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This paper describes an automated path following system using vision sensor. Lateral control law for path following is especially underlined which is developed by using the backstepping control design methodology. To establish the proposed control system, the lateral offset to the reference path, the heading angle of vehicle relative to tangent line to the path, and path curvature are required. Those inputs to the controller have been calculated through Kalman filter which is frequently adopted for the purpose. The lane mark detection has been achieved in an ECU (Electric Control Unit) platform with vision sensor. The yaw rate and side-slip angle also needed in the controller are estimated by Kalman estimator. To show the performance of the proposed controller under different speeds, experiment has been conducted on a proving ground having straight and curve sections with the curvature of about 260m.

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.

The purpose of this paper is an attempt to make a good compromise between ride and handling without deteriorating each other. Compromise between ride and handling has been a problem for suspension designer. Attempts are made by varing suspension parameters. Effects of each combination has been tested with basic ride and handling test methods. For ride to maintain a constant natural frequency through all load range was a primary target. And for handling to get adequate roll angle at 0.5g lateral acceleration was a target. In conclusion, combination of polyurethane suspension bump and normal rear spring was proved to be able to provide the best compromise, low cost, light weight and better performance. This also showed polyurethane bumper could carry out spring aids successfully.

This paper presents an industrial application of the Analytical Target Cascading (ATC) methodology to the optimal design of commercial vehicle steering and suspension system. This is a pilot study about the suspension and steering design of a semi medium bus, whose objective is to develop and introduce an ATC methodology to an automobile development process. In the conventional process, it is difficult not only to find design variables which meet the target of Ride and Handling (R&H) performance using a detailed full car model, but also to figure out the interrelation between the vehicle and its subsystems. In this study, ATC methodology is used in order to obtain the optimal values such as geometric characteristics satisfying both the vehicle's R&H target and the subsystem (suspension and steering system) 's target.

Worldwide projections anticipate a fast-growing market share of the battery electric vehicles (BEVs) to meet stringent emissions regulations for global warming and climate change. One of the new challenges of BEVs is the effective and efficient thermal management of the BEV to minimize parasitic power consumption and to maximize driving range. Typically, the total efficiency of BEVs depends on the performance and power consumption of the thermal management system, which is highly affected by several factors, including driving environments (ambient temperature and traffic conditions) and driver's behavior (aggressiveness). Therefore, this paper investigates the influence of these factors on energy consumption by using a comprehensive BEV simulation integrated with a thermal management system model. The vehicle model was validated with experimental data, and a simulation study is performed by using the vehicle model over various traffic scenarios generated from a traffic simulator.

This paper describes a torque steer reduction process for a front-wheel drive car with a high torque engine at the initial stage of vehicle development. Literature reviews for the reduction process and vehicle integration tradeoffs among chassis components, driveline components, and loading condition are included. Drive shaft angle and its stiffness, differential gear stiffness, and power train mount, and vehicle weight distribution are mainly considered. In addition, wheel alignment data such as kingpin offset, kingpin inclination, camber angle, ride height, and dynamic tire radius are also discussed to solve the torque steer problem. This paper introduces an example solution to improve the torque steer during vehicle development stage. In that case, the vehicle parameters should be considered the factors to achieve many requirements. In spite of that restriction of alteration, the result of improvement became better than that of its competitor.

This paper proposes a speed controller using a disturbance observer to regulate the speed of a commercial vehicles, and presents vehicle test results to evaluate the performance of the proposed controller. Most ADAS (Advanced Driver Assistance System) and automated driving systems need to reliably regulate the vehicle's speed under any circumstances. A conventional PID controller is commonly used to control the vehicle speed, but performance of it varies depending on changes in external conditions. Commercial vehicles are even more susceptible to these changes than passenger cars and more difficult to obtain an accurate plant model. Considering these features, a speed controller using a disturbance observer is designed for commercial vehicles. The proposed controller treats changes in external conditions as disturbances. The modeling uncertainty is also treated as a disturbance.

In this study, the preliminary validation method of the steering system is constructed and the objective is to satisfy the target performance in the conceptual design stage for minimizing the problems after the detailed design. The first consideration about steering system is how to extract the reliable steering effort for parking. The tire model commonly used in MBD(Multi-Body Dynamics) has limited ability to represent deformations under heavy loads. Therefore, it is necessary to study adequate tire model to simulate the behavior due to the large deformation and friction between the ground and the tire. The two approaches related with F tire model and mathematical model are used. The second is how to extract each link’s load in the conceptual design stage. Until now, each link’s load could be derived only by actual vehicle test, and a durability analysis was performed using only pre-settled RIG test conditions.

In this study, two-phase flow simulations have been performed for the intake system of a commercial truck. The intake duct, which is the first component in heavy-duty engine, is located in the upper side of a cabin. The flow in the intake system is a typical two-phase flow with the air as the continuous phase and the water as the dispersed phase during rainy weather. The numerical two-phase simulation is performed by using the Largrangian model as implemented in STAR-CD. The influence of the water droplets on the airflow as well as droplet break-up and interactions of the droplets with the walls can be taken into account. Two and three cyclone model inside the intake system have been investigated by numerical simulations. The computational results can be used to get a better understanding of the physics of the flow inside the intake system and to optimize the water separation.

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.

Recently, regulations on automobile emission have been significantly strengthened to address climate change. The automobile industry is responding to these regulations by developing electric vehicles that use batteries and fuel-cells. Automobile emissions are environmentally harmful, especially in the case of vehicles equipped with high-temperature and high-pressure diesel engines using compression-ignition, the proportion of nitrogen oxides (NOx) emissions reaches as high as 85%. Additionally, air pollution caused by particulate matter (PM) is six to ten times higher compared to gasoline engines. Therefore, the electrification of commercial vehicles using diesel engines could potentially yield even greater environmental benefits. For commercial vehicles battery electric vehicles (BEVs) require a large number of batteries to secure a long driving range, which reduces their maximum payload capacity.

