Development of simplified tire model to estimate tire strains from finite elements analysis = 유한 요소 해석을 이용한 타이어 변형량 예측 모델 개발

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The tires which contact with the road are important parts to determine the vehicle behavior. Recently, the studies which want to increase the vehicle safety by observing the tire strains containing additional information about vehicle are in progress actively. This system called the intelligent tire system. For developing the whole intelligent tire system, the stain sensor which can measure the strains of tire has to be developed. However, there is no sensor to measure the strains of tire yet by reasons of adhesion of sensor and lack of reliability. In this study, strains of tire were estimated using the tire Finite Elements Model. And the optimized model is made to calculate the strains by converging test. The validation test was also conducted to verify the tire FE model. Using the tire FE model, the shapes of strains can be estimated in each traveling events. In this research, I suggest the method to develop the simplified analytical tire model to estimate the tire strain in real time. The simplified analytical tire strain model can be used in vehicle simulation replaced with real tire system and be the as comparison data of real tire sensor. To develop the model the standardized shape of tire strains were established refer to the database of tire strains at first. The target strains are lateral strains at each location of tire sensors on straight rolling condition. The standardized shape of tire strains can be determined by few decisive parameters (offset, compression peak, tension peaks) which are extracted from the database. For making the tire strains model two steps are performed. The first step is developing the neural network model to estimate the decisive parameters which determined the standardized shape of tire strains. By the cross-validation the number of hidden layers and the hidden neurons are decided. In the second step, the whole strains are printed with rotation angles by the piecewise polynomials curve. In this step govern equations of tire...
Yoon, Yong-Sanresearcher윤용산researcher
한국과학기술원 : 기계공학전공,
Issue Date
467566/325007  / 020093083

학위논문(석사) - 한국과학기술원 : 기계공학전공, 2011.2, [ vi, 56 p. ]


Neural network model; Finite Element Analysis; Tire model; Intelligent tire system; Piecewise polynomials curve fitting; 구분 다항식 근사법; 신경망 모델; 유한 요소 해석; 타이어 모델; 인텔리전트 타이어 시스템

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