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CO2 emission is more serious in recent years and automobile manufacturers are interested in developing technologies to reduce CO2 emissions. Among various environmental-technologies, the use of solar roof as an electric energy source has been studied extensively. For example, in order to reduce the cabin ambient temperature, automotive manufacturers offer the option of mounting a solar cell on the roof of the vehicle [1]. In this paper, we introduce the semi-transparent solar cell mounted on a curved roof glass and we propose a solar energy management system to efficiently integrate the electricity generated from the solar roof into internal combustion engine (ICE) vehicles. In order to achieve a high efficiency solar system in different driving, we improve the usable power other than peak power of solar roof. Peak power or rated power is measured power (W) in standard test condition (@ 25°C, light intensity of 1000W/m2(=1Sun)).

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.

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.

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.

Reductions in powertrain noise have led to an increased proportion of road noise, prompting various studies aimed at mitigating it. Road excitation primarily traverses through the vehicle suspension system, necessitating careful optimization of the characteristics of bushings at connection points. However, optimizing at the vehicle assembly stage is both time-consuming and costly. Therefore, it is essential to proceed with optimization at the subsystem level using appropriate objective functions. In this study, the blocked force and energy-based index derived from complex power were used to optimize the NVH performance. Calculating the complex power in each bushing enables computing the power flow, thereby providing a basis for evaluating the NVH performance. Through stiffness injection, the frequency response functions (FRF) of the system can be predicted according to arbitrary changes in the bushing stiffness.

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.

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.

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.

The electric power system of a modern vehicle has to supply enough electrical energy to numerous electrical and electronic systems. The electric power system of a vehicle consists of two major components: a generator and a battery. A detailed understanding of the characteristics of the electric power system, electrical load demands, and the driving environment such as road, season, and vehicle weight are required when the capacities of the generator and the battery are to be determined for a vehicle. In order to avoid the over/under design problem of the electric power system, an easy-to-use and inexpensive simulation program may be needed. In this study, a vehicle electric power simulator is developed. The simulator can be utilized to determine the optimized capacities of generators and batteries appropriately. To improve the flexibility and easy usage of the simulation program, the program is organized in modular structures, and is run on a PC.

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.

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.

Brake-By-Wire (BBW) is a term used to describe next generation brake systems that rely on motor driven electro-mechanical calipers in place of conventional hydraulic components such as the booster, master cylinder, hydraulic unit, and parking brake. Instead the system configuration is simplified to a pedal simulator, electro-mechanical calipers that require no boosting, and electric control units. The active, highly-responsive, and independent control of the brake actuators at each wheel allows for great control flexibility and improved brake performance. It is also very well-suited for easy integration with cooperative regenerative braking and driver assistance functions. Although such potential and innovations have driven the interest and research into BBW systems through the years, it has yet to be successfully introduced in series production mainly due to the underlying perception of the lack of reliability of electronic components and overall cost concerns.

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 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.

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.

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.

This research aims presents the method classifying the noise source and evaluating the sound quality of the noise caused by operating of electric power steering wheel in an electric vehicle. The steering wheel has been operated by the motor drive by electric power and it called motor-driven electric power (MDPS) system. If the motor is attached to the steering column of the steering device, it is called C-MDPS system. The steering device of the C-MDPS system comprises of motor, bearings, steering column, steering wheel and worm shaft. Among these components the motor and bearings are main noise sources of C-MDPS system. When the steering wheel is operated in an electric vehicle, the operating noise of the steering device inside the vehicle is more annoying than that in a gasoline engine vehicle since the operating noise is not masked by engine noise. Defects in the C-MDPS system worsen the operating noise of the steering system.

Conventional EPS (Electric Power Steering) systems are operated by one type of steering tuning map set by steering test drivers before being released to customers. That is, the steering efforts can't change in many different driving conditions such as road conditions (low mu, high mu and unpaved roads) or some specific driving conditions (sudden stopping, entering into EPS failure modes and full accelerating). Those conditions can't give drivers consistent steering efforts. This paper approached the new concept technology detecting those conditions by using vehicle and EPS sensors such as tire wheel speeds, vehicle speed, steering angle, steering torque, steering speed and so on. After detecting those conditions and judging what the best steering efforts for safe vehicle driving are, EPS systems automatically can be changed with the steering friction level and selection of steering optimized mapping on several conditions.

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 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.