In the path following problem, a commercial vehicle has a delay of a hydraulic steering actuator and slow steering response accordingly. In addition, there are disturbances due to the harsh driving conditions of commercial vehicles. These disturbances may include uncertainties about actuator dynamic delay, modeling error and steering angle sensor offset. Designing a lateral controller with good performance that can overcome this problem is the key to successfully carrying out autonomous driving of commercial vehicles. Usually, it is difficult to consider disturbances with uncertainties in the geometric based control methods. Therefore, this paper proposed a lateral controller using feedback augmented disturbance observer for the commercial vehicle. First, a dynamics was modeled which can describe delay of the hydraulic actuator of the commercial vehicle. After that, a lateral controller was designed based on this dynamics model.

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.

This study investigates how hilly road profiles affect the optimal energy management strategy for fuel cell hybrid electric vehicle (FCHEV) with various battery sizes. First, a simplified FCHEV model is developed to describe power and energy flows throughout the powertrain and evaluate hydrogen consumption. Then, an optimal control problem is formulated to find the globally optimal energy management strategy of FCHEV over driving cycles with road elevation profile. In order to solve the optimal energy management problem of the FCHEV, Dynamic Programming, a dynamic optimization method, is used, and their results are analyzed to find out how hilly road conditions affect the optimal energy management strategies. The results show that the optimal energy management with a smaller battery tends to actively prepare (e.g. pre-charge/pre-discharge) for uphill/downhill roads in order not to violate the battery state of charge (SoC) bounds.

In the era of electric vehicles(EVs), the need for weight reduction of the vehicle body is increasing in order to maximize the driving distance of the EV. Accordingly, there is an increasing need for research to efficiently apply lightweight materials, such as aluminum and CFRP, to the EV body parts. In this study, design methodologies and optimization measures to increase lightweight efficiency when applying lightweight materials to EVs will be discussed. Based on theoretical basis and basic performance of each part of the EV, the “Material Substitution Method” of replacing existing parts of a steel body with aluminum materials will be defined, and the optimal design process on how to overcome performance trade-off caused by material characteristics will be addressed. In applying the “Material Substitution Method” to the actual EV body design process, it was possible to convert 93% of the components from steel to aluminum and reduce the overall weight of the body by 23%.

Suspension system of vehicle is very important because it has an effect on ride comfort and safety. And the leaf spring is one of the major parts of commercial vehicle. By that reason it has to be designed to operate under severe condition to ensure enough endurance. But the traditional method for fatigue design needs repeated fatigue tests for each design according to its geometry, material, and operating condition. This means that a lot of time and money is needed for those tests. Thus, in this paper, a fatigue design method for leaf spring based on numerical analysis is proposed. At first, stress analysis is performed to get the stress under operation load or rig tests. And fatigue analysis is performed to get the fatigue life and to ensure the safety of leaf spring. Through this study, design parameters that play vital role in fatigue life of the leaf spring can be found out.

APAS refers to a low speed sound warning system of electric vehicles, which emits alerting sound only to target pedestrians by sound focusing techniques with array of speakers and object detective camera. In the present study, experimental and numerical investigations are conducted in designing speaker part and array of APAS with consideration of three main performance matrices; HEV/EV warning sound regulations in Europe and U.S., pedestrian awareness, and driver’s noise comfort. The present APAS speaker consists of back enclosure, wave guide and front grill. Each of these components plays an important role for characterizing frequency emphasis and sound directivity. The main impedance frequencies of the speaker are determined by considering warning sound regulations and also by analyzing acoustic frequency response at in/outside of a vehicle.

This paper mainly focuses on a lateral control law for pre-given path following which is developed by using the backstepping control design methodology. The position information of the vehicle is obtained by Real Time Kinematic DGPS, and the yaw rate and side-slip angle used in controller are estimated by Kalman estimator. To show the performance of the proposed controller under different speed and various path curvature conditions, the results are given through experiments which are executed on proving ground especially designed for high maneuvering test of which minimum radius of curvature is about 60 m.

In order to design the in-wheel motor (IWM) for Electric Vehicles (EV), it is necessary to analyze the desired (expected) duty cycle at a higher performance level in order that the IWM becomes commercially relevant. The duty cycle may be representative of different segments of the customer base. Or, the individual customer may wish to have a set of IWMs that uniquely meet his/her measured “demand” cycle for a balance of drivability and efficiency. Questions then arise: How to measure the demand cycle of an individual? What 2 or 3 standard duty cycles should be offered as customer choices for their vehicle? Should the IWM represent multiple speed domains to enhance efficiency and drivability? Can the vehicle be updated rapidly 2 to 3 years after purchase? Etc. In this paper, we lay the groundwork to answer these types of customer questions for an EV with four independent IWMs.

Charge boosting strategy plays an essential role in improving the power density of diesel engines while meeting stringent emissions regulations. In downsized two-stage turbocharged engines, turbocharger matching is critical to achieve desired boost pressure while maintaining sufficiently fast transient response. A numerical simulation model is developed to evaluate the effect of two-stage turbocharger configurations on the perceived vehicle acceleration. The simulation model developed in GT-SUITE consists of engine, drivetrain, and vehicle dynamics sub-models. A model-based turbocharger control logic is developed in MATLAB using an analytical compressor model and a mean-value engine model. The components of the two-stage turbocharging system evaluated in this study include a variable geometry turbine in the high-pressure stage, a compressor bypass valve in the low-pressure stage and an electrically assisted turbocharger in the low-pressure stage.