A Study on Terrain-Surface Modeling and Searching Algorithms for Real-time Simulation of Off-Road Vehicles

Summary Terrain surfaces have to be modeled in very detail and wheel-surface contacting geometry must be well defined in order to obtain proper ground-reaction and friction forces for realistic simulation of off-road vehicles. Delaunay triangulation is one of the most widely used methods in modeling 3-dimensional terrain surfaces, and the T-search is a relevant algorithm for searching resulting triangular polygons. The T-search method searches polygons in a successive order and may not allow real-time computation of off-road vehicle dynamics if the terrain is modeled with many polygons, depending on the computer performance used in the simulation. In order to accelerate the searching speed of the T-search, a terrain database of triangular polygons is modeled in multi-levels by adopting the LOD (Level of Detail) method used in real-time computer graphics. Simulation results show that the new LOD-search is effective in shortening the required computing time. The LOD-search can be even further accelerated by introducing the NN (Neural Network) algorithm, in the cases where a appropriate range of moving paths can be predicted by cultural or geographical or empirical information of the simulated terrain, such as lakes, houses, etc. Numerical tests show that LOD-NN search almost doubles the speed of the original T-search.     

Cooling Efficiency According to Shape Changes to the Straight Ventilation Hole in Carbon-Ceramic Brake Disks

In this study, in order to examine the cooling efficiency of a carbon-ceramic brake disk, the temperature distribution of the disk, depending on the AMS (Auto-Motor-Sport) Fade mode, was analyzed using a numerical method. Two brake disks with different straight ventilation hole shapes were considered. The ventilation holes configuration was changed from base models in order to find a higher cooling efficiency disk design. In the Model A disk, the mean temperatures of the mid-plane and the entire disk, at the AMS Fade mode end time decreased 1.9 oC and 3 oC, hole length respectively. This was done by decreasing the length of the a2 hole from 94 mm to 59 mm. When a₂ hole length was increased from 94 mm to 128 mm, the mean temperature of the entire disk and the disk mid-plane increased 3.7 oC and 16.2 oC, respectively. This was due to the increased affined air stagnation in the disk. In the Model B disk, after removing stagnation region of the b₂ hole, the hole diameter expanded from 13 mm to 17.6 mm. As a result, the mean temperature of the entre disk and the mid-plane decreased 2.8 oC and 18.7 oC, respectively, (compared to the base model). As a result, increasing the surface area of the ventilation holes gave a higher cooling efficiency.     

Semi-Active Suspension with Preview Using a Frequency-Shaped Performance Index

The objective of this study is to develop a control law for a semi-active suspension for the purpose of ride quality improvement. The semi-active control law is determined by reproducing the control force of an optimally controlled active suspension while suppressing its damping coefficient variation. The performance index of the optimal control for the active suspension is modified to include frequency-shaping by use of Parseval's theorem, which allows us to de-emphasize the effects of particular variables over specific frequency bands.

Through the numerical simulations, it was found that the semi-active suspension may reduce the vertical acceleration of the driver's seat and the sprung mass motions significantly. The road-holding and tire deflections were not affected much.     

Design of a signal transducer for direct conversion of wheel linear accelerations into tire lateral forces

This paper describes a design of a real-time conversion system of wheel linear accelerations into tire lateral forces. Though the tire lateral forces are important elements for analyzing vehicle dynamic control performances, they cannot be easily measured in real-time owing to the non-linearities of tire dynamics, friction, and slippage on road. In this paper, we propose a practical direct method using wheel linear accelerations in order to estimate tire lateral forces transmitted into the vehicle in real-time. A simplified vehicle model based on force-acceleration analysis is proposed to assure the real-time performance. The acceleration values are obtained using three-axis accelerometers attached on each wheel location. For conditioning and rectifying the acceleration signals, a signal transducer is designed using a digital filter. And in order to investigate the feasibility and real-time performance, a prototype of signal transducer is fabricated using a digital signal processor. The experimental results and performance are validated with the road test results using six-component wheel force transducers.     

Fuel consumption parameters for realizing and verifying fuel consumption prospect algorithm of vehicle driving route information system

Emissions of CO₂, as the main component of greenhouse gases, and high fuel consumption rates are worldwide problems. To solve them, most car manufacturers have concentrated on developing various techniques to improve the efficiencies of engines and transmissions and ECO-ROUTEs to meet environmental regulations. In this study, an algorithm for determining routes that cause the least fuel consumption was developed. The core of this algorithm is a specific EEC (energy efficiency constant) map containing logic that is able to predict fuel consumption. The accuracy of the algorithm was confirmed by vehicle tests for various driving patterns. Parameters affecting vehicle fuel economy were studied and verified. Improvement in the accuracy of this algorithm was confirmed by applying these parameters to ECO-ROUTE logic.     

