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Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. This paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios.

Traditional autonomous vehicle perception subsystems that use onboard sensors have the drawbacks of high computational load and data duplication. Infrastructure-based sensors, which can provide high quality information without the computational burden and data duplication, are an alternative to traditional autonomous vehicle perception subsystems. However, these technologies are still in the early stages of development and have not been extensively evaluated for lane detection system performance. Therefore, there is a lack of quantitative data on their performance relative to traditional perception methods, especially during hazardous scenarios, such as lane line occlusion, sensor failure, and environmental obstructions.

Powertrain development requires an efficient development process with no rework and model-based development (MBD). In addition, to performance design that achieves low CO2 emissions is also required. Furthermore, it also demands fuel economy performance considering real-world usage conditions, and in North America, the EPA (U.S. Environmental Protection Agency) 5-cycle, which evaluates performance in a combination of various environments, is applied. This evaluation mode necessitates predicting performance while considering engine heat flow. Particularly, simulation technology that considers behavior based on engine temperature for Hybrid Electric Vehicle (HEV) is necessary. Additionally, in the development trend of vehicle aerodynamic improvement, variable devices like Active Grille Shutter (AGS) are utilized to contribute to reducing CO2 emissions.

In this paper, a newly developed Active Noise Control (ANC) system is introduced, that effectively reduces road noise, which becomes a major issue with electrified vehicles, and that enhances vehicle interior sound levels matching seamless acceleration by electric drive. Conventionally, reducing road noise using ANC requires numerous sensors and speakers, as well as a processor with high computing power. Therefore, the increase in system cost and the complexity of the system are obstacles to its spread. To overcome these issues, this system is developed based on four concepts. The first is a modular system configuration with unified interface to apply to various vehicle types and grades. The second is the integration and optimal placement of noise source reference sensors to achieve both reduction in number of parts and noise reduction performance.

China's plug-in electric vehicle (PEV) market with stocks at 7.8 million is the world's largest in 2021, and it accounts for half of the global PEV growth in 2021. The PEV market in China has dramatically evolved since the pandemic in 2020: over 20% of all new PEV sales are from China by mid-2022. Recent features of PEV market dynamics, consumer acceptance, policies, and infrastructure have important implications for both the global energy market and manufacturing stakeholders. From the perspective of demand pull-supply push, this study analyzes China's PEV industry with a market dynamics framework by reviewing sales, product and brand, infrastructure, and government policies from the last few years and outlooking the development of the new government’s 14th Five-Year Plan (2021-2025).

The US Department of Energy’s Co-Optimization of Engine and Fuels Initiative (Co-Optima) investigated how unique properties of bio-blendstocks considered within Co-Optima help address emissions challenges with mixing controlled compression ignition (i.e., conventional diesel combustion) and enable advanced compression ignition modes suitable for implementation in a diesel engine. Additionally, the potential synergies of these Co-Optima technologies in hybrid vehicle applications in the medium- and heavy-duty sector was also investigated. In this work, vehicles system were simulated using the Autonomie software tool for quantifying the benefits of Co-Optima engine technologies for medium-duty trucks. A Class 6 delivery truck with a 6.7 L diesel engine was used for simulations over representative real-world and certification drive cycles with four different powertrains to investigate fuel economy, criteria emissions, and performance.

G-Equation models represent propagating flame fronts with an implicit two-dimensional surface representation (level-set). Level-set methods are fast, as transport source terms for the implicit surface can be solved with finite-volume operators on the finite-volume domain, without having to build the actual surface. However, they include approximations whose practical effects are not properly understood. In this study, we improved the numerics of the FRESCO CFD code’s G-Equation solver and developed a new method to simulate kernel growth using signed distance functions and the analytical sphere-mesh overlap. We analyzed their role for simulating propane/air flames, using three well-established constant-volume configurations: a one-dimensional, freely propagating laminar flame; a disc-shaped, constant-volume swirl combustor; and torch-jet flame development through an orifice from a two-chamber device.

