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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.

For the survival of internal combustion engines, the required research right now is for alternative fuels, including drop-ins. Certain types of alternative fuels have been estimated to confirm the superiority in thermal efficiency. In this study, using a single-cylinder engine, olefin and oxygenated fuels were evaluated as a drop-in fuel considering the fuel characteristic parameters. Furthermore, the effect of various additive fuels on combustion speed was expressed using universal characteristics parameters.

To realize stable combustion in lean or diluted conditions, reducing cycle-to-cycle variations of flow and fuel distribution is important. In this study, the effect of initial flow field was examined by simultaneous Time-Resolved PIV and visualization on two cross-sections in a fully optical-access engine under motoring and firing conditions with homogeneous pre-mixture. As a result, Omega index was defined and plotted on the correlation map between turbulence kinetic energy and CA10 (duration from ignition timing to 10% to the total accumulated heat). The omega index describes the strength of a horizontal flow field that resembles the shape of the Greek letter Omega. The plots with high Omega index were found frequently in the CA10 retarded cycles. On the other hand, the plots with low Omega index have simple tumble flows and the correlation was clearly found.

We propose low inductance batteries and enhance power density for a inverter. Conventionally, the capacitors are used for smoothing ripple of the inverter. The low inductance battery which responds at carrier frequency of inverter can reduce the capacity of the smoothing capacitors and enable to enhance power density for the inverter. For reducing the inductance, it is necessary to separately understand the impact of electrochemical reaction under wide range of assumed conditions and structural reaction on frequency characteristics. Furthermore, it is also necessary to design the low inductance batteries based on combining the both of characteristics. However, there are no study focusing on modeling by combining such different domains. Therefore, we made original inductance model inside battery considering frequency characteristics among all materials and structural influence with electromagnetic field analysis simulator.

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.

To increase thermal efficiency of internal combustion engines, dilution combustion systems, such as lean burn and exhaust gas recirculation systems, have been developed. These systems require spark-ignition coils generating large discharge current and discharge energy to achieve stable ignition under diluted mixture conditions. Several studies have clarified that larger discharge current increases spark-channel stretch and decreases the possibility of spark channel blow-off and misfire. However, these investigations do not mention the effect of larger discharge current and energy on the initial combustion period. The purpose of this study was to investigate the relation among dilution ratio, initial-combustion period, and coil specifications to clarify the control factor of the dilution limit.

We have developed a cooperative simulation environment for multiple electronic control units (ECUs) including a parallel executions mechanism to improve the test efficiency of a system, which was designed with multiple ECUs for autonomous driving. And we have applied it to a power window system for multiple ECUs with a controller area network (CAN). The power window model consists of an electronic-mechanical model and a CPU model. Each simulator with a different executions speed operates in parallel using a synchronization mechanism that exchanges data outputted from each simulator at a constant cycle. A virtual ECU simulated microcontroller hardware operations and executed its control program step-by-step in binary code to test software for the product version. As co-simulation technology, a mechanism that synchronously executes heterogeneous simulators and a model of an in-vehicle communication CAN connecting each ECU were developed.

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.

In recent years, improvement of in-use fuel economy is required with tightening of exhaust emission regulation. We assume that one of the most effective solutions is ACC (Adaptive Cruise Control), which can control a powertrain accurately more than a driver. We have been developing a fuel saving ADAS (Advanced Driver Assistance System) application named “Sailing-ACC”. Sailing-ACC system uses sailing stop technology which stops engine fuel injection, and disengages a clutch coupling a transmission when a vehicle does not need acceleration torque. This system has a potential to greatly improve fuel efficiency. In this paper, we present a predictive powertrain state switching algorithm using external information (route information, preceding vehicle information). This algorithm calculates appropriate switching timing between a sailing stop mode and an acceleration mode to generate a “pulse-and-glide” pattern.

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.

An improvement of thermal efficiency of internal combustion engines is strongly required. Meanwhile, from the viewpoint of refinery, CO2 emissions and gasoline price decrease when lower octane gasoline can be used for vehicles. If lower octane gasoline is used for current vehicles, fuel consumption rate would increase due to abnormal combustion. However, if a Homogeneous Charge Compression Ignition (HCCI) engine were to be used, the effect of octane number on engine performance would be relatively small and it has been revealed that the thermal efficiency is almost unchanged. In this study, the engine performance estimation of HCCI combustion using lower octane gasoline as a vision of the future engine was achieved. To quantitatively investigate the fuel consumption performance of a gasoline HCCI engine using lower octane fuel, the estimation of fuel consumption under different driving test cycles with different transmissions is carried out using 1D engine simulation code.

