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In order to understand the automotive PEM fuel cell system, mathematical system modeling is conducted and the model is implemented and simulated by using the Matlab®/Simulink®. The components such as fuel cell stack, air supplier, and radiator are modeled individually and integrated into a system level. The PEM fuel cell system operation control includes thermal management, air supply control, hydrogen supply control, fuel cell stack protection control, and load following control. In the thermal management, the inlet and outlet temperature of coolant are controlled to operate the fuel cell stack in desired temperature range and to prevent flooding inside the fuel cell stack. In air supply control and hydrogen supply control, the flow rates of air and hydrogen are controlled not to starve the fuel cell stack according to the output current. A control structure for the system is developed and confirmed by using the developed simulation model.

For a complete automotive HVAC system, it is desirable to keep good air quality control for the interior vehicle cabin. This experimental study for evaluating the CO2 concentration levels in a vehicle cabin was done on the roads in South Korea. Increasing levels of CO2 can cause a passenger to become tired, sleepy and cause headaches or discomfort. The study results shows that CO2 and fine dust concentration is a result of the number of passengers,_driving condition and HVAC user settings. The result from this investigation can be used to establish a development guide for air quality in a vehicle cabin.

To predict structure-borne interior noise using CAE simulation, it is important to establish a model for both the noise and vibration transfer path, as well as the excitation source. In the passenger vehicle, powertrain and road induced loads are major input sources for NVH. This paper describes a process to simulate the structure-borne road noise to 150Hz. A measured road surface is used for input for the simulation. Road surface data, in the form of height vs. distance, is converted to enforced motions at the tire patch in the frequency domain for input to the vehicle system model. The input loads are validated by the comparison of wheel hub excursions. The ability of the CAE simulation model to predict interior acoustic responses is shown by the comparison of the simulation results with measured vehicle interior responses.

The mobility technique is used to analyze the transfer functions of road noise between the suspension and the body structure. In the previous analyses, the suspension system and the body structure are altogether modeled as subsystems in the noise transfer path. In this paper, the mobility between the suspension and the body structure is analyzed by the dynamic stiffness at the connecting points. The measured drive point acceleration FRF at the connecting point in the transfer path was used to estimate the contributions of subsystems. The vibration modes of tire, the acoustic noise of tire's interior cavity, the vibration modes of the car's interior room, and the vibrations of body structure and the chassis are also considered to analyze the coupling effects of the road noise. Analyzing the measured results, direction for modification of car components is suggested.

The engine indicated torque is not delivered entirely to the wheels, because it is lowered by losses, such as the pumping, mechanical friction and front auxiliary power consumption. The front auxiliary belt drive system is a big power consumer-fueling and operating the various accessory devices, such as air conditioning compressor, electric alternator, and power steering pump. The standard fuel economy test does not consider the auxiliary driving torque when it is activated during the actual driving condition and it is considered a five-cycle correction factor only. Therefore, research on improving the front end auxiliary drive (FEAD) system is still relevant in the immediate future, particularly regarding the air conditioning compressor and the electric alternator. An exertion to minimize the auxiliary loss is much smaller than the sustained effort required to reduce engine friction loss.

In general, the ride and handling characteristics of a vehicle are strongly dependent on chassis parameters that come from the kinematic and compliance properties of a suspension system. For ride comfort improvement of a compact SUV with increasing handling performance simultaneously, this research proposes a new quantitative approach by considering various driving maneuvers and road surfaces. Particularly, five different road surfaces were used for ride comfort analysis, and this analysis was performed for two different vehicle speeds on a cleat road profile and three different vehicle speeds on a rough road profile. The contribution analysis of a suspension and a seat structure to ride comfort was investigated in order to decide an optimal structural combination. It was shown that contribution of each factor is different according to road profiles and driving conditions respectively.

