• Journal of Korea Society of Industrial Information Systems
• /
• v.28 no.4
• /
• pp.35-43
• /
• 2023

In next-generation electric vehicles, research is being conducted on an in-wheel motor system that directly controls torque by each wheel to improve total cost and driving performance. Accordingly, in this paper, a study was conducted on an algorithm that distributes the torque applied to each wheel in a torque vectoring system applied to an in-wheel motor for driving an electric vehicle. In order to implement a vehicle model that applies actual vehicle characteristic parameters according to vehicle driving and steering, a simulation was conducted in the MATLAB Simulink environment, and it was confirmed that torque distribution was performed according to the proposed algorithm.

• Advances in materials Research
• /
• v.12 no.3
• /
• pp.227-242
• /
• 2023

Polyester composites play a vital role in civil engineering applications, especially in bridge and car park structures. Therefore, the addition of waste silica-based fillers will both improve the mechanical and durability performance of composites and produce an environmentally friendly material. In this study, the mechanical performance of polyester composites was investigated experimentally and numerically by adding micro and nano-sized silica-based fillers, marble powder, silica fume and nano-silica. 24 cubes for the compression test and 18 prisms for the flexural test were produced in six different groups containing 30% marble powder, 5% silica fume and 1% nano-silica by weight. SEM/EDS testing was used to investigate the distribution of filler particles in the matrix. Experimentally collected results were used to validate tests in the Abaqus software. Additionally, the Extended Finite Element Method (XFEM) was used to estimate the fracture process for the flexural test. The results show that the added silica fume, marble powder and nano silica improves the compressive strength of polyester composites by 32-38% and the flexural tensile strength by 10-60% compared to pure polyester composite. The numerically obtained results matched well with the experimental data, demonstrating the accuracy and feasibility of the calibrated finite element model.

• International Journal of Advanced Culture Technology
• /
• v.11 no.2
• /
• pp.330-344
• /
• 2023

This research report cuts across management sciences (market strategy entry mode development) and innovative technology (Electric Vehicle (EV)) alongside measures to submerge global warming. The development of a successful entry mode for the electric Vehicle into the African continent is the main objective of the study. The study focuses on an analysis of how electric car manufacturers can enter the African market in other to achieve global sustainability and social responsibility. The methodology is based on identifying the factors that affect the choice of an entry mode into international markets by multinational companies desiring to leverage their revenue through a foreign market. It also offered a quantitative approach that can support the economic and sustainability entry mode model for EVs and a qualitative approach of Porter's five forces analysis as an entry mode coaching tool for EVs. These proxies are used in quite a wide range of multivariate statistical methods (trend analysis, ratio, and probability, comparative t-test technique, auto-regression, and ordinary least square technique). The result acknowledges joint venture and setting of the plant (physical presents) as the optimal entry mode in African EV market. It requires the EV manufacturers a tire-free emission innovation technology in order to optimize the global sustainability initiative.

• Journal of the Ergonomics Society of Korea
• /
• v.35 no.5
• /
• pp.371-381
• /
• 2016

Objective:This study aims to evaluate the features of heart rate variability (HRV) and respiratory signals as indices for a driver's drowsiness and waking status in order to develop the classification model for a driver's drowsiness and waking status using those features. Background: Driver's drowsiness is one of the major causal factors for traffic accidents. This study hypothesized that the application of combined bio-signals to monitor the alertness level of drivers would improve the effectiveness of the classification techniques of driver's drowsiness. Method: The features of three heart rate variability (HRV) measurements including low frequency (LF), high frequency (HF), and LF/HF ratio and two respiratory measurements including peak and rate were acquired by the monotonous car driving simulation experiments using the photoplethysmogram (PPG) and respiration sensors. The experiments were repeated a total of 50 times on five healthy male participants in their 20s to 50s. The classification model was developed by selecting the optimal measurements, applying a binary logistic regression method and performing 3-fold cross validation. Results: The power of LF, HF, and LF/HF ratio, and the respiration peak of drowsiness status were reduced by 38%, 22%, 31%, and 7%, compared to those of waking status, while respiration rate was increased by 3%. The classification sensitivity of the model using both HRV and respiratory features (91.4%) was improved, compared to that of the model using only HRV feature (89.8%) and that using only respiratory feature (83.6%). Conclusion: This study suggests that the classification of driver's drowsiness and waking status may be improved by utilizing a combination of HRV and respiratory features. Application: The results of this study can be applied to the development of driver's drowsiness prevention systems.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.21 no.3
• /
• pp.419-432
• /
• 2019

