• 대한기계학회논문집A
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• 제24권7호
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• pp.1871-1877
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• 2000

Longitudinal and lateral forces acting at tire are known to be closely related to the tractive ability, braking characteristics, handling stability and maneuverability of ground vehicles. However, it is not feasible in the operating vehicles to measure the tire forces directly because of high cost of sensors, limitations in sensor technology, interference with the tire rotation and harsh environment. In this paper, in order to develop tire force monitoring system, a new vehicle dynamics monitoring model is proposed including the roll motion. Based on the monitoring model, tire force monitoring system is designed to estimate the lateral tire force acting at each tire. A newly proposed SKFMEC (Scaled Kalman Filter with Model Emr Compensator) method is developed utilizing the conventional EKF (Extended Kalman Filter) method. Tire force estimation performance of the SKFMEC method is evaluated in the Matlab simulations where true tire force data is generated from a 14 DOF vehicle model with a combined-slip Magic Formula tire model.

• 한국자동차공학회논문집
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• 제24권6호
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• pp.730-736
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• 2016

Recent research suggests the various applications of Model Predictive Control on vehicle systems. In numerous cases, nonlinear tire models such as the Magic Formula, which are highly complex and are more detailed than necessary, are used. This paper presents a nonlinear tire model that excludes the region of negative slope but expresses the nonlinear properties of tire well enough for tracking the lane of a racing course. The proposed inverse tire model can also be used to calculate the slip angle from the tire force. Thus, the model can be utilized to design the Model Predictive Controller.

• 자동차안전학회지
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• 제13권4호
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• pp.33-38
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• 2021

This paper presents a comparative study between the parameter-optimized Pacejka model and artificial neural network model for the tire force estimation. The two different approaches are investigated and compared in this study. First, offline optimization is conducted based on Pacejka Magic Formula model to determine the proper parameter set for the minimization of tire force error between the model and test data set. Second, deep neural network model is used to fit the model to the tire test data set. The actual tire forces are measured using MTS Flat-Track test platform and the measurements are used as the reference tire data set. The focus of this study is on the applicability of machine learning technique to tire force estimation. It is shown via the regression results that the deep neural network model is more effective in describing the tire force than the parameter-optimized Pacejka model.

• 한국자동차공학회논문집
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• 제24권5호
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• pp.581-587
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• 2016

Braking is a basic and an important safety feature for all vehicles, and the final braking performance of a vehicle is determined by the vehicle's ABS performance and tire performance. However, the combination of excellent ABS and tires will not always ensure good braking performance. This is due to the fact that tire performance has non-linearity and uncertainty in predicting the repeated increase and decrease of wheel slip when activating the ABS, thus increasing the uncertainty of tire performance prediction. Furthermore, existing studies predicted braking performance after using an ABS that used a wheel slip control as a controller, which was different from an actual vehicle's ABS that controlled angular acceleration, therefore causing a decrease in the prediction accuracy of the braking performance. This paper reverse-designed the ABS that controlled angular acceleration based on the information on brake pressure, etc., which were obtained from vehicle tests, and established a braking performance prediction analysis model by combining a multi-body dynamics(MBD) vehicle model and a magic formula(MF) tire model. The established analysis model was verified after comparing it with the results of the braking tests of an actual vehicle. Using this analysis model, this study analyzed the braking effect by vehicle factor, and finally designed a tire that had optimized braking performance. As a result of this study, it was possible to design the MF tire model whose braking performance improved by 9.2 %.

• 비교문화연구
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• 제26권
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• pp.321-351
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• 2012

This paper attempts to clarify the similarity found in Seo Jungjoo's two books of poems, Seo Jungjoo Shiseon and Shillacho, and thereby to establish the continuity between Seo's early poetry and his mid-period poetry. This attempt arises from the realization that unfamiliar poetic material, background, and narration are merely surface features, and that in fact his early concerns nevertheless persist in terms of his poetic imagination and his Weltanschauung. Furthermore, this continuity seems to originate from shamanistic spiritual chaos that is consubstantially interrelated with the spirit of his deceased lover. After chaos and confusion subsided, the poet's endeavor to discover the lineal origin of his personal shamanism shows itself in Seo Jungjoo Shiseon, and we witness the embodiment of such endeavor in Shillacho. His interest in the skies as it is expressed in my poem, and Shilla as it is intimated by Gwanghwamun are sublimated in saso yeonjag and the words of Queen Seondeog into shamanic wisdom that served as the norm for both spiritual life and physical life in ancient times, and the wisdom is carried on further into the present in Seo's own times. Moreover, the star and the bell sound that were presented as signs of desirable Weltanschauung in Sangrigwawon are transformed into the symbols of shamanic wisdom, and into the inner magic formula that contributes to achieving the wisdom. This analysis offers as its result the evidence embedded in his poems that shows, first, that the two books correspond to merely two separate stages of his poetic concern, and second, that his early poetic concern persists, though transformed through a peculiar manner, into his mid-period poems.