Professional bus drivers are highly exposed to physical fatigue and work-related injuries because driving task includes complicated actions that require a variety of ability and cause extreme concentration or strain. For this reason, there has always been some sense of concern regarding driver fatigue, especially for drivers of commercial vehicles. In this study, we have tried to analyze quantitative fatigue degree of urban bus drivers by measuring their physiological signals. The investigation is made up of the following approaches: a traditional questionnaire survey and video-ethnographic method with 4-way cameras. The close-circuit cameras are installed to observe the upper and lower body of real drivers when they are in driving or even resting. This approach can help to understand urban bus drivers' behaviors and fatigue-related issues. Based on the video-ethnographic investigation results above, we have got certain patterns of drivers.

Road friction estimation algorithms had been studied for many years because it is very important factor for safety control and fuel efficiency of vehicle. But traditional solutions are hard to adapt in automotive industry because their performance is not sufficient enough and expensive to implement. Therefore, this paper proposes a road friction estimation algorithm based on a trained artificial neural-network which is low cost and robust. The suggested method doesn’t need expensive additional sensors such as optical or lidar sensor, also it shows better performance in real car environment compared to other algorithms based on vehicle dynamics. In this paper, we would describe this algorithm in detail and analyze the test results evaluated in real road conditions.

A fractional recirculation of cabin air was proposed and studied to improve cabin air quality by reducing cabin particle concentrations. Vehicle tests were run with differing number of passengers (1, 2, 3, and 4), four fan speed settings and at 20, 40, and 70 mph. A manual control was installed for the recirculation flap door so different ratios of fresh air to recirculated air could be used. Full recirculation is the most efficient setting in terms of thermal management and particle concentration reduction, but this causes elevated CO₂ levels in the cabin. The study demonstrated cabin CO₂ concentrations could be controlled below a target level of 2000 ppm at various driving conditions and fan speeds with more than 85% of recirculation. The proposed fractional air recirculation method is a simple yet innovative way of improving cabin air quality. Some energy saving is also expected, especially with the air conditioning system.

Generally, the HVAC system of a vehicle is composed of Blower unit assembly and Heater unit assembly, and is located on the driver’s side of the dash panel. However, electric vehicles have far fewer parts than conventional internal combustion engine vehicles, so electric vehicles have large space in the engine room. This allows HVAC, which occupies large volume in the interior side, to be pushed in the direction of the engine room altogether, or by placing a part inside the engine room to make a slim cockpit and expand the interior space. However, this new structure, called the Split HVAC System, is mounted through the dash, allowing noise to pass through relatively easily. Since this adversely affects the NVH of an electric vehicle, it needs to be developed in terms of noise transmission. Therefore, in this paper, a study was conducted to predict the sound transmission loss of Split HVAC through an analytical method.

The sound sources of modern road vehicle can be classified into three components, driving sound (sound generated through normal driving patterns and events), operating sound (sound generated through actuated components not related to driving), and generated synthetic sound (electronic warning / interactive feedback). The characteristic features of these sounds are dependent upon customer expectation and usage requirements. Additional development complexities are introduced due to each market's cultural and regional differences. These differences in preference must be considered for the establishment of the target sound quality in the early vehicle development process. In this paper, a sound quality goal setting procedure based on user preference is introduced. The sound targets are created as a result of the user preference investigation and validated by intercultural comparison.

This paper summarizes the development of a wireless message from infrastructure-to-vehicle (I2V) for safety applications based on Dedicated Short-Range Communications (DSRC) under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). During the development of the Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure (RSZW/LC) safety applications [1], the Basic Information Message (BIM) was developed to wirelessly transmit infrastructure-centric information. The Traveler Information Message (TIM) structure, as described in the SAE J2735, provides a mechanism for the infrastructure to issue and display in-vehicle signage of various types of advisory and road sign information. This approach, though effective in communicating traffic advisories, is limited by the type of information that can be broadcast from infrastructures.

This paper summarizes the validation of prototype vehicle-to-infrastructure (V2I) safety applications based on Dedicated Short Range Communications (DSRC) in the United States under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). After consideration of a number of V2I safety applications, Red Light Violation Warning (RLVW), Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure Warning (RSZW/LC) were developed, validated and demonstrated using seven different vehicles (six passenger vehicles and one Class 8 truck) leveraging DSRC-based messages from a Road Side Unit (RSU). The developed V2I safety applications were validated for more than 20 distinct scenarios and over 100 test runs using both light- and heavy-duty vehicles over a period of seven months. Subsequently, additional on-road testing of CSW on public roads and RSZW/LC in live work zones were conducted in Southeast Michigan.

