Search Results

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.

It is well known that the wheels and tires account for approximately 25% of the overall aerodynamic drag of a vehicle. This is because the contribution of the tires to aerodynamic drag stems from not only aerodynamic drag itself directly caused by exposure to the main flow (tire CD), but also from aerodynamic drag indirectly caused by the interference between tire wakes and the upper body flow (body CD). In the literature, as far as the authors are aware, there have been no reports that have included the following all four aspects at once: (1) CD sensitivity to detailed tire shape factors; (2) CD sensitivity differences due to different vehicle body types; (3) CD sensitivity for each aerodynamic drag component, i.e., tire CD and body CD; (4) Flow structure and mechanism contributing to each aerodynamic drag component. The purpose of this study was to clarify CD sensitivity to tire shape factors for tire CD and body CD considering two different vehicle body types, sedan and SUV.

In order to improve the accuracy of the coil temperature prediction, detailed fundamental experiments have been conducted on thermal resistances that are caused by the void air gap and contact surfaces. The thermal resistance of the coil around the air gap can be calculated by an air gap distance and air heat conductivity. Contact surface thermal resistance between the core and the housing was constant regardless of the press-fitting state in this experiment. Prediction accuracy of the coil temperature is improved by including the heat resistance characteristics that is obtained by the basic experiment to conjugate heat transfer analysis model.

A new variable compression turbo (VC-Turbo) engine, which has a multi-link system for controlling the compression ratio from 8:1 to 14:1, requires high axial force for fastening the multi-links because of high input loads and the downsizing requirement. Therefore, it was necessary to develop a 1.6-GPa tensile strength bolt with plastic region tightening. One of the biggest technical concerns is delayed fracture. In this study, quenched and tempered alloy steels were chosen for the 1.6-GPa tensile strength bolt.

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.

Wheels play an important role in determining the aerodynamic drag of passenger vehicles. This is because the contribution of wheels to aerodynamic drag comes from not only the wheels themselves, but also from the interference effect between wheel wakes and the base wake. As far as the authors are aware, there have been no reports about aerodynamic drag sensitivity to wheel shape factors for different vehicle types and different exterior body shapes. The purpose of this study was to clarify CD sensitivity to wheel shape factors for a sedan and an SUV, including different rear fender shapes. Many different wheel configurations were investigated in terms of the CD, base pressure and flow fields in wind tunnel tests. Multiple regression analyses were conducted to clarify CD sensitivity to each wheel shape factor based on the test data. This study revealed high CD sensitivity factors for both the sedan and SUV.

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.

An electric vehicle (EV) has less powertrain energy loss than an internal combustion engine vehicle (ICE), so its aerodynamic accounts have a larger portion of drag contribution of the total energy loss. This means that EV aerodynamic performance has a larger impact on the all-electric range (AER). Therefore, the target set for the aerodynamics development for a new EV hatchback was to improving AER for the customer’s benefit. To achieve lower aerodynamic drag than the previous model’s good aerodynamic performance, an ideal airflow wake structure was initially defined for the new EV hatchback that has a flat underbody with no exhaust system. Several important parameters were specified and proper numerical values for the ideal airflow were defined for them. As a result, the new EV hatchback achieves a 4% reduction in drag coefficient (CD) from the previous model.

In open-grille vehicle aerodynamics simulation using computational fluid dynamics, in addition to basic flow characteristics, such as turbulent flow with a Reynolds number of several million on the bluff body, it is important to accurately estimate the cooling air flow introduced from the front opening. It is therefore necessary to reproduce the detailed geometry of the entire vehicle including the engine bay as precisely as possible. However, there is a problem of generating a good-quality calculation grid with a small workload. It usually takes several days to a week for the pretreatment process to make the geometry data ‘clean’ or ‘watertight’. The authors proposed a computational method for complex geometries with a hierarchical Cartesian grid and a topology-independent immersed boundary method with dummy cells that discretize the geometry on a cell-by-cell basis and can set an imaginary point arbitrarily.

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.