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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.

To improve the fuel economy, we developed a turbo-charged spark ignition engine combined with a low pressure loop EGR system. A negative pressure control valve has been applied to achieve high EGR ratio in wide engine operation condition. In this paper, a new developed model-based control system for low pressure loop EGR with a negative pressure control valve will be described.

There are two primary technical issues in the application of position sensorless control to generators for 100% electric-drive hybrid vehicles. The first is the risk of losing control when position sensorless estimation methods are changed in accordance with the generator speed, while. The second is the reduction in the maximum torque if the rate of change in the generator speed is extremely large in a relatively low-rotation-speed area. This study proposes countermeasures for each issue and their effects examines them via simulations and experiments.

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.

The size and weight of the traction inverter needs to be reduced to ensure a sufficient cruising range of an electric vehicle. To this end, one approach involves changing materials of the inverter case from aluminum to resin. However, the resin in use of inverter case causes technical issues in terms of collision performance, electromagnetic compatibility (EMC), and cooling performance because of the difference in the material properties between the resin and the conventionally used aluminum. By solving the abovementioned issues, a resin water jacket case (hereinafter, resin water jacket) was successfully adopted with inverters designed for next-generation electric powertrain in mass production models for the first time. The resin-based structure had advantages to reduce the weight of the inverter case by ~35% and decrease the number of parts to ~3/5, compared to that for the conventional cases.

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.

There are many production robots used at car manufacturing plants, and each of them is fitted with several reducers. A breakdown of one of these reducers may cause a huge loss due to the stoppage of all production lines. Therefore, condition-based maintenance is currently being used to predict failures by predetermined thresholds for average and standard deviations. However, this method can cause many false alarms or some false negatives. There are some ways of suppressing false alarms, such as detecting a change in the probability density function. However, when false alarms are suppressed using the probability density function in the operational range, some false negatives may occur, leading to a breakdown of a reducer and huge loss. A false negative is caused by overlooking an anomaly with slight changes and it is difficult to detect using only the probability density function.

Wireless Power Transfer (WPT) promises automated and highly efficient charging of electric and plug-in-hybrid vehicles. As commercial development proceeds forward, the technical challenges of efficiency, interoperability, interference and safety are a primary focus for this industry. The SAE Vehicle Wireless Power and Alignment Taskforce published the Recommended Practice J2954 to help harmonize the first phase of high-power WPT technology development. SAE J2954 uses a performance-based approach to standardizing WPT by specifying ground and vehicle assembly coils to be used in a test stand (per Z-class) to validate performance, interoperability and safety. The main goal of this SAE J2954 bench testing campaign was to prove interoperability between WPT systems utilizing different coil magnetic topologies. This type of testing had not been done before on such a scale with real automaker and supplier systems.

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.

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.

This paper presents the technologies incorporated in an electric vehicle (EV)/hybrid electric vehicle (HEV) inverter built with power semiconductors of silicon carbide (SiC) metal-oxide-semiconductor field-effect transistors (MOSFETs) instead of conventional silicon (Si) insulated gate bipolar transistors (IGBTs). A SiC inverter prototype of 2.9 L in size for driving an 80-kW motor was fabricated and evaluated on a motor test bench. The SiC inverter prototype attained average efficiency of 98.5% in the Worldwide harmonized Light-duty Test Cycle (WLTC) driving mode. The two main technologies achieved with this SiC inverter prototype are described. The first one is a new direct-cooled power module with a thick copper (Cu) heat spreader located under the semiconductors that improves thermal resistance by 34% compared with a conventional direct-cooled power module.

Because of rising demands to improve aerodynamic performance owing to its impact on vehicle dynamics, efforts were previously made to reduce aerodynamic lift and yawing moment based on steady-state measurements of aerodynamic forces. In recent years, increased research on dynamic aerodynamics has partially explained the impact of aerodynamic forces on vehicle dynamics. However, it is difficult to measure aerodynamic forces while a vehicle is in motion, and also analyzing the effect on vehicle dynamics requires measurement of vehicle behavior, amount of steering and other quantities noiselessly, as well as an explanation of the mutual influence with aerodynamic forces. Consequently, the related phenomena occurring in the real world are still not fully understood.

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.