In the development of environmentally friendly vehicles aimed at achieving carbon neutrality，reducing air pollutants remains a critical challenge． Conventional approaches to improving exhaust purification efficiency often involve trade-offs， such as increasing catalyst volume or cell density， which result in higher pressure loss． This study investigates the fluid dynamics near the catalyst cell inlet， focusing on enhancing gas–catalyst interaction through the use of convection． By leveraging this mechanism， we have developed an innovative structural design that improves purification performance while improving the traditional trade-off with pressure loss．

In this study, a direct-injection hydrogen engine for motorcycles was investigated using a newly developed simultaneous dual-direction in-cylinder direct imaging method. Two optical access windows were arranged on the cylinder head, enabling simultaneous observation of flame propagation in both intake and exhaust valve directions. OH* chemiluminescence imaging was applied to observe combustion processes. OH* chemiluminescence imaging was combined with combustion analysis, histogram-based image analysis, CFD analysis, and two-band near infrared thermometry. These approaches enabled spatial evaluation of combustion phase and chemiluminescence behavior from qualitative and quantitative viewpoints. Furthermore, under high-speed operating conditions, dual-direction imaging captured changes in flame shape and propagation behavior, indicating rapid flame development in high-flow fields.

This study investigates CO₂ absorption and recovery systems for diesel-engine-powered trucks, industrial machinery, agricultural machinery, and generators as a CO₂ reduction technology to be combined with carbon-neutral fuels. In a previous report, we investigated a chemical absorption method that uses droplet impingement and atomization on a textured surface plate and confirmed CO₂ absorption efficiency at room temperature. In this report, we additionally investigated the effects of gas temperature and impingement plate temperature and examined the potential of a new CO₂ absorption and recovery system that combines chemical absorption with physical adsorption using downstream CO₂ adsorbents.

This study aims to establish a high-efficiency combustion system by utilizing the fuel-specific properties of oxymethylene dimethyl ether (OME). A combined methodology involving CFD simulations, single-cylinder engine tests, and in-cylinder OH chemiluminescence imaging was employed to evaluate the effects of compression ratio, nozzle flow rate (large-orifice), and injection pressure (low-pressure) on indicated efficiency, heat losses, and emissions. OME achieved indicated efficiency comparable to diesel while simultaneously reducing NOx and soot by combining of large-orifice nozzle, low injection pressure, and high compression ratio. However, total heat losses increased, preventing efficiency from exceeding that of diesel. The visualization results revealed that the residence time of the high-temperature reaction zone near the wall is prolonged at low injection pressures, which is considered a factor leading to increased heat loss.

The rapid electrification and increasing intelligence of vehicles have significantly increased power unit system complexity, making prototype-based development inefficient. Drivability (DRB), a key attribute of vehicle product quality, has traditionally relied on subjective evaluation using actual vehicles, limiting early verification. This study proposed model-based development (MBD) framework that enables quantitative and reproducible DRB evaluation using Power Unit Transient Bench (PTB). DRB perception was restructured as the relationship between driver operation and vehicle response, and six standardized DRB metrics were defined. In addition, standardized acceleration evaluation, unified driver models, and advanced battery emulator with flexible State Of Charge (SOC) initialization were introduced. The proposed approach enabled comprehensive DRB verification and significantly shortened verification periods.

Due to shading from buildings and trees, solar irradiance received by onboard PV systems is lower than that of stationary PV systems. This study measured vehicle and fix-point irradiance under sunny and cloudy weather across various urban, suburban, and expressway routes. The measured data was analyzed to clarify how these diverse driving and weather conditions specifically influence the ratio between vehicle and fixed-point irradiance (V/F). Furthermore, the practical method for estimating vehicle irradiance was proposed and constructed with the insights obtained from this analysis.

In this study, an analytical method was developed to predict the vibration noise of motor when vehicle is running. Time harmonics of the current, spatial harmonics of the motor, and velocity dependence were considered. The spatial mode of the electromagnetic excitation force was shown, and the relationship between the magnetic flux density and the electromagnetic excitation force was shown by the Maxwell stress equation. A method to reflect the velocity dependence and spatial mode of the electromagnetic excitation force as the frequency dependence and phase of the structural analysis was shown. The reduction of 6th order of electromagnetic excitation force and the reduction of acoustic power by the reduction of the 5th order of the current were confirmed. This study is expected to contribute to the model-based development of vehicles by raising the hierarchy of prediction from the component level to the system level.