It is considered that improper usage of rubber bushes and weak dynamic characteristics of chassis and body structures yield interior road noise problems. This paper describes systematic processes for road noise improvement along with measurement and analysis process. Firstly, the noise sources are identified by using a source decomposition method. Secondly, the main noise paths are identified by using a noise path analysis (NPA) method. Thirdly, the design modification of body panels is suggested for road noise reduction by using a panel contribution analysis. Finally the method is validated by applying to road noise improvement process for a new vehicle.

In order to perform the Optimal Route Planning avoiding traffic congestion, the structural elements (Rode type, Link type, Facilities type, Lane number, Turning type) in digital map and real-time traffic information are required. However, subjectively tuned cost weights of these elements, non theoretical relationship, and partially supported real-time traffic information that are mostly used for this implementation are not enough to satisfy. Therefore, in this research, by analyzing the relationship between the previously acquired traffic information history for some period of time and elements in digital map, we introduce the reasonable traffic information model that makes to estimate the speed information. Including the estimated speed, all the important factors of map database and the driver's preference, finally we made the cost model.

The shift towards electric vehicles is gaining pace to address carbon neutrality and environmental concerns. New technologies are being developed to cater to the unique features of EVs, such as the low indoor noise at low speeds, which require a low-noise ventilation system. A new dual-blower type system was developed to solve the problem of seat-bottom package caused by battery placement in the vehicle. This system uses two blowers, one for the cushion and one for the back, and reduces RPM to lower high-frequency noise. A new solution was introduced for temperature drop performance in the ventilation system. An integrated controller was also developed to control the seat warmer and ventilation system, with a smart control function added to respond to vehicle speed and ventilation time based on customer usage. As a result, this new ventilation system improves air volume, reduces noise, improves foot space, and reduces the number of parts compared to the previous system.

Platoon is a system that connects vehicles through vehicle-to-vehicle (V2V) communication technology to maintain a short distance between vehicles while driving on the road. To improve fuel efficiency, many automotive original equipment manufacturers (OEMs) are interested in developing and demonstrating real-world platoon system. However, it is hard for heavy duty trucks to develop this system due to the difficulty of maintaining the targeted intervehicle distance not only for fuel efficiency but also for safety in case of emergency braking. Because of this critical safety issue in the emergency situation, the platoon system for heavy duty trucks can be hardly demonstrated or tested in real vehicle environment. The relatively complex system and the slow response characteristic of commercial vehicles makes this even more difficult.

Electric Power Steering (EPS) needs to meet both functional and stability requirements, it plays significant role in controlling vehicle motion. In the meantime, customers emphasizes natural steering feel which can reflect vehicle motion and road surface information while isolate unwanted external disturbances. In general, conventional EPS control algorithms exert assist torque according to driver torque measured from torque sensor, while maintaining stability using stabilizing compensator. However, there exist significant trade-off between steering feel and stability, because the performances of assist torque control and stabilizing compensator are strongly coupled. In this paper a torque feedback control algorithm for EPS system is proposed in order to overcome the trade-off, and to achieve more natural, robust steering feel.

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.

This study has been conducted to analyze microbial diversity and its community by using a method of NGS(Next generation sequencing) technique that is not rely on cultivation for microbial community in an core evaporator causing odor of car air conditioner. The NGS without any cultivation method of cultivation, has been developed recently and widely. This method is able to research a microorganism that has not been cultivated. Differently with others, it can get a result that is closer to fact, also can acquire more base sequence with larger volume in relatively shorter time. According to bacteria population analysis of 23 samples, It can be known limited number of bacteria can inhabit in Evaporator core, due to small exposure between bacteria and evaporate, as well as its environmental characteristics. With the population analysis, only certain group of it is forming biofilm in proportion.