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This paper presents a control methodology to maintain vehicle cabin air quality within desirable levels, giving particular attention to gaseous contaminants carbon dioxide (CO2) and carbon monoxide (CO). The CO2 is generated by the occupant exhalation while the CO is assumed to be ingested with the incoming outside air. The system is able to detect and improve cabin air quality by controlling the recirculation flap of the ventilation system to control the amount of outside air intake. The methodology is demonstrated in the laboratory using controlled experiments with a production level automotive HVAC module. The results indicated that the designed control system can work automatically and control the CO and CO2 gas concentrations within acceptable levels when operating in an environment of near zero ppm CO and 600 ppm CO2 concentrations, respectively.

Drifting, a very popular challenge in the recent motorsport, is a cornering technique with large angle of sideslip when rear tires encounter with combined slip over the linear region of the slip-tire friction characteristic. Besides, this technique is frequently used by expert rally drivers in order to ensure that the vehicle will not understeer. In this work, steady state cornering of a RWD vehicle on plane, with constant speed, sideslip and radius of curvature, was simplified via the single track vehicle model. In addition, BNP magic formula, along with MNC model, was used to estimate tire frictions. The computer program was developed, based on EOMs derived via body fixed coordinate, in order to calculate a suitable cornering speed and corresponding open-loop driving control inputs, steering angle and rear slip ratio, for a given radius of curvature and vehicle sideslip.

This paper presents the development and simulation results of dynamic model for electric Tuk-tuk that can be used to predict energy consumption in Bangkok driving condition by using MATLAB/Simulink. The major components of this model are battery, motor, controller, transmission and tractive effort. The model consider in dynamics of motor and battery. The driving cycle which is employed is consist of Bangkok driving cycle (BDC). The simulation results were verified with collected data from real condition driving test. It shown that the simulation results of the model can represent accurately the actual electric Tuk-tuk behavior during both steady state and transient and can indicate the energy consumption from battery. The energy consumption required is 6.85 kWh with 20.04km distance along the urban Bangkok driving route before the battery cannot supply adequate power.

This paper presents a Tire-Suspension-Steering Hardware-In-the-Loop Simulator (HILS) system for using in a development of a student formula car suspension. The HILS system was modified from an existing Tire-Suspension-Steering Hardware-In-the-Loop Simulator developed in Chulalongkorn University. The system can be used to reduce the development time and cost when comparing to testing a real prototype car on a test track. Firstly, we designed and built the adjustable support for the student formula car suspension on the HILS such hat wheel parameters such as camber and toe can be adjusted. CATIA V5 was used to design and test the structural strength. On the other hand, the HILS system is used to simulate and test vehicle dynamics by replacing the front wheel of a bicycle model with a real student formula wheel and suspension. The wheel is running on a rotating drum whose speed and orientation can be controlled to simulate the car speed and the tire side slip angle.

The world is aging rapidly. Many countries can already be categorized as aging or aged societies while a few are becoming super-aged societies. In Thailand as well as in other countries, traffic accidents caused by elderly drivers will continue to rise as a significant percentage of elderly people still prefer to drive. Accidents may be prevented with driving tests and screening methods for elderly drivers. However, it is also necessary to understand the effect of aging on driving ability. With this understanding, driver training, driver assistant systems, and improvements on infrastructure may be designed accordingly. Among various physical changes, cognitive ability of the brain is one of the most significant factors affecting driving ability. In this paper, correlation between various cognitive functions of the brain and car following skill of drivers are considered.

The utility of energy efficiency and zero-emission of electric vehicles leads the way to electrify the urban public transport bus networks in many cities around the world. The purpose of this paper is to study the operational feasibility of transition the existing conventional combustion bus fleet to Electric bus fleet. The analysis is based on the data of the bus operation in Bangkok, Thailand. Traffic congestion as occurred in Bangkok is considered in the analysis. This research is focused on Fast charging technology of Electric vehicles. Instead of slow-charging overnight, Fast-charging is used during the regular layover time of the bus operation which is called Opportunity charging. The opportunity charging allows to extend the driving range of the electric buses which is a prominent problem of electric vehicles.

The road accident is major problem around the world and also in Thailand, The main cause is concerning the driving behavior e.g. uncarefulness, aggression, drowsiness and etc. Dangerous driving is categorized by means of lateral vehicle dynamics when the turning or lane changing is performed, and longitudinal one if the braking or rapid acceleration is occurred. For this reason, we developed the vehicle monitoring system based on novel consumer grade multi-satellite navigation receivers and proposed the lateral acceleration estimation from these data. The system were tested within controlled condition tested track. The multiple satellite system, GPS and multi-GNSS: GPS+Glonass and GPS+Beidou were tested and compared to the reference inertial measurement unit (IMU) As results, the maximum lateral acceleration in tested track were chosen and compared with reference IMU.

Drowsiness has been one of the major reasons of road fatality over a decade because the effect of drowsiness is trying to shut down both mind and body. That means drivers are unable to completely control the car while trapped in an unconscious state. It will lead to a several number of casualties on road. In this research, two sets of people, partial sleep-deprivation and non-sleep-deprivation, are tested on the driving simulator. Two methods were used in this study to identify driver drowsiness. First, driving behavior focusing on steering pattern. And secondly, vehicle offset from the lane center. The tests were carried out on the designed scenarios in the Driving Simulator. The scenarios are such as following straight lane with vehicle along the road, following curve lane without other cars, car following on a single lane and following straight lane without other cars. From the results, there are significant results that can roughly separate drowsy driver from regular driver.

Urban Mobility is one of the most critical issues at the present. Public transport in connection with feeder bus system is proposed to be one of the main solution. Chulalongkorn University has a fleet of electric feeder bus in operation for a few years now. The fleet service is, however, to be improved because of current limitations in battery energy capacity and long battery charging time. This paper aims to examine the total cost of ownership (TCO) of the electric feeder buses using various types of energy storage. The results on the sensitivity analysis highlight the major parameters that exert strong influence in the TCOs. The fast charging system using supercapacitor battery bus shows the lowest TCO for the present bus fleet. The travel distance (km/year) and operational years were illustrated to be the top two parameters that exert major influence towards the TCO.