勢，并指出需要改進的地方。分析每個設(shè)計變量的變化對樣機性能的影響，提出優(yōu)化設(shè)計的方案。再次進行仿真，對比分析了優(yōu)化前后的仿真結(jié)果，并評價了優(yōu)化方案。優(yōu)化后懸架的性能明顯提高，驗證了優(yōu)化方案的可行性，并完成虛擬設(shè)計及試驗。最后運用Pro/E軟件對雙橫臂獨立懸架進行實體的建立。
本設(shè)計研究的目的和意義為在賽車制造前進行設(shè)計和試驗仿真，并且提出改進意見，可以發(fā)現(xiàn)并更正設(shè)計缺陷，完善設(shè)計方案，提高設(shè)計質(zhì)量和效率。
關(guān)鍵詞：雙橫臂；獨立懸架；虛擬樣機技術(shù)；優(yōu)化；ADAMS
ABSTRACT
On the basis of the Suspension design, this paper calculated a detailed requirements for double wishbone independent suspension structure, I simplified and built a model of double wishbone independent suspension system in ADAMS/View, made the model parameters, then the model was open, and prepared the necessary measuring function. I discussed the performance of the front wheel alignment parameters in a front wheel vehicle positioning. The model was a virtual front suspension test platform. This thesis analyzed the change trend of the suspension performance parameters in the process of flopping the wheel. The impacts of its changes in the trend of design variables are also analyzed, make an optimized design of the program, with the comparative analysis to verify the feasibility of the optimization program before and after the optimization, the suspension’s key data was generated, the virtual design and test were finished. Finally I used Pro/E for double wishbone independent suspension a modeling.
The design for the purpose and significance of the study in car manufacturing design and test before simulation, and puts forward Suggestions of improvement can be found and corrected design flaw, perfecting the design scheme, and improve the design quality and efficiency.
Keywords: Double Wishbone; Independent suspension; Virtual Prototyping Technology; Optimize; ADAMS
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