In order to reproduce the actual driving conditions of an xEV on a 4WD chassis dynamometer, it is essential to appropriately reflect the unique power performance of an electric vehicle (especially the transient characteristics including sudden acceleration and deceleration) on the platform. Following the results of the first report, this second report discusses evaluation indices that consider the impact on power consumption rates of the 4WD chassis dynamometer necessary for evaluating actual driving characteristics of xEV.

To improve development efficiency of power unit, Model-Based Development (MBD) has been promoted throughout the entire development process. As part of this initiative, a 1D system model and a Power unit Transient Bench (PTB) have been applied to power unit development, enabling efficient calibration and performance verification by reproducing vehicle driving conditions. However, differences among individual PTB systems require inefficient, system-specific setup procedures for power unit installation. The differences have become a barrier to fully leveraging the potential of PTB systems in practical operation. This paper describes efforts toward standardization of PTB systems (standardizing bench replacement method, standardizing measurement architecture, and standardizing automated test scenarios) aimed at achieving more efficient PTB operation.

In early-stage automotive hood design, identifying low-injury regions (Green: HIC < 650) is useful for screening hood structure-induced pedestrian protection potential and prioritizing CAE allocation before detailed under-hood packaging is fixed. However, at this stage, design drawings lack sufficient geometric fidelity for reliable injury estimation through high fidelity CAE. This study proposes a framework combining deep learning surrogate models with a class-conditional residual calibration inspired by conformal prediction to estimate low-injury regions with uncertainty-aware margins, presented as an action map. Because the patch-based CNN baseline predicts each evaluation point independently without explicitly using physical correlations between neighbors, we constructed Spatial VisionGNN (S-VGNN), which connects CNN features via graph neural networks (GNNs) to propagate information across spatially adjacent points. Comparing LeNet5 (CNN), S-VGNN, and SwinTransformer through leave-one-out cross-validation on 22 production hoods, S VGNN achieved the best Green F1 score (0.800). Since prediction errors vary significantly across HIC classes, calibration using only low-injury-class residuals identified 20.4% of evaluation points as Safe candidates with 93% precision. The results are presented as an action map classifying each evaluation point into Safe (CAE priority can be lowered), Re-CAE (CAE recommended), or Non-Green(detailed design review required), enabling prioritized allocation of CAE resources in early design stages.

This study treats local kinking of a thin-walled curved tube within a conceptual design framework for impact performance based on Impact Statistical Energy Analysis (ISEA). Force–stroke (FS) curves were obtained by finite element analysis, and the deformation process was classified into an initial peak, kinking of the curved segment, and bending collapse of the straight segments. Only the kinking of the curved segment was treated as the design target. A quasi-static FS expression was derived for this segment and compared with dynamic and quasi-static FEM results. Excluding the initial peak, the dynamic response fluctuated around the quasi-static response, and the quasi-static FEM result agreed with the theory within about 2% in absorbed energy. From the absorbed energy of the averaged FS curve, the equivalent viscous damping coefficient used in ISEA was formulated, and a thickness design based on the derived coefficient achieved the target energy absorption under dynamic impact.

Creating training data for long-range nighttime vehicle recognition requires substantial manual annotation effort for monocular camera images. In this study, we propose an automatic training data generation technique that aligns vehicle detection results obtained by a 90-cm baseline stereo camera at distances of up to approximately 1 km with monocular camera images using a calibration-based two-stage processing method. The proposed method achieves approximately 90 % reduction in annotation labor while maintaining high alignment accuracy.

This study analyzes the effect of recent institutional reforms in the automotive maintenance field, specifically the "revision of the automotive mechanic qualification system" and the "update of regulations on automotive maintenance businesses," on the educational system. Textbook analysis revealed that the revision of educational content is progressing not as a quantitative expansion, but as a qualitative restructuring, clearly indicating a shift from a mechanically-centered system to a comprehensive educational system including electrical, electronic, and software fields. Furthermore, while securing personnel is progressing due to the shortening of practical experience periods and the relaxation of qualification requirements, the structure is changing, with the quality of educational content and environment now influencing skill levels. In addition, institutional reforms such as the mandatory use of scan tools and the introduction of electronic record books are promoting the digitalization of maintenance work, requiring educational institutions to develop advanced curricula and teacher training systems.