Numerical study to evaluate the characteristics Of HVAC-related Parameters to reduce CO<Subscript>2</Subscript> concentrations in cars

Today, as people are spending increasing amounts of time in their cars, they have come to recognize that the car should function as a “residential” space. An eco-friendly indoor environment that provides comfort in terms of visual, tactile, and auditory senses is needed for the driver and the passengers. The quality of the car’s indoor environment was evaluated on various factors, such as indoor thermal comfort, indoor air quality, smell, and noise. For the indoor air quality, the typical pollutants that degrade the air quality are CO₂, volatile organic compounds, and exhaust gases. Especially, CO₂ has a direct relationship with drowsy driving which leads to traffic accidents. There have been many experimental and analytical studies to reduce the level of CO₂ in a short time, but analyses of parameters that affect indoor CO₂ concentration are insufficient and comprehensive standards for evaluating the car indoor CO₂ concentration do not yet exist. In this study, several parameters were selected that can influence the reduction rate of CO₂ concentration, and a series of computational analyses were conducted to study the results of these parameters in CO₂ reduction. Based on this study, a prediction equation for CO₂ concentration was derived. For this, a general full factorial design was used to evaluate the CO₂ reduction characteristic based on various parameters (ventilation mode, boarding condition, vent angle, mass flow rate, and operation mode), and then their effects were analyzed to obtain an evaluation database of indoor air quality. From that, a prediction equation was derived to estimate the indoor air quality, enabling us to evaluate the CO₂ concentration quickly that actually influences the human body without carrying out time-consuming CFD analyses for CO₂ concentration. This study will be useful in designing HVAC systems and establishing the control logic for effective improvement of the car’s indoor air quality in the future.     

Optimal solution to the vehicle routing problem by adopting a meta-heuristic algorithm

The delivery service provided by large-scale retailers continues to grow as online sales occupy an increasingly large share of the market. This study aims to tease out efficient vehicle scheduling times as well as optimal delivery routes by applying meta-heuristic algorithms. Monthly data on existing routes were obtained from a branch of Korea’s leading large-scale online retailer. The first task was to examine the status of existing routes by comparing delivery routes created using Dijkstra’s algorithm with existing delivery routes and their vehicle scheduling. The second task was to identify optimal delivery routes through a comparative analysis of the genetic algorithm and Tabu search algorithm, known for its superior applicability amongst other meta-heuristic algorithms. These findings demonstrate that the optimal vehicle routing problem not only has the potential to reduce distribution costs for operators and expedite delivery for consumers, but also the added social benefit of reduced carbon emissions.     

Activity space estimation with longitudinal observations of social media data

In this paper, we demonstrate the use of an inexpensive and easy-to-collect long-term dataset to address the problems caused by basing activity space studies off short-term data. In total, we use 63,114 geo-tagged tweets from 116 unique users to create individuals’ activity spaces based on minimum bounding geometry (convex hull). By using polygon density maps of activity space, we found clear differences between weekday and weekend activity spaces, and were able to observe the growth trajectory of activity space over 17 weeks. In order to reflect the heterogeneous nature of spatial behavior and tweeting habits, we used Latent Class Analysis twice. First, to identify five unique patterns of location-based activity spaces that are different in shape and anchoring. Second, we identify three unique growth trajectories. The comparison among these latent growth trajectories shows that in order to capture the extent of activity spaces we need long time periods for some individuals and shorter periods of observation for others. We also show that past studies using a single digit number of weeks may not be sufficient to capture individuals’ activity space. The major activity locations identified using a multilevel latent class model, do not appear to be statistically related to the growth patterns of Twitter users activity spaces. The evidence here shows Twitter data can be a valuable complementary source of information for heterogeneity analysis in activity-based modeling and simulation.     

Manoeuvring characteristics of twin-rudder systems: rudder-hull interaction effect on the manoeuvrability of twin-rudder ships

With a recent increase in ship capacity and propulsion performance, a wide-beam ship fitted with a twin-rudder system has been adopted in many cases. However, to improve ship manoeuvring, it is still necessary to have a better understanding of rudder-hull interactions in twin-rudder ships. Captive model tests (oblique towing and circular motion test) as well as free-running tests with a single-propeller twin-rudder ship and a twin-propeller twin-rudder ship are carried out. The effect of drift angle on the rudder forces and some peculiar phenomena concerning rudder normal force for twin-rudder ships are evaluated. A method for estimating the hull-rudder interaction coefficients based on free-running experimental results is proposed.