Most of deep learning model training was proceeded by supervised learning, which is to train labeling data composed by inputs and corresponding outputs. Labeling data was directly generated manually, so labeling accuracy of data is relatively high. However, it requires heavy efforts in securing data because of cost and time. Additionally, the main goal of supervised learning is to improve detection performance for 'True Positive' data but not to reduce occurrence of 'False Positive' data. In this paper, the occurrence of unpredictable 'False Positive' appears by trained modes with labeling data and 'True Positive' data in monitoring of deep learning-based CCTV accident detection system, which is under operation at a tunnel monitoring center. Those types of 'False Positive' to 'fire' or 'person' objects were frequently taking place for lights of working vehicle, reflecting sunlight at tunnel entrance, long black feature which occurs to the part of lane or car, etc. To solve this problem, a deep learning model was developed by simultaneously training the 'False Positive' data generated in the field and the labeling data. As a result, in comparison with the model that was trained only by the existing labeling data, the re-inference performance with respect to the labeling data was improved. In addition, re-inference of the 'False Positive' data shows that the number of 'False Positive' for the persons were more reduced in case of training model including many 'False Positive' data. By training of the 'False Positive' data, the capability of field application of the deep learning model was improved automatically.

• Proceedings of the KSR Conference
• /
• 2011.05a
• /
• pp.680-689
• /
• 2011

A dynamic analysis procedure is developed to provide a comprehensive estimation of the dynamic response spectrum for locomotive's wheels running over a Pre-Stressed Concrete (PSC) box girder bridge on the Korea high speed railway. The wheel force spectrum with the bridge behavior are analyzed as the dynamic procedure for various running speeds (50~450km/h). The high-speed railway locomotive (KTX) is used as 38-degree of freedom system. Three displacements(vertical, lateral, and longitudinal) and three rotational components (pitching, rolling, and yawing). For one car-body and two bogies as well as five movements except pitching rotation components for four wheel axes forces are considered in the 38-degree of freedom model. Three dimensional frame element is used to model of the PSC box girder bridges, simply supported span length of 40m. The irregulation of rail-way is derived using the exponential spectrum density function under assumption of twelve level tracks conditions based on the normal probability procedure. The dynamic responses of bridge passing through the railway locomotive with high-speed analyzed by Newmark-${\beta}$ method and Runge-Kutta method are compared and contrasted considering the developed models of bridge, track and locomotive comprehensively. The dynamic analyses of wheel forces by Runge-Kutta method which are able to analyze the forces with high frequency running on the bridge and ground rail-way are conducted. Additionally, wheel forces spectrum and three rotational components of vehicle body for three typical running speeds is also presented.

• International Journal of Highway Engineering
• /
• v.18 no.6
• /
• pp.173-180
• /
• 2016

OBJECTIVES : Fixed roadside objects are a threat to drivers when their vehicles deviate from the road. Therefore, such roadside objects need to be suitably dealt with to decrease accidents. This study determines the factors affecting the severity of accidents because of fixed roadside objects. METHODS : This study analyzed the crash severity impact of fixed roadside objects by using ordered probit regression as the analysis methodology. In this research, data from 896 traffic accidents reported in the last three years were used. These accidents consisted of sole-car accidents, fixed roadside object accidents, and lane-departure accidents on the national highway of Korea. The accident severity was classified as light injury, severe injury, and death. The factors relating to the road and the driver were collected as independent variables. RESULTS : The result of the analysis showed that the variables of the crash severity impact are the collision location (left side), gender of the driver (female), alcohol use, collision facility (roadside trees, traffic signals, telephone poles), and type of road (rural segments). Additionally, the collision location (left side), gender of the driver (female), alcohol use, collision facility (street trees, traffic signals, telephone poles), and type of road (rural segments), in order of influence, were found to be the factors affecting the crash severity in accidents due to fixed roadside objects. CONCLUSIONS : An alternative solution is urgently required to reduce the crash severity in accidents due to fixed roadside objects. Such a solution can consider the appropriate places to install breakaway devices and energy-absorbing systems.