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.

The problem of high fatal accident rates due to drunk driving persists, and must be reduced. This paper reports on a prototype system mounted on a car mock-up and a prototype portable system that enables the checking of the drivers’ sobriety using a breath-alcohol sensor. The sensor unit consists of a water-vapor-sensor and three semiconductor gas sensors for ethanol, acetaldehyde, and hydrogen. One of the systems’ features is that they can detect water vapor from human-exhaled breath to prevent false detection with fake gases. Each gas concentration was calculated by applying an algorithm based on a differential evolution method. To quickly detect the water vapor in exhaled breath, we applied an AC voltage between the two electrodes of the breath-water-vapor sensor and used our alcohol-detection algorithm. The ethanol level was automatically calculated from the three gas sensors as soon as the water vapor was detected.

A virtual power window control system was built in order to look into and demonstrate applications of microcontroller models. A virtual ECU simulated microcontroller hardware operations. The microcontroller program, which was written in binary digital codes, was executed step-by-step as the virtual ECU simulation went on. Thus, production-ready codes of ECUs are of primary interest in this research. The mechanical system of the power window, the DC motor to lift the window glass, the H-bridge MOSFET drivers, and the current sensing circuit to detect window locking are also modeled. This means that the hardware system of the control system was precisely modeled in terms of mechanical and circuit components. By integrating these models into continuous and discrete co-simulation, the power window control system was analyzed in detail from the microscopic command execution of the microcontroller to the macroscopic motion of the window mechanism altogether.

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.

In previous study, a method of combustion detection for homogeneous charge compression ignition (HCCI) using a crank angle sensor and a knock sensor has been estimated [1]. In addition, an ion-current sensor has been used as a countermeasure against abnormal combustion with downsizing and higher compression ratio engines. An ion-current sensor has been newly adopted in engine systems. In this study, detection performance of combustion conditions in HCCI and spark ignition (SI) using with the ion-current sensor was estimated. The purpose of this study was to confirm detectable combustion conditions using with the ion-current sensor, and to confirm a requirement of applied voltage for the ion-current sensor. A detection signal of the ion-current sensor was changed by combustion style (HCCI,SI). Experimental results showed a heat release rate increased with ion signals increasing approximately at the same time in HCCI and SI.

In this study, in order to clarify the mechanism of preignition occurrence in highly boosted SI engine at low speed and high load operating conditions, directphotography of preignition events and light induced fluorescence imaging of lubricant oil droplets during preignition cycles were applied. An endoscope was attached to the cylinder head of the modified production engine. Preigntion events were captured using high-speed video camera through the endoscope. As a result, several types of preignition sources could be found. Preignition caused by glowing particles and deposit fragments could be observed by directphotography. Luminous flame was observed around the piston crevice area during the exhaust stroke of preignition cycles.

A recent trend in high-pressure gasoline pumps is increasing the outlet pressure. One of the most important topics for increasing this pressure is improving volumetric efficiency. Therefore, the purpose of this research is to quantify the breakdown of efficiency loss factors and to suggest a new design for improving volumetric efficiency. Authors developed a method of quantifying the efficiency loss breakdown of high-pressure gasoline pumps by using 1D fluid pressure simulation results and conducting evaluation experiments regarding sensitivity. Authors separated pump movement into three phases; suction, compression, and delivery. Authors then investigated the loss factors in each phase. As a result, authors obtained an equation for predicting the final output volume. The equation consists of a limit output volume and other types of leakage volumes.

The authors investigated the reasons of how a preignition occurs in a highly boosted gasoline engine. Based on the authors' experimental results, theoretical investigations on the processes of how a particle of oil or solid comes out into the cylinder and how a preignition occurs from the particle. As a result, many factors, such as the in-cylinder temperature, the pressure, the equivalence ratio and the component of additives in the lubricating oil were found to affect the processes. Especially, CaCO3 included in an oil as an additive may be changed to CaO by heating during the expansion and exhaust strokes. Thereafter, CaO will be converted into CaCO3 again by absorbing CO2 during the intake and compression strokes. As this change is an exothermic reaction, the temperature of CaCO3 particle increases over 1000K of the chemical equilibrium temperature determined by the CO2 partial pressure.