• 한국자동차공학회논문집
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• 제8권4호
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• pp.121-129
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• 2000

this paper develops a computational model for the turning maneuver analysis of a cabover type heavy truck. The model having 42 degree-of-freedom is developed using ADAMS. Leaf springs used in the front and rear suspension systems are modeled by dividing it three links and joining them with joints. Force and displacement relationship showing nonlinear hysteric characteristics of the leaf spring is measured and modeled with an exponential function. A velocity and force relationship of a shock absorber is measured and modeled with a spline function. And a stabilizer bar is modeled using ADAMS beam element to consider a twisting and bending effect. To verify the developed model an actual vehicle test is performed in the double lane change course with 50kph and 60kph vehicle velocity. In the actual vehicle test lateral acceleration roll angle and yaw rate are measured, The tendency and peak-to-peak values of the actual vehicle test and simultion results are compared each other.

• 한국자동차공학회논문집
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• 제20권1호
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• pp.14-19
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• 2012

On-line and real-time information of the longitudinal velocity is the essential factor for the Advanced Vehicle Control Systems such as ABS(Anti-lock Brake System), TCS(Traction Control System), ESC (Electronic Stability Control) etc. However, the longitudinal velocity cannot be easily measured or calculated during braking maneuvering. A new algorithm is presented for the estimation of the longitudinal velocity with the measurements of the vehicle longitudinal/lateral acceleration, steering angle and yaw rate. The algorithm is designed utilizing the Extended Kalman Filter based on the 3 degree of freedom vehicle model. In order to compensate for the biased sensor signal on the inclined road, the inclined angle is also estimated. The performance of the proposed estimation algorithm is evaluated in field tests.

• 한국정밀공학회지
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• 제17권4호
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• pp.226-232
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• 2000

This paper develops a finite element model for studying the crashworthiness analysis of a mid-size truck. A simulation for a truck frontal crash to a rigid barrier using the model is performed with PAM-CRASH installed in super computer SP2. Full vehicle model is composed of 86467 shell elements, 165 beam elements and 98 bar elements, and 86769 nodes. The model uses four material model such as elastic, elastic-plastic(steel), rigid and elastic-plastic(rubber) material model which are in PAM-CRASH. Frame and suspension system are modeled with 28774 shell elements and 31412 nodes. Cab is modeled with 34680 shell elements and 57 beam elements, and 36254 nodes. Bumper is modeled with 2262 shell elements, and 2508 nodes. Axle, steering shaft, etc are modeled using beam or bar elements. Mounting parts are modeled using rigid bodies. Bodies are interconnected using nodal constrains or joint options. To verify the developed model, frontal crash test with 30mph velocity to a rigid barrier is carried out. In the crash test, vehicle pulse at lower part of b-pillar is measured, and deformed shapes of frame and driver seat area are photographed. Those measured vehicle pulse and photographed pictures are compared those from the simulation to verify the developed finite element model.

• 한국자동차공학회논문집
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• 제11권5호
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• pp.210-218
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• 2003

MDO (multidisciplinary design optimization) technology has been proposed and applied to solve large and complex optimization problems where multiple disciplinaries are involved. In this research. an MDO problem is defined for automobile design which has crashworthiness analyses. Crash model which are consisted of airbag, belt integrated seat (BIS), energy absorbing steering system .and safety belt is selected as a practical example for MDO application to vehicle system. Through disciplinary analysis, vehicle system is decomposed into structure subspace and occupant subspace, and coupling variables are identified. Before subspace optimization, values of coupling variables at given design point must be determined with system analysis. The system analysis in MDO is very important in that the coupling between disciplines can be temporary disconnected through the system analysis. As a result of system analysis, subspace optimizations are independently conducted. However, in vehicle crash, system analysis methods such as Newton method and fixed-point iteration can not be applied to one. Therefore, new system analysis algorithm is developed to apply to crashworthiness. It is conducted for system analysis to determine values of coupling variables. MDO algorithm which is applied to vehicle crash is MDOIS (Multidisciplinary Design Optimization Based on Independent Subspaces). Then, structure and occupant subspaces are independently optimized by using MDOIS.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집A
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• pp.764-769
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• 2001

Brake-induced vibrations of a vehicle such as brake judder are determined by the excitation of brake torque variations and by their transfer to the driver's contact points via suspension, body and steering system. The formation of brake torque variation is mainly determined by static and dynamic disk thickness variations. The vibration transfer from the excitation by brake torque variation to the perception by the driver depends on the kinematic and dynamic behaviour of the components in the transfer path. Optimization of the judder performance can be achieved either by minimizing the excitation or by reduction of the judder sensitivity of the vehicle. In this paper, the optimization process of a front rotor is suggested to reduce brake judder considering the cooling performance of the rotor, the judder sensitivity of the vehicle and durability of the rotor.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.110-113
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• 2006