• Journal of Applied Reliability
• /
• v.15 no.4
• /
• pp.241-247
• /
• 2015

Purpose : The demand for higher fuel economy vehicles has helped develop fuel-efficient vehicles such as a CVVL called continuous variable valve lift. Existing CVVL has been applying DC type motor to control intake valve, but recently some car parts manufacturers have been developing a BLDC type CVVL motor for improvements of endurance performance. The purpose of this study is to find the potential failure mechanism of the CVVL BLDC moto in early stage of development based on the design properties and design the accelerated life test model. Methods : CVVL BLDC is consist of brushs, coil, magnetic, PCB, bearing and so on. Each component has a latent failure mechanism caused by temperature, humidity, vibration. By analysis result of the failure mechanism, thermal fatigue is the most important factor of a durability of CVVL BLDC motor. So, we designed a new accelerated life test model for guarantee of the CVVL BLDC motor. Results : A crack occurred on via hole in test using the conditions we designed, so we did change the design to avoid this failure. The via hole dimension is changed a little larger, as a result we achieve improvements in reliability of the CVVL BLDC motor. By applying various kinds and extreme level of stresses, we can find the operating limits of products. Conclusion : In thesis, We analyzed the failure mechanism of CVVL BLDC and designed an accelerated life test method to give a guarantee for reliability. Based on the test results, we could improve the reliability of developments by change of design.

• Archives of design research
• /
• v.16 no.3
• /
• pp.91-100
• /
• 2003

The Korea's automotive industry have been achieved remarkable growth with many original models for over 28 years since the first original model Pony had developed. And most of the early models were licensed from the other country's makers. Now it is independent with our own technologies and designs, and the automobile is one of the major exporting products of Korea. In the early times the basic design concept of a passenger car didn't reflect the characteristics of the way of domestic life, but today's Korean developed cars have speciffic characters those are distinguished to others not only in the overall body shape but also in the package layout. And it is considered that the Korean cars would have different characteristics to the others in the future. These changes would come from the ways of life of the nations characteristics and they would influence to technologies of development. And the influence would be resulted as another type of sedan which has much differences to the current sedans. The main elements and the reasons for the 'post sedan' have been observed to specify the characters of the future Korean sedan in this research.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.18 no.5
• /
• pp.115-123
• /
• 2010

Cool-down performance after soaking is important because it affects passenger's thermal comfort. The cooling capacity of HVAC system determines initial cool down performance in most cases, the performance is also affected by location, and shape of panel vent, indoor seat arrangement. Therefore, optimal indoor designs are required in developing a new car. In this paper, initial cool down performance is predicted by CFD(computational fluid dynamics) analysis. Experimental time-averaging temperature data are used as inlet boundary condition. For more reliable analysis, real vehicle model and human FE model are used in grid generation procedure. Thermal and aerodynamic characteristics on re-circulation cool vent mode are investigated using CFX 12.0. Thermal comfort represented by PMV(predicted mean vote) is evaluated using acquired numerical data. Temperature and velocity fields show that flow in passenger's compartment after soaking is considerably unstable at the view point of thermodynamics. Volume-averaged temperature is decreased exponentially during overall cool down process. However, temperature monitored at different 16 spots in CFX-Solver shows local variation in head, chest, knee, foot. The cooling speed at the head and chest nearby panel vent are relatively faster than at the knee and foot. Horizontal temperature contour shows asymmetric distribution because of the location of exhaust vent. By evaluating the passenger's thermal comfort, slowest cooling region is found at the driver's seat.