The main purpose of this study is to investigate the effect of visual stimulus on voluntary eye movement during driving. In this paper, we examine two cases: driving with/without visual stimulus by means of a driving simulator. We develop a model that consists of both vestibulo-ocular reflex (VOR) and optokinetic reflex (OKR) components. By comparing the observed eye movement and the simulation result of the model, the results of eye movement simulation was more accurate than VOR model only even in a naturalistic situation with optic flow of the visual scene and the driver’s voluntary eye movement.

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The paper describes the simulation approach for quenching of aluminum and steel parts. The two materials require different treatment due to the release of latent heat during the cooling of steel. The boiling process within the liquid domain is treated with the CFD tool AVL FIRETM regardless of the solid material being quenched. For aluminum parts the solid is simulated using the same software, whereas for steel the latent effect requires usage of DANTE^Ⓡ running within a commercial Finite Element tool. Liquid and solid domains are online coupled in both configurations.

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This study investigated the electricity consumption properties of ultra-compact electric vehicles (UCEVs) in the real world. Vehicle running data collected in a social experiment of UCEVs implemented in Kato City, Japan, were used for an empirical study. The major findings suggest: 1) the average electricity consumption rate of UCEVs is 89.8 Wh/km; 2) UCEVs can reduce the CO₂ emissions from vehicle use by approximately 67.0%; 3) gasoline cost savings amount by adopting UCEVs varies from 9,000 to 86,000 Yen annually for participants owning gasoline cars; 4) UCEVs have a lower maximal and average speeds than gasoline cars.

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In this research, we conduct unsteady CFD to investigate the effect of engine bay flow on the steady and unsteady aerodynamics of the extended DrivAer model reproducing engine bay flow. Dynamic Mode Decomposition (DMD) is performed to analyze unsteady aerodynamics. As a result, it is revealed that different engine bay setups results in not only differences of steady aerodynamics but also the differences of unsteady aerodynamic characteristics. Furthermore, we perform an on-the-fly algorithm of DMD called Streaming Total DMD (STDMD) which can be conducted with much less memory than conventional DMD to investigate the relevancy and applicability of STDMD on the analysis of unsteady aerodynamics of a road vehicle.

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Interior sound measurements play an important role in vehicle development and refinement. Sometimes hundreds of microphones are installed in an automotive cabin. During test preparation and execution, a lot of time is spent in determining the microphone positions and in tracking cables to the data acquisition channel. A smart acoustic localization approach is presented to automate this process and to realize considerable time gains. It is based on estimating the distance between a microphone and (at least 4) sources by acoustic time-of-arrival measurements, combined with novel algorithms that cope with reflections and non-line-of-sight issues. The method will be illustrated using in-vehicle measurements.

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In this paper, two versions of the Abbreviated Injury Scale codes (AIS98 and AIS08) were used to develop Injury Severity Prediction algorithms with the help of NASS-CDS (US) 2009-2012 database. Some severe injuries in the AIS98 are scaled as less severe in the AIS08, especially in head and thorax regions; but in other body regions, there are no significant changes. Changes in AIS severity level will affect the distribution around the Injury Severity Score equal to 15, the threshold level for serious/minor injury judgment and hence leads to change in Injury Severity Prediction (ISP) prediction value related to AACN. The total number of false cases reduced for ISP algorithm formulated with AIS08 code when compared to that of AIS98 code. The proposed modified ISP algorithm is more efficient for both the AIS codes (98 and 08) than the original publicly available Kononen’s algorithm.

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This paper presents an in-cylinder pressure pegging algorithm based on cyclic polytropic coefficient learning for combustion engines. In order to take the cycle-to-cycle variation of the polytropic coefficient into account in the incylinder measurement, an iterative learning algorithm is proposed to provide cyclic estimation of the polytropic coefficient and then with the estimation cyclic compensation method is proposed for the offset of in-cylinder pressure measurement. A comparative study of the proposed algorithm, the least-squares method (LSM) with a fixed polypropic coefficient and the nonlinear least-squares method (NLSM) with a variable polytropic coefficient is conducted using the simulated pressure data. Experimental validations are conducted on a six-cylinder gasoline engine at a motored condition and a steady fired operation condition.

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Fatigue strength is affected by assembling stress at flanges. Using samples of exhibiting different degrees of flange surface flatness, local stress was measured with strain gauges, and the effect of assembling strain and stress on fatigue strength was verified through fatigue strength examinations. Bending fatigue strengths were inversely proportional to static assembling stress which was proportional to the degree of flange flatness. Factors causing fatigue to failure, such as welding bead shape, metal structure, and crack state were identified through microscope observations and SEM-EDS chemical composition analyses, while assembling deformation and stress concentration were analyzed through FEM computer simulation.

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