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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.

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.

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.

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.

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.

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.

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.

We developed a thermal calculation 1D simulator for an electric valve timing control system (VTC). A VTC can optimize the open and close timing of the intake and exhaust valves depending on the driving situation. Since a conventional VTC is driven hydraulically, the challenges are response speed and operation limit at low temperature. Our company has been developing an electric VTC for quick response and expansion of operating conditions. Currently, it is necessary to optimize the motor and reduction gear design to balance quicker response with downsizing. Therefore, a coupled simulator that can calculate electricity, mechanics, control, and thermo characteristics is required. In 1D simulation, a thermal network method is commonly used for thermal calculation. However, an electric VTC is attached to the end of a camshaft; therefore, determining thermal resistances is difficult. We propose a method of determining thermal resistances, using both theoretical and experimental approaches.

Recently emissions regulations are being strengthened. An air-fuel ratio cylinder imbalance causes emissions to increase due to universal exhaust gas oxygen (UEGO) sensor error or exhaust gas oxygen (EGO) sensor error. Various methods of reducing an air-fuel ratio cylinder imbalance have been developed. It is preferable for a control system to operate over a wide range of conditions. Our target is to expand the operating conditions from idling to high load conditions. Our approach is to use both an UEGO sensor and a crank angle sensor. A two-revolution frequency component calculated from the UEGO sensor output signal and angular acceleration calculated from the crank angle sensor output signal are used to identify the cylinder where the air-fuel ratio error occurs.

The authors developed a multi-swirl type injector characterized by a short spray penetration length and fine atomization to improve exhaust emissions and fuel consumption for port fuel injection (PFI) gasoline engines. In PFI gasoline engines, fuel adhesion to an intake manifold causes exhaust emission. In addition, good mixing of fuel and air causes high combustion efficiency, and as a result the fuel consumption improves. Injectors therefore require two improvements: first, a short spray penetration to avoid fuel adhesion to the intake manifold, and second, a fine atomization spray to generate a good mixture formation of fuel and air. In this study, the authors developed a multi-swirl type injector equipped with multiple orifice holes featuring swirl chambers upstream of each orifice. The key feature of the proposed injector is “involute curve-formed swirl chambers” for generating a uniform thin liquid-film in the orifices.

“Virtual Failure Mode and Effects Analysis” (vFMEA), a novel safety-verification method of control software for automotive electronic systems, was proposed to save prototyping cost at verification stage. The proposed vFMEA is system-level FMEA method, which uses virtualized electronic control units (ECUs) consisting of microcontroller models on a microcontroller simulator and a transistor-level circuit models on a circuit simulator. By using the structure, the control software in binary code formats can be verified when a circuit-level fault occurs in the ECU hardware. As an illustrative example, vFMEA was applied to an engine ECU. As a result of short-circuit fault into a driver IC, engine revolution and engine speed decreased. However, the engine continued to operate normally when an open-circuit fault occurred in a capacitor connected in parallel. Effects of the hardware faults in ECU on a vehicle are demonstrated; thereby software verification can be performed using vFMEA system.

A pioneering approach to implement transfer path analysis (TPA) is proposed in this paper through applying it to an automobile. We propose to use particle velocity as a measure of TPA, in addition to using sound pressure as a conventional measure for TPA. These two quantities together will give a comprehensive and complete definition of sound. Although sound pressure is a scalar, while particle velocity is a vector, it is also proposed that the same technique of the conventional sound pressure TPA should be independently applicable to each component of particle velocity vector. This has been experimentally verified with a study on our test box system. In this paper, we apply the proposed TPA to an actual vehicle to examine its applicability, advantages and limitations. The driving motor sound of a hybrid electric vehicle is chosen as the case study. A tri-axial particle velocity sensor which also measures sound pressure at the same point is utilized in the experiment.

We investigated the size of fuel spray droplets from nozzles for direct injection gasoline (DIG) engines. Our findings showed that the droplet size can be predicted by referencing the geometry of the nozzle. In a DIG engine, which is used as part of a system to reduce fuel consumption, the injector nozzle causes the fuel to spray directly into the combustion chamber. It is important that this fuel spray avoid adhesion to the chamber wall, so multi-hole injection nozzles are used to obtain spray shape adaptability. It is also important that spray droplets be finely atomized to achieve fast vaporization. We have developed a method to predict the atomization level of nozzles for fine atomization nozzle design. The multi-hole nozzle used in a typical DIG injector has a thin fuel passage upstream of the orifice hole. This thin passage affects the droplet size, and predicting the droplet size is quite difficult if using only the orifice diameter.