Vehicle response to steering input is affected by interaction between the steering system and vehicle motion. Front-tyre lateral forces generate a restoring moment about the kingpin, which acts on the steering system and couples the steering system with vehicle motion. Previous studies have proposed steering control methods to decouple this interaction. However, a framework for incorporating the restoring moment into steering system dynamics as a steering–vehicle coupling term has not been explicitly organised. This study examines the coupled structure of a steering–vehicle system with steering control. A two-degree-of-freedom steering-system model is reduced to a one-degree-of-freedom steering-system model, and dominant poles are compared. Root loci and coefficients of the characteristic equation show that the restoring moment appears as a coupling term. The derived stability conditions clarify the roles of the restoring-moment coupling term and steering control in system stability. Incorporating the coupling term into steering-system dynamics enables vehicle-motion effects and steering control to be treated in a unified form.

We propose a multi-component surrogate framework for diesel and biodiesel blends that separates liquid-phase and gas-phase surrogates derived directly from measured fuel composition. The liquid surrogate retains distillation behavior using 36 components, while 13 gas-phase representative species are mapped to a detailed kinetic mechanism. Cetane-number equivalence is achieved through targeted adjustments to low-temperature oxidation pathways and surrogate blending, enabling consistent ignition ranking across B7, HVO, PME50, and SME50. A reduced mechanism (284 species, 5842 reactions) is coupled with 3D CFD spray combustion simulations and validated against engine tests and RCEM optical diagnostics. The model reproduces pressure and heat-release histories, captures NOx and THC trends, and qualitatively matches soot evolution and spatial distribution. The approach provides a practical, composition-driven tool for combustion and emissions studies of diverse carbon-neutral fuels.

In the latest common rail injection system diesel engines, combustion is controlled to meet emission regulations while suppressing combustion noise to the desired level by using multi-stage fuel injection into the cylinder. In such combustion control using multi-stage injection, predicting the intake air temperature is extremely important for optimizing pilot injections. In this study, as Step 1, we define the in-cylinder gas temperature at the time of intake valve closure as Tivc and propose a prediction formula for Tivc during steady-state operation that can be calculated onboard. Next, as Step 2, we develop a method to modify the prediction formula from Step 1 to accommodate transient operation.In this report, as Step 1, we considered the effect of heat exchange temperature with the combustion chamber wall during the intake stroke based on the Woschni formula. As a result, it was clarified that Tivc can be estimated as a linear sum of three components: intake manifold gas temperature, coolant temperature, and engine output. Furthermore, using the Tivc formula identified from actual engine tests, we predicted the heat release rate using the 0-dimensional cycle simulation UniDES developed by our company. The ignition timing of the pilot under various operating conditions from cold to warm matched well with the experiments, supporting the validity of the proposed formula.

A floating-liner measurement technique was developed, which quantifies piston friction force under fired engine operation over a wide speed range. To suppress thermal-stress–induced drift in the liner caused by combustion temperature, a double-liner structure was adopted. The liner assembly is held with high rigidity by a double-sided support configuration, in which force sensors support the double-liner from both sides. In addition, acceleration sensors installed on both the double-liner and its support structure are used for a newly introduced vibration-noise cancellation method. Using this apparatus and the proposed cancellation method, high repeatability of piston friction-force measurement up to 4000 r/min was confirmed, and the variation in FMEP was less than 0.5 kPa in terms of 3σ.

It is necessary to define the required characteristics of both tires and suspensions to efficiently improve road noise performance. In this paper, we first clarify the contributions of subsystem resonance to the whole structure resonance, where the tire and suspension are strongly coupled, by analyzing the energy exchange between subsystems at the hub coupling point. Furthermore, we analyze the proximity of the eigenfrequencies of the whole structure and the subsystems, as well as the similarity between the eigenvectors of the subsystems and the eigenvectors of the transfer functions at the coupling point, to understand the coupling mechanism. Based on this analysis, we present guidelines for the eigenvectors of tire subsystem at the coupling point that are advantageous for reducing road noise and confirm their validity.

