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The flight area of drones and other unmanned aerial vehicles (UAVs) had been highly restricted but has been relaxing, including flights beyond the scope of sight. Deregulation without aircraft-reliability improvement increases the risk of accidents. However, demanding high reliability for all aircraft leads to an increase in the price of the aircraft. Therefore, if airspace restrictions are relaxed for more reliable aircraft, the cost of higher reliability and its benefits can be balanced. This will improve efficiency and optimize cost-effectiveness. The purpose of this proposal is to balance the cost of aircraft-reliability improvement (which allows flight to continue in the event of a failure) and its advantages. Specifically, the author proposes rules that apply more relaxed airspace restrictions to UAVs with higher FCLs (Flight Continuity Possibility Levels) and stricter airspace restrictions to those with lower FCLs.

In electrified automobiles, wind noise significantly contributes to the overall noise inside the cabin. In particular, underbody airflow is a dominant noise source at low frequencies (less than 500 Hz). However, the wind noise transmission mechanism through a battery electric vehicle (BEV) underbody is complex because the BEV has a battery under the floor panel. Although various types of underbody structures exist for BEVs, in this study, the focus was on an underbody structure with two surfaces as inputs of wind noise sources: the outer surface exposed to the external underbody flow, such as undercover and suspension, and the floor panel, located above the undercover and battery. In this study, aero-vibro-acoustic simulations were performed to clarify the transmission mechanism of the BEV underbody wind noise. The external flow and acoustic fields were simulated using computational fluid dynamics.

This paper describes a method for evaluating the equivalent temperature in vehicle cabins based on the new international standard ISO 14505-4, published in 2021. ISO 14505-4 defines two simulation methods to determine a thermal comfort index “equivalent temperature.” One method uses a numerical thermal manikin, and the other uses thermal factors to calculate. This study discusses the latter method to validate its accuracy, identify the key points to consider, and examine its advantages and disadvantages. First, the definition of equivalent temperature and the equation to calculate the equivalent temperature using thermal factors, such as air temperature, radiant temperature, solar radiation, and air velocity, are explained. In addition, the experiments and simulation methods are described.

Nissan’s variable compression turbo (VC-Turbo) engine has a multilink mechanism that continuously adjusts the top and bottom dead centers of the piston to change the compression ratio and achieve both fuel economy and high power performance. Increasing the exhaust gas recirculation (EGR) rate is an effective way to further reduce the fuel consumption, although this increases the exhaust gas condensation in the cylinder bores, causing a more corrosive environment. When the EGR rate is increased in a VC-Turbo engine, the combined effect of piston sliding and exhaust gas condensation at the top dead center accelerates the corrosive wear of the thermal spray coating. Stainless steel coating is used to improve the corrosion resistance, but the adhesion strength between the coating and the cylinder bores is reduced.

Suspension is an important chassis part which is vital to ride comfort [1]. However, it is difficult to achieve our targeted comfortability level in a short time. Therefore, improving efficiency of damper development is our primary challenge. We have launched a project which aims to reduce the workload on developing dampers by introducing analytical approaches to the improvement of ride comfort. To be more specific, we have been putting effort into developing the damping force prediction, the vehicle dynamics prediction and subjective rating prediction. This paper describes subjective rating prediction method which output a subjective rating corresponding to the physical value of the vehicle dynamics with deep learning. As a result of verification using objective data which was not used for learning process, DNN (Deep Neural Network) prediction method could fairly precisely predict subjective rating of the expert driver.

The adoption of electric vehicles (EVs) has been announced worldwide with the aim of reducing CO2 emissions. However, a significant increase in electricity demand by EVs might impact the stable operation of the existing power grid. Meanwhile, EV charging is acceptable to most users if it is completed by the time of the next driving event. From the viewpoint of power grid operators, flexibility for shifting the timing of EV charging would be advantageous, including making effective use of renewable energy. In this work, an EV model and simulation tool were developed to make clear how the total charging demand of all EVs in use will be influenced by future EV specifications (e.g., charge power) and installation of charging infrastructure. Among the most influential factors, EV charging behavior according to use cases and regional characteristics were statistically analyzed based on the real-world usage data of over 14, 000 EVs and incorporated in the simulation tool.

This study focused on European NCAP activities of introducing a new head protection evaluation procedure, as proposed by BASt (Federal Highway Research Institute - GERMANY). Various kinds of E-bikes are available in the market, ranging from E-bikes that have a small motor to assist the rider’s pedal-power i.e., pedelecs to somewhat more powerful E-bikes which is similar to a moped-style scooter. This paper focused on identifying the factors influencing bicyclist head kinematics during bicycle vs. passenger vehicle (PV) collisions at the intersection. Two AM50 bicyclist FE models are developed using i) GHBMC Human Body Model (HBM) and ii) WorldSID (WS) side impact dummy. Head kinematics of bicyclists of pedal-assist E-bike and normal bike were compared using CAE simulation. It is found that the vehicle’s impact velocity, type of bicycle, the mass of E-bike and bicycle traveling speed will influence the head kinematics.