This paper describes the development process of body and full vehicle for reduced idle vibration through the data level of frequency and sensitivity. The vibration mode map is used to separate body structure modes from resonance of engine idle nm and steering system. This paper describes the analysis approach process to reduce the variation of uncertainties for idle vibration performance at initial design stage. The robust design method is performed to increase the stabilization performance under vehicle vibration. It is used to predict the effects of the stiffness deviation according to the spot welding condition of the body structure. The tolerance associated with hood over slam bumper is analyzed for the quality deviation of the moving system in full vehicle. And the glass sealant stiffness and weight difference is considered for the deviation characteristic. The design guideline is suggested considering sensitivity about body and full vehicle by using mother car at initial design stage. It makes possible to design the good NVH performance and save vehicles to be used in tests. These improvements can lead to shortening the time needed to develop better vehicles.

• 한국군사과학기술학회지
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• 제18권1호
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• pp.8-14
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• 2015

Transmission of a tracked vehicle designed for multiple functions such as steering, gear-shifting, and braking is a core component of heavy vehicle to which the power is transferred based on combined technology of various gears, bearing, and fluid machineries. Robustness and durability of transmission, however, have been issued due to a large number of driving units and sub-components inside its body. Particularly, transmission housing is important structure which supports the transmission, and is made of aluminum alloy. Thus, structural robustness against such mechanical loading or vibration must be attained. Structural reliability evaluation through FEM analysis can save time and cost of the actual tests. In this study, structural evaluation is conducted on output housing of transmission, which is core component of tracked vehicle, using the simulation program. In addition, transmission dynamo test is performed to evaluate structural robustness of the output housing against the vibration which can be produced during the transmission operation.

• Journal of Electrical Engineering and Technology
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• 제8권4호
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• pp.899-910
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• 2013

This paper presents a novel lateral stability control system for electric vehicle based on sideslip angle estimation through Kalman filter using the integration of a single antenna GPS receiver and yaw rate sensor. Using multi-rate measurements including yaw rate and course angle, time-varying parameters disappear from the measurement equation of the proposed Kalman filter. Accurate sideslip angle estimation is achieved by treating the combination of model uncertainties and external disturbances as extended states. Active front steering and direct yaw moment are integrated to manipulate sideslip angle and yaw rate of the vehicle. Instead of decoupling control design method, a new control scheme, "two-input two-output controller", is proposed. The extended states are utilized for disturbance rejection that improves the robustness of lateral stability control system. The effectiveness of the proposed methods is verified by computer simulations and experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권12호
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• pp.5842-5861
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• 2019

A current autonomous vehicle determines its driving strategy by considering only external factors (Pedestrians, road conditions, etc.) without considering the interior condition of the vehicle. To solve the problem, this paper proposes "An Optimal Driving Support Strategy(ODSS) based on an Genetic Algorithm for Autonomous Vehicles" which determines the optimal strategy of an autonomous vehicle by analyzing not only the external factors, but also the internal factors of the vehicle(consumable conditions, RPM levels etc.). The proposed ODSS consists of 4 modules. The first module is a Data Communication Module (DCM) which converts CAN, FlexRay, and HSCAN messages of vehicles into WAVE messages and sends the converted messages to the Cloud and receives the analyzed result from the Cloud using V2X. The second module is a Data Management Module (DMM) that classifies the converted WAVE messages and stores the classified messages in a road state table, a sensor message table, and a vehicle state table. The third module is a Data Analysis Module (DAM) which learns a genetic algorithm using sensor data from vehicles stored in the cloud and determines the optimal driving strategy of an autonomous vehicle. The fourth module is a Data Visualization Module (DVM) which displays the optimal driving strategy and the current driving conditions on a vehicle monitor. This paper compared the DCM with existing vehicle gateways and the DAM with the MLP and RF neural network models to validate the ODSS. In the experiment, the DCM improved a loss rate approximately by 5%, compared with existing vehicle gateways. In addition, because the DAM improved computation time by 40% and 20% separately, compared with the MLP and RF, it determined RPM, speed, steering angle and lane changes faster than them.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.434-439
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• 1993

This paper present a sensor based obstacle avoidance method which is based on a VFH(Vector Field Histogram) method. The basic idea of obstacle avoidance is to find a minimum obstacle direction and distance. From the minimum sonar index and the target direction high level system determine steering angle of mobile robot. The sonar sensor system consists of 12 ultra sonic sensor, and each sensor have its direction and safety value. This method has advantage on calculation speed and small memory. This method is implemented on indoor autonomous vehicle'ALiVE-2'.