Digital human body model for seat comfort simulation

Using the recent anthropometry of the North American population, human body models were developed for seat comfort simulation. The external geometry of the models was acquired from the three-dimensional whole body laser scan of recruited volunteers in a driving position. The selection criteria for volunteers with standard size and shape were derived from a statistical factor analysis of the Size USA database. As a practical application of the model in a design process, comfortable driving postures were constructed by adopting the cascade prediction model (CPM), which takes into account both interior package layout and the driver’s anthropometry. The detail modeling process of finite element modeling and its validation results against volunteer measurements are introduced.     

Effects of end coils on the natural frequency of automotive engine valve springs

In this paper, we present a method for estimating the natural frequencies of various engine valve springs such as constant pitch, two-step variable pitch, three-step variable pitch, and progressive springs. Since a valve spring’s surging amplitude is magnified when the spring’s natural frequency coincides with the frequency of the cam profile harmonic components, estimating the natural frequency of the spring is the first step in predicting valve spring surging phenomena. A new method for calculating the valve spring’s natural frequency is proposed in this paper that considers the end coil effect. This method predicts not only the natural frequency of a helical spring at a fixed number of active turns, but also the change in the natural frequency as the spring is compressed. The experimental results demonstrate that nonlinear characteristics of engine valve springs can be predicted from the given initial pitch curves.     

Prediction of vibrating forces on meshing gears for a gear rattle using a new multi-body dynamic model

An efficient multibody dynamic model was developed to predict the vibrating transmitted gear forces of loaded and unloaded pairs of helical gears simultaneously at all speeds. The model can also calculate the bearing forces of a manual transmission that, in turn, may be converted to rattling noises. The bending of meshing gear teeth and torsional flexibility of transmission shafts were considered and embodied effectively in the multibody dynamic model by calculating the tooth bending stiffness and adding a torsion spring on a shaft section between two gears, respectively. The reactive forces on teeth and bearings were calculated and compared using three different models that were developed for this study — an equivalent model, a rigid-body model, and a frequency-based model. The equivalent model took only 58% computation time, compared to the frequency-based method, even though the two showed very similar results.     

Improved method for analyzing automotive transmission parts (shaft/gear) manufactured using the warm shrink fitting process

There are three sub-processes associated with the assembly of an automobile transmission: heat fitting, shrink fitting, and combination fitting. In the heat fitting stage, the gear is heated to a specified temperature and then squeezed towards the outer diameter of the shaft. The stress of the heat-fitted gear depends on the yield strength of the gear. In the shrink fitting process, the gear is typically squeezed towards the shaft at room temperature using a press. An alternate method, known as warm shrink fitting, heats the already warm gear and safely squeezes it toward the shaft. The warm shrink fitting process for automobile transmission parts is becoming more commonplace, but the additional heating can cause the dimensions of the assembled parts (shaft/gear) to change with respect to both the outer diameter and the profile of the gear. As a result, there may be additional noise and vibration between gears. To address these problems, we analyzed the warm shrink fitting process using the contact pressure caused by fitting interference between the outer diameter of the shaft and the inner diameter of the gear, fitting temperature, and the profile tolerance of the gear as design parameters. In this study, a closed form equation for predicting the contact pressure and fitting load is proposed. This equation is used to develop an optimization technique for the warm shrink fitting process. The reliability of the model was verified using experimental results measured in the field, and FEM with thermal-structural coupled field analysis. Actual loads measured in the field showed good agreement with the results obtained by theoretical and finite element analysis, and expansion of the outer diameters of the gears agreed well with the results.     

Motor control of input-split hybrid electric vehicles

A motor control strategy for an input-split hybrid electric vehicle (HEV) is proposed. From a power characteristic analysis, it is found that the powertrain efficiency decreases for speed ratios at which power circulation occurs. Using dynamic models of an input-split HEV powertrain, a motor-generator control algorithm for obtaining high system efficiency is designed by inversion-based control. The performance of the control algorithm is evaluated by the simulator which is developed based on PSAT, and simulation results are compared with the test results. It is found that, even if the engine thermal efficiency is sacrificed by moving the engine operation point from the OOL for the control strategy, improved overall powertrain system efficiency can be achieved by the engine operation that gives a relatively high efficiency from the viewpoint of the overall powertrain efficiency. The control algorithm developed can be used in design of future electric vehicles.     

