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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.

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.

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.

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.

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.

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.

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 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.

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 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 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.

“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.