When a vehicle is cruising, unpleasant noise in the 4 to 5 KHz high-frequency band can be heard at the center of all seats in the vehicle cabin. In order to specify the source of this noise, the correlation between the noise and airborne noise from the outer surface of the transmission was determined, and transfer path analysis was conducted for the interior of the transmission. The results indicated that the source of the noise was the 0th-order breathing mode specific to the drive motor. To make it possible to predict this at the desk, a vibrational analysis method was proposed for drive motors made up of laminated electrical steel sheets and segment-type coils. Material properties data for the electrical steel sheets and coils was employed in the drive motor vibrational analysis model without change. The shapes of the laminated electrical steel sheets and coils were also accurately modeled.

Current artificial intelligence techniques for end to end driving of autonomous vehicles typically rely on a single form of learning or training processes along with a corresponding dataset or simulation environment. Relatively speaking, success has been shown for a variety of learning modalities in which it can be shown that the machine can successfully “drive” a vehicle. However, the realm of real-world driving extends significantly beyond the realm of limited test environments for machine training. This creates an enormous gap in capability between these two realms. With their superior neural network structures and learning capabilities, humans can be easily trained within a short period of time to proceed from limited test environments to real world driving.

Metal additive manufacturing has high potential to produce automobile parts, due to its shape flexibility and unique material properties. On the other hand, residual stress which is generated by rapid solidification causes deformation, cracks and failure under building process. To avoid these problems, understanding of internal residual stress distribution is necessary. However, from the view point of measureable area, conventional residual stress measurement methods such as strain gages and X-ray diffractometers, is limited to only the surface layer of the parts. Therefore, neutron which has a high penetration capability was chosen as a probe to measure internal residual stress in this research. By using time of flight neutron diffraction facility VULCAN at Oak Ridge National Laboratory, residual stress for mono-cylinder head, which were made of aluminum alloy, was measured non-distractively. From the result of precise measurement, interior stress distribution was visualized.

In-cylinder surface temperature is of heightened importance for Homogeneous Charge Compression Ignition (HCCI) combustion since the combustion mechanism is thermo-kinetically driven. Thermal Barrier Coatings (TBCs) selectively manipulate the in-cylinder surface temperature, providing an avenue for improving thermal and combustion efficiency. A surface temperature swing during combustion/expansion reduces heat transfer losses, leading to more complete combustion and reduced emissions. At the same time, achieving a highly dynamic response sidesteps preheating of charge during intake and eliminates the volumetric efficiency penalty. The magnitude and temporal profile of the dynamic surface temperature swing is affected by the TBC material properties, thickness, morphology, engine speed, and heat flux from the combustion process. This study follows prior work of authors with Yttria Stabilized Zirconia, which systematically engineered coatings for HCCI combustion.

In this research, a material model was developed that has orthotropic properties with respect to in-plane damage to support finite element strength analysis of components manufactured from a randomly oriented long-fiber thermoplastic composite. This is a composite material with randomly oriented bundles of carbon fibers that are approximately one inch in length. A macroscopic characteristic of the material is isotropic in in-plane terms, but there are differences in the tension and compression damage properties. In consideration of these characteristics, a material model was developed in which the damage evolution rate is correlated with thermodynamic force and stress triaxiality. In-plane damage was assumed to be isotropic with respect to the elements. In order to validate this material model, the results from simulation and three-point bending tests of closed-hat-section beams were compared and found to present a close correlation.

The cooling performance and the heat resistance performance of commercial vehicle are balanced with aerodynamic performance, output power of powertrain, styling, cost and many other parameters. Therefore, it is desired to predict the cooling performance and the heat resistance performance with high accuracy at the early stage of development. Among the three basic forms of heat transfer (conduction, convection and radiation), solving thermal conduction accurately is difficult, because modeling of “correct shape” and setting of coefficient of thermal conductivity for each material need many of time and efforts at the early stage of development. Correct shape means that each part should be attached correctly to generate the solid mesh with high quality. Therefore, it is more efficient and realistic method to predict the air temperature distribution around the rubber/resin part instead of using the surface temperature at the preliminary design stage.

The dynamic performance of battery electric vehicles (BEV) is affected by battery output power, which depends on state of charge (SOC) and the temperature of battery cells. The temperature of the batteries varies in particular with the environment, in which the user stores the vehicle, and the battery output power. It is therefore necessary to employ thermal management systems that can control the battery temperature within the optimal range under severely hot and cold conditions in BEVs. A highly sophisticated thermal management system and its operation strategy were developed to fulfill the above requirements. The powertrain components to be thermo-controlled were located into two coolant circuits having different temperature range. The compact and efficient front-end heat exchangers were designed to optimally balance the cooling performance of powertrain, cabin comfort, vehicle aerodynamics and the vehicle design.