The present paper is Part 1 of two consecutive studies. Part 1 describes three subjects: definition of the equivalent temperature (teq), measurements of teq using a clothed thermal manikin in a vehicle cabin, and modeling of the clothed thermal manikin for teq simulation. After defining teq, a method for measuring teq with a clothed thermal manikin was examined. Two techniques were proposed in this study: the definition of “the total heat transfer coefficient between the skin surface and the environment in a standard environment (hcal)” based on the thermal insulation of clothing (Icl), and a method of measuring Icl in consideration of the area factor (fcl), which indicates the ratio of the clothing surface to the manikin surface area. Then, teq was measured in an actual vehicle cabin by the proposed method under two conditions: a summer cooling condition with solar radiation and a winter heating condition without solar radiation.

Wheels play an important role in determining the aerodynamic drag of passenger vehicles. This is because the contribution of wheels to aerodynamic drag comes from not only the wheels themselves, but also from the interference effect between wheel wakes and the base wake. As far as the authors are aware, there have been no reports about aerodynamic drag sensitivity to wheel shape factors for different vehicle types and different exterior body shapes. The purpose of this study was to clarify CD sensitivity to wheel shape factors for a sedan and an SUV, including different rear fender shapes. Many different wheel configurations were investigated in terms of the CD, base pressure and flow fields in wind tunnel tests. Multiple regression analyses were conducted to clarify CD sensitivity to each wheel shape factor based on the test data. This study revealed high CD sensitivity factors for both the sedan and SUV.

A new 2L gasoline turbo engine, named KR20DDET was developed with the world’s first mass-producible variable compression turbo (VC-Turbo) technology using a multi-link variable compression ratio (VCR) mechanism. It is well known that increasing the compression ratio improves gasoline engine thermal efficiency. However, there has always been a compromise for engine designers because of the trade-off between increasing the compression ratio and knocking. At Nissan we have been working on VCR technology for more than 20 years and have now successfully applied this technology to a mass production engine. This technology uses a multi-link mechanism to change the top and bottom dead center positions, thereby allowing the compression ratio to be continuously changed. The VC-Turbo engine with this technology can vary the compression ratio from 14:1 for obtaining high thermal efficiency to 8:1 for delivering high torque by taking advantage of the strong synergy with turbocharging.

Predicting the vibration of a motor gearbox assembly driven by a PWM inverter in the early stages of development is demanding because the assembly is one of the dominant noise sources of electric vehicles (EVs). In this paper, we propose a simulation model that can predict the transient vibration excited by gear meshing, reaction force from the mount, and electromagnetic forces including the carrier frequency component of the inverter up to 10 kHz. By utilizing the techniques of structural model reduction and state space modeling, the proposed model can predict the vibration of assembly in the operating condition with a system level EV simulator. A verification test was conducted to compare the simulation results with the running test results of the EV.

This paper presents the “Virtual Failure Mode and Effects Analysis (vFMEA)” system, which is a high-fidelity electrical-failure-simulation platform, and applies it to the software verification of an electric power steering (EPS) system. The vFMEA system enables engineers to dynamically inject a drift fault into a circuit model of the electronic control unit (ECU) of an EPS system, to analyze system-level failure effects, and to verify software-implemented safety mechanisms, which consequently reduces both cost and time of development. The vFMEA system can verify test cases that cannot be verified using an actual ECU and can improve test coverage as well. It consists of a cycle-accurate microcontroller model with mass-production software implemented in binary format, analog and digital circuit models, mechanical models, and a state-triggered fault-injection mechanism.

The purpose of this work was to gain a fundamental understanding of which fuel property parameters are responsible for particulate emission characteristics, associated with key intermediate behavior in the engine cylinder such as the fuel film and insufficient mixing. Accordingly, engine tests were carried out using various fuels having different volatility and chemical compositions under different coolant temperature conditions. In addition, a fundamental spray and film visualization analysis was also conducted using a constant volume vessel, assuming the engine test conditions. As for the physical effects, the test results showed that a low volatility fuel displayed high particulate number (PN) emissions when the injection timing was advanced. The fundamental test clearly showed that the amount of fuel film on the impingement plate increased under such operating conditions with a low volatility fuel.

