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Wonsik Choi(최원식),Pandu Sandi Pratama(프라타마 판두 산디),Destiani Supeno(수페노 데스티아니),Jaeyoung Byun(변재영),Ensuk Lee(이은숙),Jiung Yang(양지웅),Dimas Harris Sean Keefe(키프 디마스 하리스 신),Yeonho Jeon(전연호),Sungwon Chung(정성원) 한국산업융합학회 2018 한국산업융합학회 논문집 Vol.21 No.5
In this research, tricycle vehicle simulation based on multi-body environment has been introduced. Mathematical model of tricycle vehicle was developed. In this research the left and right wheel speed are calculated based on the rear steering angle and velocity. The kinematic model for the three - wheel drive system was completed and the results were analyzed using the actual vehicle drawings. Through simulink vehicle performance on linear and rotation movement were simulated. Using the mathematical model the control system can be applied directly to the tricycle vehicle. The simulation result shows that the proposed vehicle model is successfully represent the movement characteristics of the real vehicle. This model assists the vehicle developer to create the controller and understand the vehicle during the development process.
Wonsik Choi(최원식),Pandu Sandi Pratama(프라타마 판두 산디),Destiani Supeno(수페노 데스티아니),Jaeyoung Byun(변재영),Ensuk Lee(이은숙),Jihee Woo(우지희),Jiung Yang(양지웅),Dimas Harris Sean Keefe(키프 디마스 하리스 신),Maynanda Brigita Chry 한국산업융합학회 2018 한국산업융합학회 논문집 Vol.21 No.5
In this research, the effect of normal load, sliding velocity, and texture density on thefriction coefficient of surfaces micro-textured on AISI 4140 under paraffin oil lubrication were investigated. The predicted tribological behavior by numerical calculation can be serves as guidance for the designer during the machine development stage. Therefore, in this research friction coefficient prediction model based on response surface methodology (RSM), support vector machine (SVM), and artificial neural network (ANN) were developed. The experimental result shows that the variation of load, speed and texture density were influence the friction coefficient. The RSM, ANN and SVM model was successfully developed based on the experimental data. The ANN model can effectively predict the tribological characteristics of micro-textured AISI 4140 in paraffin oil lubrication condition compare to RSM and SVM.