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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.

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.

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.

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.

A method and equipment for the determination of material limits for polymeric thrust elements is presented along with initial data based on the system. Methods are presented to better simulate drive train thrust element operation on equipment that utilizes production ready mating components under actual load, speed, and lubrication conditions. Initial results for limited materials are presented. This study allows for a more complete understanding of the effects of the product of pressure and velocity (PV) on material wear and frictional behavior for drive train applications of thrust elements.

Engine off control is conducted on parallel hybrid vehicles in order to reduce fuel consumption. It is efficient in terms of fuel economy, however, noise and vibration is generated on engine cranking and transferred through engine mount on every mode transition from EV to HEV. Engine crank position control has been studied in this paper in order to reduce vibration generated when next cranking starts. System modeling of an architecture composed of an engine, P1 and P2 motors has been conducted. According to the prior studies, there exists correlation between crank vibration level and the crank angle. Thus a method to locate pistons on a specific crank angle which results in a local minimum of vibration magnitude could be considered. The P1 motor facilitates this crank position control when engine turns off, for its location directly mounted on a crankshaft allows the system model to obtain more precise crank position estimation and improved linearity in torque control as well.

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.

High-voltage battery system plays a critical role in eco-friendly vehicles due to its effect on the cost and the electric driving range of eco-friendly vehicles. In order to secure the customer pool and the competitiveness of eco-vehicle technology, vehicle electrification requires lowering the battery cost and satisfying the customer needs when driving the vehicles in the real roads, for example, maximizing powers for fun drive, increasing battery capacities for achieving appropriate trip distances, etc. Because these vehicle specifications have a critical effect on the high-voltage battery specification, the key technology of the vehicle electrification is the appropriate decision on the specification of the high-voltage battery system, such as battery capacity and power. These factors affect the size of battery system and vehicle under floor design and also the profitability of the eco-friendly vehicles.

Parallel Hybrid Electric Vehicle consists of internal combustion engine, engine clutch, motor, automatic transmission, Integrated Starter Generator (ISG), and battery. Due to hybridizations such as using engine clutch to disengage the internal combustion engine and omitting torque converter from the automatic transmission to increase fuel economy, drivability will not be same as conventional vehicle. To ensure drivability comparable to conventional vehicle, dynamic simulation has been utilized to foresee the drivability issues for the proposed hybrid system and ideas for improvements are tested in simulation. CoSimulation of AMESim vehicle model and Simulink Hybrid Control Unit (HCU) model has been used to test and improve HCU logic.