Automotive fuel can be efficiently combusted by injecting it into the cylinders at high pressure to atomize it to pass the regulations for exhaust gas and fuel economy. For this reason, automotive companies have developed direct injection engines, which can inject gasoline into the cylinders directly. Furthermore, the demand for lower-noise high pressure pumps is also increasing from the viewpoint of automotive comfort. Since the valve velocity and noise level will increase as the pressure in fuel pumps increases, noise problems need to be solved under the high pressure conditions. Accordingly, the valve motion should be predicted with high accuracy under operating conditions to evaluate the noise caused by valve impingement. In addition, the squeeze film effect phenomenon will occur in the physical fuel pumps affect the prediction of the noise level caused by valve impingement.

With the development of downsized spark ignition (SI) engines, low-speed pre-ignition (LSPI) has been observed more frequently as an abnormal combustion phenomenon, and there is a critical need to solve this issue. It has been acknowledged that LSPI is not directly triggered by autoignition of the fuel, but by some other material with a short ignition delay time. It was previously reported that LSPI can be caused by droplets of lubricant oil intermixed with the fuel. In this work, the ignition behavior of lubricant component containing fuel droplets was experimentally investigated by using a constant volume chamber (CVC) and a rapid compression and expansion machine (RCEM), which enable visualization of the combustion process in the cylinder. Various combinations of fuel compositions for the ambient fuel-air mixture and fractions of base oil/metallic additives/fuel for droplets were tested.

Technologies for improving the fuel economy of gasoline engines have been vigorously developed in recent years for the purpose of reducing CO2 emissions. Increasing the compression ratio is an example of a technology for improving the thermal efficiency of gasoline engines. A significant issue of a high compression ratio engine for improving fuel economy and low-end torque is prevention of knocking under a low engine speed. Knocking is caused by autoignition of the air-fuel mixture in the cylinder and seems to be largely affected by heat transfer from the intake port and combustion chamber walls. In this study, the influence of heat transfer from the walls of each part was analyzed by the following three approaches using computational fluid dynamics (CFD) and experiments conducted with a multi-cooling engine system. First, the temperature rise of the air-fuel mixture by heat transfer from each part was analyzed.

We developed the numerical simulation tool by using OpenFOAM® and in-house simulation codes for Gasoline Direct Injection (GDI) engine in order to carry out the precise investigation of the throughout process from the internal nozzle flow to the fuel/air mixture in engines. For the piston/valve motions, a mapping approach is employed and implemented in this study. In the meantime, the spray atomization including the liquid-columnbreakup region and the secondary-breakup region are simulated by combining the different numerical approaches applied to each region. By connecting the result of liquid-column-breakup simulation to the secondary-breakup simulation, the regions which have different physical phenomena with different length scales are seamlessly jointed; i.e., the velocity and position of droplets predicted by the liquid-column-breakup simulation is used in the secondary breakup simulation so that the initial velocity and position of droplets are transferred.

Variable flux permanent magnet synchronous machines (VFPMSMs) have been designed by using finite element analysis (FEA) to evaluate speed-torque capability considering requirement for magnetization state (MS) manipulation. However, due to its unique characteristic to change the MS, numerous combinations of design parameters need to be evaluated to achieve a final design. To accelerate the design process, this paper presents a method that consists of an equivalent magnetic circuit model and a process to obtain magnet width and thickness that satisfy target maximum torque and power factor (P.F.) capability. This model includes magnet operating point analysis under given magnet width and thickness condition to achieve target MS and avoid demagnetization at full load. This analysis provides desired stator magnetomotive force, magnet and stator induced flux linkage. Therefore, expected torque and P.F. capability is calculated.

Highly automated driving systems have a responsibility to keep a vehicle safe even in abnormal conditions such as random or systematic failures. However, creating redundancy in a system to respond to failures increases the cost of the system, and simple redundancy cannot detect systematic failures because some systematic failures occur in each system at the same time. Systematic failures in automated driving systems cannot be verified sufficiently during the development phase due to numerous patterns of parameters input from outside the system. A safety concept based on a “safety sustainer” for highly automated driving systems is proposed. The safety sustainer is designed for keeping a vehicle in a safe state for several seconds if a failure occurs in the system and notifying the driver that the system is in failure mode and requesting the driver to take over control of the vehicle.

Mechanism of suddenly occurring behavior of low speed pre-ignition (LSPI) in boosted spark ignition (SI) engines was analyzed with various experimental methodologies. Endoscope-visualized 1st cycle of LSPI showed droplet-like luminous flame kernels as the origin of flame propagation before spark ignition. With the oil lubricated visualization engine, droplets flying were observed only after enough accumulation of fuel at piston crevice. Also, it was confirmed that subsequent cycles of LSPI occur only after enough operation time. These results indicated that local accumulation of liner adhered fuel and saturation of oil dilution can be a contributing factor to the sudden occurrence of LSPI.