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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.

We developed a flexible system with EVs for solving imbalance between electricity demand and supply avoiding degradation of EV’s battery life. Such flexible systems are commonly being examined but nothing the system which uses battery considering impact of its battery life to avoid shorten EV’s operation period. Therefore, we developed one of methodologies to select preferable load facilities based on imbalance trend and flexible prices. The imbalance trend means a duration of the imbalance. The flexible prices mean operation cost to provide flexibility. By comparing the flexible prices and operation profit, it is possible to prevent unnecessary operation. As a result, we demonstrated our flexible system works as designed based on these parameters.

Autonomous Driving (AD) and Advanced Driver Assistance Systems (ADAS) are being actively developed to prevent traffic accidents. As the complexity of AD/ADAS increases, the number of test scenarios increases as well. An efficient development process that meets AD/ADAS quality and performance specifications is thus required. The European New Car Assessment Programme (Euro NCAP®1) and the Japan Automobile Manufacturers Association (JAMA®2) have both defined test scenarios, but some of these scenarios are difficult to carry out with real-vehicle testing due to the risk of harm to human participants. Due to the challenge of covering various scenarios and situations with only real-vehicle testing, we utilize simulation-based testing in this work. Specifically, we construct a Model-in-the-Loop Simulation (MILS) environment for virtual testing of AD/ADAS control logic.

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.

We propose a combined battery system (CBS) for low cost electric vehicles (EVs) to enhance battery life. The EVs popularly called as Neighborhood Electric Vehicle or Low-Speed-Electric-Vehicle are spreading in developing countries. Conventionally the EVs batteries consist of high energy density cells, and we call it as energy cells (EC). A major issue with the EVs is high operational costs mainly due to high battery cost and short lifespan of the ECs. In this study, we develop a CBS consisting of a combination of following two kinds of batteries: i) EC which is the main energy source for the EV, and ii) a battery having high power density also called as power cells (PC) which is more suitable to bear high charge-discharge currents. The key feature of the proposed system is to minimize the size of additional battery by using our high power lithium ion battery. We performed experiments to estimate EC life for several capacity values of the PC.

We have developed a drive cycle (DC) to test Hitachi’s combined battery system (CBS) for electric vehicles (EVs) having battery lifespan enhancements. Conventionally EV batteries consist of high energy density cells, and we call them as energy cells (EC). A major issue with the EVs is high operational costs mainly due to short lifespan of the ECs. CBS almost doubles the EC and thus overall battery system lifespan, as per the evaluation over a WLTP based method. We want to test the CBS under Indian conditions which has predominantly hot weather, and traffic jam scenarios. Battery deterioration and thus its lifespan is sensitive to traffic conditions and ambient temperature. Hence, it was needed to evaluate the CBS over an Indian DC and use 40°C as ambient temperature. However, it was difficult to carry out the tests since there is no standard Indian DC for small / light weight four wheelers.

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.

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.

We have developed an excitation source identification system that can distinguish excitation sources on a sub-assembly level (around 30mm) for vehicle components by combining a measurement and a timing analysis. Therefore, noise and vibration problems can be solved at an early stage of development and the development period can be shortened. This system is composed of measurement, control, modeling, and excitation source identification parts. The measurement and the excitation source identification parts are the main topics of this paper. In the measurement part, multiple physical quantities can be measured in multi-channel (noise and vibration: 48ch, general purpose: 64ch), and these time data can be analyzed by using a high-resolution signal analysis (Instantaneous Frequency Analysis (IFA)) that we developed.

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.

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.

The ISO 26262 is a functional safety standard for road vehicles. The standard requires manufacturers to conduct quantitative assessment of the diagnostic coverage (DC) of products. The DC is defined as the percentage of failure probability covered by safety mechanisms. However, DC evaluation methods for drift faults, in which the change in element values is not constant, have not been discussed. In this paper, we propose a DC evaluation method for analog circuits with drift faults. With this method, we first parameterize the effect of drift faults onto a bounded region then split the region into safe fault, hazardous detectable fault, and hazardous undetectable fault regions. We evaluate the classification rate distribution by the area ratios of these regions.

Electromagnetic compatibility (EMC) is becoming more important in power converters and motor drives as seen in hybrid electric vehicles (HEV) to achieve higher reliability of the vehicle and its components. Electromagnetic interference (EMI) of the electronic components for a vehicle are evaluated and validated at a component-level test bench; however, it is sometimes observed that the EMI level of the components can be changed in a vehicle-level test due to differences in the vehicle's configuration (cable routing, connecting location etc.). In this presentation, a vehicle-level EMC simulation methodology is introduced to estimate radiated emissions from a vehicle. The comparison between the simulation and measurement results is also presented and discussed.

We have achieved injection quantity range enhancement by using the current waveform control technique for direct injection (DI) gasoline injectors. In this study, we developed an injection quantity simulator to find out the mechanism of non-linear characteristics. We clarified the non-linear production mechanism by using the simulator. This simulator is a one-dimensional simulator that incorporates calculation results from both unsteady electromagnetic field analysis and hydraulic flow analysis into the motion equation of this simulation code. We investigated the relation between armature and the injection quantity by using the simulator. As a result, we clarified that the non-linearity was produced by the bounce of the armature in the opening action. Thus, we found that it is effective to reduce the armature bounce to improve the linearity of the injection quantity characteristics.

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.

We have developed a model-based control for the air intake system in a variable valve engine, employing total engine simulation, the response surface method and multi-objective optimization scheme. In our technique, we performed the simulation model tuning and validation, followed by the creation of a dataset for the polynomial regression analysis of the charging efficiency. A D-optimal design, robust least squares method, and likelihood-ratio test were demonstrated to yield a robust and accurate control model. Coupling the total engine simulator with a genetic algorithm, model based calibration for optimal valve timing stored in lookup table was carried out under multiple objectives and restrictions. The reliability of the implementation control model, which considers the effect of gas dynamics in the intake system, was confirmed using a model-in-the-loop simulation.

Electric vehicle will come into wide use in worldwide with the arrival of the Low-carbon society in the next twenty years. And total capacity of the battery on the electric vehicle in the power system network amounts for several Giga Watts, which corresponds to the capacity of several nuclear power plants. It is difficult for power system operator to forecast of the amount of the charging power because there is much uncertainty of using power on electric vehicles compared to the electric facility like air conditioner and so on. In order to operate the power system network stable, it is necessary for power system operator to control charging power of electric vehicle independently as controllable facilities. We propose a “Smart Charging” concept based on the index for the security monitoring of power system network which makes power system operation more efficiently and makes electric vehicle owners more conveniently.