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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.

An efficient method to determine optimal bushing stiffness for improving noise and vibration of passenger cars is developed. In general, a passenger vehicle includes various bushings to connect body and chassis systems. These bushings control forces transferred between the systems. Noise and vibration of a vehicle are mainly caused by the forces from powertrain (engine and transmission) and road excitation. If bushings transfer less force to the body, levels of noise and vibration will be decreased. In order to manage the forces, bushing stiffness plays an important role. Therefore, it is required to properly design bushing stiffness when developing passenger vehicles. In the development process of a vehicle, bushing stiffness is decided in the early stage (before the test of an actual vehicle) and it is not validated until the test is performed.

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.

Systematic numerical simulations were performed for the improvement of fuel efficiency and thermal performance of a compact size passenger vehicle. Both aerodynamic and thermal aspects were considered concurrently. For the sake of systematic evaluation, our study was conducted employing various design changes in multiple steps: 1) analysis of the baseline design; 2) elimination of the engine room components; 3) modification of the engine room component layout; 4) modification of the aerodynamic components (such as under body cover and cooling ducts). The vehicle performance characteristics corresponding to different design options were analyzed in terms of aerodynamic coefficient, engine coolant temperature, and surface temperatures of thermally critical components such as battery and exhaust manifold. Finally optimal design modification solutions for better vehicle performance were proposed.

NVH analysis based on numerical simulations before actual test vehicle is available becomes common process in the automotive industry. Furthermore, the latest work scope is extending even to conceptual study in the very early design stage, beyond traditional numerical simulations simply using 3-D CAD data. In case when reasonable information is provided at this very early vehicle development stage, a better decision on the design concept would be possible, and subsequent design process can be carried out in more efficient manner. The core of this trend is that it allows us to predict vehicle performance at the conceptual design stage without 3-D CAD data, and then, with this prediction, to suggest meaningful design directions for next stage. From this point of view, FRF-Based Substructuring (FBS) methodology has potential to be used as an appropriate tool for this purpose.

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 body stiffness plays a key role in vehicle performance, such as noise and vibration, ride and handling, durability and so on. In particular, a body D-pillar ring structure is the most sensitive affecting the body stiffness on vehicle with tail gate. Therefore, since D-pillar body ring structure for high stiffness and lightweight is required, an optimized design methodology that simultaneously satisfies the requirements was studied. It focused on a methodology that body engineering designers can optimize design parameters easily and quickly by themselves in the preceding stages of vehicle’s styling distribution and design conceptual planning. First, it is important to establish the body stiffness design strategy by predicting the body stiffness with the vehicle’s styling at early design stage. The methodology to predict body stiffness with the styling and body dimension specification parameters was introduced.

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.

The tire is the vital element in vehicle dynamics, as its contact patch transmits all forces and moments to the ground (accelerating, braking, cornering, rolling).Over the recent decades tire development for passenger cars has been continuously improved and optimized in order to achieve a good overall vehicle performance in R&H that is in balance with all other tire performances (Wear, Durability, NVH, RR, Miles). This general development process has to be suitable for various vehicle types from regular passenger cars over eco-friendly hybrid or electric vehicles to high performance sport cars. The balance between Ride and Handling performance is further adjusted to local customer preferences that are usually distinguished by markets (US, EU, Asia). The tire development process, which is embedded in the overall vehicle development, is usually realized in a mutual collaboration between OEM and tire supplier.

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 paper is concerned with the energy management strategy of hybrid electric vehicle using stochastic dynamic programming. The aim is the control strategy of the power distribution for hybrid electric vehicle powertrains to minimize fuel consumption while maintaining drivability. The fuel economy of hybrid electric vehicle is strongly influenced by power management control strategy. Rule-based control strategy is popular strategy thanks to its effectiveness in real-time implementation, but rule should be designed and efficiency of entire drive trains is not optimized. Dynamic programming, one of optimization-based control strategy presents outstanding performance, but cannot be used as real-time control strategy directly, since its non-causal property and drawback that global optimal solution can only be obtained for specific driving cycle. In this paper, stochastic dynamic programming is applied to parallel hybrid electric vehicle to optimize vehicle performance in average sense.