Sensor fusion-based lane detection for LKS+ACC system

This paper discusses the market trends and advantages of a safety system integrating LKS (Lane Keeping System) and ACC (Adaptive Cruise Control), referred to as the LKS+ACC system, and proposes a method utilizing the range data from ACC for the sake of lane detection. The overall structure of lane detection is the same as the conventional method using monocular vision: EDF (Edge Distribution Function)-based initialization, sub-ROI (Region Of Interest) for left/right and distance-based layers, steerable filter-based feature extraction, and model fitting in each sub-ROI. The proposed method adds only the system for confining lane detection ROI to free space that is established by range data. Experimental results indicate that such a simple adaptive ROI can overcome occlusion of lane markings and disturbance of neighboring vehicles.     

Driving environment assessment using fusion of in- and out-of-vehicle vision systems

Because the overall driving environment consists of a complex combination of the traffic Environment, Vehicle, and Driver (EVD), Advanced Driver Assistance Systems (ADAS) must consider not only events from each component of the EVD but also the interactions between them. Although previous researchers focused on the fusion of the states from the EVD (EVD states), they estimated and fused the simple EVD states for a single function system such as the lane change intent analysis. To overcome the current limitations, first, this paper defines the EVD states as driver’s gazing region, time to lane crossing, and time to collision. These states are estimated by enhanced detection and tracking methods from in- and out-of-vehicle vision systems. Second, it proposes a long-term prediction method of the EVD states using a time delayed neural network to fuse these states and a fuzzy inference system to assess the driving situation. When tested with real driving data, our system reduced false environment assessments and provided accurate lane departure, vehicle collision, and visual inattention warning signals.     

Development of an IoT-based container tracking system for China’s Belt and Road (B&R) initiative

To ensure the successful implementation of China’s Belt and Road (B&R) Initiative, it is essential to enable the real-time monitoring of containers’ locations, prevent theft during cargo delivery, ensure more efficient logistics management and reduce carbon emissions. For this, it is vital to have an economic and effective system to track and control containers across multiple countries. However, this requirement cannot be met by today’s container tracking systems because they are either limited within the borders of each country or expensive to employ internationally. This study thus presents a framework for an IoT-based container tracking system that enables users not only to grasp the international flow of container movement with one check but also to achieve smooth cross-border procedures. To verify the system’s performance, an empirical test was made for an actual container shipped from Korea to Poland. The test results showed that the system could successfully track the location of the container in real time across international borders. Last, this study discusses the policy development and international cooperation that should take place to enable the introduction of this container tracking system.     

Switching service types for multi-region bus systems

Conventional fixed-route bus services are generally preferred to flexible-route services at high demand densities, and vice versa. This paper formulates the problem of integrating conventional and flexible services that connect a main terminal to multiple local regions over multiple time periods. The system’s vehicle size, route spacing (for conventional services), service area (for flexible services), headways and fleet sizes are jointly optimized to minimize the sum of supplier costs and user costs. The route spacing for conventional bus services and service area for flexible bus services are also optimized for each region. The proposed solution method, which uses a genetic algorithm and analytic optimization, finds good solutions quickly. Numerical examples and sensitivity analyses confirm that the single fleet variable-type bus service may outperform either the single fleet conventional bus service or the single fleet flexible bus service when demand densities vary substantially among regions and time periods.     

An analysis of Metro ridership at the station-to-station level in Seoul

While most aggregate studies of transit ridership are conducted at either the stop or the route level, the present study focused on factors affecting Metro ridership in the Seoul metropolitan area at the station-to-station level. The station-to-station analysis made it possible to distinguish the effect of origin factors on Metro ridership from that of destination factors and to cut down the errors caused by the aggregation of travel impedance-related variables. After adopting two types of direct-demand patronage forecasting models, the multiplicative model and the Poisson regression model, the former was found to be superior to the latter because it clearly identified the negative influences of competing modes on Metro ridership. Such results are rarely found with aggregate level analyses. Moreover, the importance of built environment in explaining Metro demand was confirmed by separating built environment variables for origin and destination stations and by differentiating ridership by the time of day. For morning peak hours, the population-related variables of the origin stations played a key role in accounting for Metro ridership, while employment-related variables prevailed in destination stations. In evening peak hours, both employment- and population-related variables were significant in accounting for the Metro ridership at the destination station. This showed that a significant number of people in the Seoul metropolitan area appear to take various non-home-based trips after work, which is consistent with the results from direct household travel surveys.