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In this study, we developed the defrost performance evaluation technology using the multi-objective optimization method based on the CFD. The defrosting is one of the key factors to ensure the drivers’ safety using the forced flow having proper temperature from HVAC during drive. There are many factors affecting the defrost performance, but the configurations of guide-vane and discharge angles in the center DEF(defrosting) duct section which are main design factors of the defrost performance in automotive, so these were set to the design parameters for this study. For the shape-optimization study, the discharge mass flow rate from the HVAC which is transferred to the windshield and the discharge areas in the center defrost duct were set to the response parameters. And then, the standard deviation value of mass flow rate on the selected discharge areas checking the uniformity of discharge flow was set to the objective function to find the optimal design.

This paper describes a lateral disturbance estimator for an application to a Motor Driven Power Steering (MDPS)-based driving assistant system. A vehicle motion can be disturbed laterally by wind force or load from bank angle acting on the vehicle in the lateral direction. An MDPS-based driving assistant system can be used to reduce steering effort of a human driver in a driving situation with lateral disturbance. In designing the MDPS-based driving assistant system, the lateral wind disturbance should be estimated to determine an assistant torque. An estimator for the vehicle lateral disturbance estimation has been developed. The proposed estimator consists of two parts: a tire self-aligning torque estimator and the lateral disturbance estimator. The lateral disturbance estimator has been designed on the basis of a 2-DOF bicycle model with available sensor signals from the MDPS module. A numerical simulation has been conducted in order to evaluate the proposed estimator.

This paper is intended to find out the optimized restraint system for various crash conditions and to analyze the characteristics of those conditions numerically. 40km/h FF (Full Frontal crash), 56km/h FF and 64km/h ODB (Offset Deformable Barrier crash) conditions have been considered with 5th%ile female, 50th%ile male and 95th%ile male dummies on driver side. The vehicle lay out and crash pulses came from a compact passenger car. The restraint system was focused on the driver side airbag and seat belt. MADYMO 3D was used in this study for simulation.

As occupant injuries induced by airbag deployment became a critical issue, revisions to FMVSS 208 were made to mandate the adoption of advanced airbag which can protect occupants of varying statures. As a result, OCS (Occupant Classification System) has become an important part of advanced airbag technologies. In this paper, we review existing OCS technologies briefly and list details of development issues and solutions for weight-based OCS. As an effort to reduce cost and optimize performance for the semi-LRD (Low Risk Deployment) airbag system, a study on reducing the number of sensors from 4 to 2 for the current system utilizing DFSS methodology is provided and discussed.

The integrated control system of Electronic Stability Control (ESC) and Motor-Driven Power Steering (MDPS) improves vehicle performance and extends functions via CAN network without any hardware modification. Although the ESC and MDPS integrated system does not improve vehicle behavior directly, it can inspire drivers to steer to the right direction by changing steering torque assistance characteristics. There are two different ways to control both ESC and MDPS systems: Top-down and Parallel control mode. First, the Top-down control mode, which is already widely used on the market, imposes ESC on the additional functions of ESC+MDPS integrated system. On the contrary, the Parallel control mode distributes the functions to ESC and MDPS, therefore each system does their own role and cooperates on special events. In this study, the parallel control mode controller is proposed and compared with the Top-down control mode.

Drivers continually require steering performance improvement, particularly in the area of feedback from the road. In this study, we develop a new electrically-assisted steering logic by 1) analyzing existing steering systems to determine key factors, 2) modeling an ideal steering system from which to obtain a desirable driver torque, 3) developing a rack force observer to faithfully represent road information and 4) building a feedback compensator to track the tuned torque. In general, the estimator uses the driver torque, assist torque and other steering system signals. However, the friction of the steering system is difficult to estimate accurately. At high speed, where steering feeling is very important, greater friction results in increased error. In order to solve this problem, we design two estimators generated from a vehicle model and a steering system model. The observer that uses two estimators can reflect various operating conditions by using the strengths of each method.

A Head-Up Display (HUD) is electrical device that provides virtual images in front of driver. Virtual images are consists of various driving information. Because HUD uses optical system there exist image distortions with respect to image height and driver’s eye position. Image warping is image correction method that makes a geometrical change on image to minimize image distortions. In this paper to minimize image distortions, we use optical data driven warping matrix for each image height. But even though we applied data driven warping matrix, image distortions occur due to assemble and manufacturing tolerances when HUD is built. In this paper, we also suggest pre-warping method to minimize image distortions considering tolerances. We simulated 3 compensation functions to get rid of image distortions from the tolerances. By using proposed pre-warping method we could reduce maximum x, y distance by 31.5%, 39% and average distance by 32.2%, 27.9% of distortions.