In recent years, there has been remarkable progress in technology related to the stability of vehicles when driving at high-velocity. However, recently, some users have been driving their vehicles at high-velocity significantly exceeding the velocity limit on public roads in order to enjoy the high performance of their vehicles, causing tragic fatal accidents. This has become a social problem. In a previous study, the author used statistical traffic accident data to derive an approximate formula for the relationship between vehicle velocity and fatal or serious injury rates for vehicle-to-vehicle collisions and vehicle-pedestrian collisions, and clarified the danger of collisions occurring at velocity significantly exceeding the velocity limit. However, there have been cases where motorcycles and motorized bicycles have become victims of accidents caused by high-velocity runaway vehicles. For this reason, this paper analyzes traffic accident statistics data on motorcycles and motorized bicycles, and attempts to numerically clarify the risk of accidents caused by high-velocity runaway vehicles based on the relationship between injury severity and collision velocity.

We are studying a method to distinguish a condition in which a driver is looking ahead but has insufficient cognitive ability and has reduced attentional resources for driving (cognitive distraction) using eye movements. To reproduce a condition in which attentional resources are reduced, participants were assigned an n-back task in addition to an eye-tracking task in which the eyes follow a moving visual object on a display. The gaze center phenomenon, in which the gaze is located at the center of the visual field, was frequently observed. When this phenomenon was quantified by fixation time around the center of the visual field, it was suggested that it could be identified with more than 80% accuracy.

In order to chemically investigate the base-fuel dependence of the ignition suppression caused by ETBE addition, shock-tube experiments and numerical simulations based on detailed reaction model were performed. Measurements of ignition delay times showed that the ignition suppression effect of ETBE was less dependent on base-fuel components, such as paraffins, olefins, and aromatics, in contrast to that of ethanol. Reaction simulations demonstrated that this weak base-fuel dependence was caused by differences both in the dominant chain carriers and in their generation timing. In the ETBE-added systems, the contribution of hydroperoxyl radicals (HO₂) is relatively small, because highly reactive hydroxyl radicals (OH) also participate in chain reactions. This reduces the base-fuel dependence of the ignition suppression effect in the ETBE-added systems. Furthermore, in ETBE-added systems, the formation of chain carriers takes longer than in ethanol-added systems, resulting in a shorter reaction time between the ETBE-derived chain carriers and the hydrocarbons in the base-fuel. These two factors contribute to the weak base-fuel dependence of the ignition suppression when ETBE is added.

This study aimed to improve die durability during press forming of high-tensile steel with a tensile strength of 1470 MPa. Test dies were fabricated by carburizing the base material (SKD11) and applying vacuum quenching. By comparing results with dies treated only with TRD, differences in damage levels and changes in coating and base material properties were evaluated. Dies carburized before TRD-VC coating and those vacuum quenched after TRD-VC coating exhibited fewer cracks after press forming than dies treated with TRD alone, indicating potential for improved durability. Carburizing before TRD-VC coating increases coating hardness, coating thickness, and substrate hardness, suppressing die deformation and improving durability. Vacuum quenching after TRD-VC coating increases substrate hardness, contributing to deformation suppression, but heat during quenching causes coating damage and reduces coating thickness.

"Random Time Division MIM" (Random TD-MIMO) is a one of prosperous new technologies, which is suitable for automotive radars. It's gradually becoming well-known as a basic technology for large scale MIMO (Massive MIMO). But essential point is it's capability to extend velocity dynamic range, regardless of whether it is small scale MIMO or Massive MIMO. In automotive radar industry, wider velocity dynamic range is always an important topic, so even for small scale MIMO, it's worth to test Random TD-MIMO. In this paper, first we pointed out three major drawbacks of Random TD-MIMO, Then we propose an improved signal processing to solve these drawbacks. The proposed signal processing consists of higher dimensional Matching Pursuit algorithm, with reduced dimensional dictionary. Simulation results show that the proposed signal processing is an upward compatible technology to conventional one for Random TD-MIMO.