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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.

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 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.

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.

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.

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.

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.

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.

A technique of estimating particulate matter (PM) from gasoline direct injection engines is proposed that is used to compute mass density and particle number density of PM by using fuel mass in rich mixtures obtained by using non-combustion computational fluid dynamics (CFD). The CFD code that was developed by the authors employed a Cartesian coordinates system as a discretization method and large eddy simulation (LES) as a turbulence model. Fuel spray droplets were treated with the discrete droplet model (DDM). The code was verified with some experimental data such as those obtained from in-cylinder gas-flows with a laser Doppler velocimeter (LDV) and in-cylinder fuel concentration with laser induced fluorescence (LIF). PM emissions from a single-cylinder gasoline direct injection engine were measured with an electrical low pressure impactor (ELPI) to determine the model constants that were required in the estimation model.

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.

The cooled EGR system has been focused on as a method for knocking suppression in gasoline engines. In this paper, the effect of cooled EGR on knocking suppression that leads to lower fuel consumption is investigated in a turbo-charged gasoline engine. First, the cooled EGR effect is estimated by combustion simulation with a knock prediction model. It shows that the ignition timing at the knocking limit can be advanced by about 1 [deg. CA] per 1% of EGR ratio, combustion phasing (50% heat release timing) at the knocking limit can be advanced by about 0.5 [deg. CA] per 1% of EGR ratio, and the fuel consumption amount can be decreased by about 0.4% per 1% of EGR ratio. Second, the effect of cooled EGR is verified in an experimental approach. By adding inert gas (N2/CO2) as simulated EGR gas upstream of the intake pipe, the effect of EGR is investigated when EGR gas and fresh air are mixed homogeneously. As a result, the ignition timing at the knocking limit is advanced by 7 [deg.

The robustness control for homogeneous charge compression ignition (HCCI) using a crank angle sensor and a knock sensor has been estimated. On the other hand, an ion current sensor is used as a countermeasure against abnormal combustion with downsized and higher compression ratio engines. This sensor can generally be adopted in engine systems. Therefore, we examined the application of an ion current sensor to robustness control for HCCI. The purpose of this research was to develop a method of detecting combustion conditions to make HCCI engines more robust. Therefore, we evaluated the performance of the ion current sensor. Experimental results comparing ion intensity detection in HCCI. The detection value of the ion current sensor changed based on the form of combustion. Experimental results showed that the heat release rate increased with an increase in ion signals appear during the same time at approximately in both spark ignition (SI) and HCCI.

The internal combustion engines waste large amounts of heat energy, which account for 60% of the fuel energy. If this heat energy could be converted to the output power of engines, their thermal efficiency could be improved. The thermal efficiency of the Otto cycle increases as the compression ratio and the ratio of specific heat increase. If high octane number fuel is used in engines, their thermal efficiency could be improved. Moreover, thermal efficiency could be improved further if fuel could be combusted in dilute condition. Therefore, exhaust heat recovery, high compression combustion, and lean combustion are important methods of improving the thermal efficiency of SI engines. These three methods could be combined by using hydrous ethanol as fuel. Exhaust heat can be recovered by the steam reforming of hydrous ethanol. The reformed gas including hydrogen can be combusted in dilute condition. In addition, it is cooled by directly injecting hydrous ethanol into the engine.

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.