The purpose of this study is to develop model-based methodologies which employ thermo-fluid dynamic engine simulation and multiple-objective optimization schemes for engine control and calibration, and to validate the reliability of the method using a dynamometer test. In our technique, creating a total engine system model begins by first entirely capturing the characteristics of the components affecting the engine system's behavior, then using experimental data to strictly adjust the tuning parameters in physical models. Engine outputs over the full range of engine operation conditions as determined by design of experiment (DOE) are simulated, followed by fitting the provided dataset using a nonlinear response surface model (RSM) to express the causal relationship among engine operational parameters, environmental factors and engine output. The RSM is applied to an L-jetronic® air-intake system control logic for a turbocharged engine.

A new diagnosis method for an air-fuel ratio cylinder imbalance has been developed. The developed diagnosis method is composed of two parts. The first part detects an occurrence of an air-fuel ratio cylinder imbalance by using a two revolution frequency component of an EGO sensor output signal or an UEGO sensor output signal upstream from a catalyst. The two revolution frequency component is from a cycle where an engine rotates twice. The second part of the diagnosis method detects an increase of emissions by using a low frequency component which is calculated from the output of an EGO sensor downstream from the catalyst. When the two revolution frequency component calculated using the upstream sensor output is larger than a certain level and the low frequency component calculated using the downstream sensor output is shifted to a leaner range, the diagnosis judges that the emissions increase is due to an air-fuel ratio cylinder imbalance.

Model-based methodologies for the engine calibration process, employing engine cycle simulation and polynomial regression analysis, have been developed and the reliability of the proposed method was confirmed by validating the model predictions with dynamometer test data. From the results, it was clear that the predictions by the engine cycle simulation with a knock model, which considers the two-stage hydrocarbon ignition characteristics of gasoline, were in good agreement with the dynamometer test data if the model tuning parameters were strictly adjusted. Physical model tuning and validation were done, followed by the creation of a dataset for the regression analysis of charging efficiency, EGR mass, and MBT using a 4th order polynomial equation. The stepwise method was demonstrated to yield a logarithm likelihood ratio and its false probability at each term in the polynomial equation.

A new variable valve event and lift (VVEL) system has been developed by applying a multiple-link mechanism. This VVEL system can continuously vary the valve event angle and lift over a wide range from an exceptional small event angle and small lift and to a large event angle and large lift. This capability offers the potential to improve fuel economy, power output, emissions and other parameters of engine performance. The valve lift characteristics obtained with the VVEL system consist of a synthesis of the oscillatory motion characteristics of the multiple-link mechanism and the oscillating cam profile. With the multiple-link mechanism, the angular velocity of the oscillating cams varies during valve lift, but the valve lift characteristics incorporate both gentle ramp sections and sharp lift sections, the same as a conventional engine.

The increasing number of controllable parameters in modern engine systems leads to complicated and enlarged engine control software. This in turn has led to dramatic increases in software development time and costs in recent years. Model-based control design seems to be an effective way to reduce development time and costs. In the present study, we have developed model-based methodologies for the engine calibration process using an engine cycle simulation technique combined with a regression analysis of engine responses. From the results it was clear that the engine cycle simulation technique was useful in the engine calibration process, if the empirical parameters included in physical models were adjusted at typical sampling-points in several engine speeds and loads. The cycle simulation produced a multi-dimensional MBT map, and a response surface method was employed in the modeling of the engine map dataset using a polynomial equation.

A continuously variable valve event and lift (VEL) system, actuated by oscillating cams, can provide optimum lift and event angles matching the engine operating conditions, thereby improving fuel economy, exhaust emission performance and power output. The VEL system allows small lift and event angles even in the engine operating region where the required intake air volume is small and the influence of valvetrain friction is substantial, such as during idling. Therefore, the system can reduce friction to lower levels than conventional valvetrains, which works to improve fuel economy. On the other hand, a distinct feature of oscillating cams is that their sliding velocity is zero at the time of peak lift, which differs from the behavior of conventional rotating cams. For that reason, it is assumed that the friction and lubrication characteristics of oscillating cams may differ from those of conventional cams.