Since the operation of the powertrain system and the engine speed and torque are determined in the ECU in hybrid vehicles, control parameters in these vehicles are more sensitive to a variety of performance factors than those employed in conventional vehicles. The three performance factors acceleration performance, NVH and fuel consumption in particular are in a tradeoff relationship, the calibration of control parameters in order to satisfy these performance targets entail considerable development costs. Given this, it is possible to increase the efficiency of hybrid vehicle development by determining Pareto design solutions for the three performance factors via multi-objective optimization using CAE, and selecting target performance and control parameters based on these Pareto design solutions.

A compact intelligent power unit capable of being installed under the rear seating was developed for the 2018 model year Accord Hybrid that is to be equipped with the SPORT HYBRID Intelligent Multi Mode Drive (i-MMD) system. The space under the rear seat features multiple constraints on dimensions. In the longitudinal direction, it is necessary to attempt to help ensure occupant leg room and to position the fuel tank; in the vertical direction, it is necessary to attempt to help ensure occupants comfort and a minimum ground clearance; and in the lateral direction, it is necessary to avoid the position of the body side frames and the penetrating section of the exhaust pipe. The technologies described below were applied in order to reduce the size of components, making it possible to position the IPU amid these constraint conditions.

4C3B (4 coat 3 bake) painting system (see Figure 1) which needs a bake process after the primer surfacer paint was very general and common process for the automotive body painting system. In the beginning of the 2000s, 4C2B painting system (Reference 1) was developed which changed the oven after the primer surfacer paint to a pre heat area, so it can reduce the carbon dioxide (Figure 1, and Figure 2). But unfortunately in this 4C2B painting system, the base coat will be painted on the primer surfacer paint wet-on-wet. By that reason, the appearance deterioration will occur often. The authors used a low temperature crosslinking agent “Polycarbodiimide” to a water born primer surfacer paint, to control the viscosity of primer surfacer paint at the pre heat area. Controlling the viscosity is important to avoid the layer mixing of the primer surfacer paint and the base coat which makes appearance deterioration.

With accelerating exhaust gas regulations in recent years, not only CO / HC / NOx but also PN regulation represented by Euro 6 d, China 6 are getting stricter. PN reduction by engine combustion technology development also progresses, but considering RDE, PN reduction by after treatment technology is also indispensable. To reduce PN exhausted from the gasoline engine, it is effective to equip GPF with a filter structure. Considering the installation of GPF in limited space, we developed a system that so far replaces the second TWC with GPF for the TWC 2 bed system. In order to replace the second TWC with GPF, we chose the coated GPF with filtering and TWC functions. Since the initial pressure drop and the catalyst amount (purification performance) of coated GPF have a conflicting relationship, we developed the coated GPF that can achieve both the low initial pressure drop and high purification performance.

At present, measurements of running resistance are conducted outdoors as a matter of course. Because of this, the ambient temperature at the time of the measurements has a considerable impact on the measurement data. The research discussed in this paper focused on the temperature characteristic of the tires and developed a new correction technique using a special rolling test apparatus. Specifically, using a tire rolling test apparatus that made it possible to vary the ambient temperature, measurements were conducted while varying the levels of factors other than temperature that affect rolling resistance (load, inflation pressure, and speed). Next, a regression analysis was applied to the data for each factor, and coefficients for a relational expression were derived, making it possible to derive a quadratic equation for the tire rolling resistance correction formula.

In motorcycles, the mass difference between a vehicle and a rider is small and motions of a rider impose a great influence on the vehicle behaviors as a consequence. Therefore, dynamic properties of motorcycles should be evaluated not merely dealing with a vehicle but considering with a man-machine system. In the studies of a simulation for vehicle dynamics, various types of rider models have been proposed and it has already been reported that rider motions have a significant influence on the dynamic properties. However, the mechanism of the interaction between a rider and a vehicle has not been clarified yet. In our study, we focused on weave motion and constructed a full vehicle simulation model that can reflect the influences of the movements of the rider’s upper body and lower body. To construct the rider model, we first measured the vibrational characteristics of a human body using a vibration test bench.