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In this paper, we consider smart charging and vehicle-to-home (V2H) technologies for plugin electric vehicles coordinated with home energy management systems (HEMS) for automated demand response. In this system, plugin electric vehicles automatically react to demand response events with or without HEMS’s coordination, while vehicles are charged and discharged (i.e., V2H) in appropriate time slots by taking into account demand response events, time-ofuse rate information, and users’ vehicle usage plan. We introduce three approaches on home energy management: centralized energy control, distributed energy control, and coordinated energy control. We implemented smart charging and V2H systems by employing two sets of standardized communication protocols: one using OpenADR 2.0b, SEP 2.0, and SAE standards and the other using OpenADR 2.0b, ECHONET Lite, and ISO/IEC 15118.

The use of hybrid, fuel cell electric, and pure electric vehicles is on the increase as part of measures to help reduce exhaust gas emissions and to help resolve energy issues. These vehicles use regenerative-friction brake coordination technology, which requires a braking system that can accurately control the hydraulic brakes in response to small changes in regenerative braking. At the same time, the spread of collision avoidance support technology is progressing at a rapid pace along with a growing awareness of vehicle safety. This technology requires braking systems that can apply a large braking force in a short time. Although brake systems that have both accurate hydraulic control and large braking force have been developed in the past, simplification is required to promote further adoption.

Many vehicles are currently equipped with active safety systems that can detect vulnerable road users like pedestrians and bicyclists, to mitigate associated conflicts with vehicles. With the advancements in technologies and algorithms, detailed motions of these targets, especially the limb motions, are being considered for improving the efficiency and reliability of object detection. Thus, it becomes important to understand these limb motions to support the design and evaluation of many vehicular safety systems. However in current literature, there is no agreement being reached on whether or not and how often these limbs move, especially at the most critical moments for potential crashes. In this study, a total of 832 pedestrian walking or cyclist biking cases were randomly selected from one large-scale naturalistic driving database containing 480,000 video segments with a total size of 94TB, and then the 832 video clips were analyzed focusing on their limb motions.

This paper presents a modeling method for prediction of low-frequency road noise in a steady-state condition where rotating tires are excited by actual road profile undulation input. The proposed finite element (FE) tire model contains not only additional geometric stiffness related to inflation pressure and axle load but also Coriolis force and centrifugal force effects caused by tire rotation for precise road noise simulation. Road inputs act on the nodes of each rib in the contact patch of the stationary tire model and move along them at the driving velocity. The nodes are enforced to displace in frequency domain based on the measured road profile. Tire model accuracy was confirmed by the spindle forces on the rotating chassis drum up to 100Hz where Coriolis force effect should be considered. Full vehicle simulation results showed good agreement with the vibration measurement of front/rear suspension at two driving velocities.

This paper proposes a novel method of verifying comprehensive driver model used for the evaluation of driving safety systems, which is achieved by coupling the traffic simulation and the driving simulator (DS). The method consists of three-step procedure. In the first step, an actual driver operates a DS vehicle in the traffic flow controlled by the traffic simulation. Then in the next step, the actual driver is replaced by a driver model and the surrounding vehicle maneuvers are replayed using the recorded data from the first step. Then, the maneuver by the driver model is compared directly with the actual driver's maneuver along the simulation time steps.

The application of Model-Based Development (MBD) techniques for automotive control system and software development have become standard processes due to the potential for reduced development time and improved specification quality. In order to improve development productivity even further, it is imperative to introduce a systematic Verification and Validation (V&V) process to further minimize development time and human resources while ensuring control specification quality when developing large complex systems. Traditional methods for validating control specifications have been limited by control specification scale, structure and complexity as well as computational limitations restricting their application within a systematic model-based V&V process. In order to address these issues, Toyota developed Hierarchical Accumulative Validation (HAV) for systematically validating functionally structured executable control specifications.

A number of active safety systems are already developed to support drivers’ decision and action to help avoid accidents, but further enhancement of those active safety systems cannot be accomplished without increasing our understanding on driver behaviors and their interaction with vehicle systems. For this reason, a state-of-art driving simulator (DS) has been developed that creates very realistic scenarios as a means of realizing these requirements. The DS consists of a simulator cabin, turntable (inside the dome), a 6-DOF hexapod system, shakers (vehicle vertical vibration actuators), and a motion system capable of moving 35 meters longitudinally and 20 meters laterally. The system is also capable of projecting images of actual city streets and highways onto a 360° spherical screen inside of the dome. As a result, the DS is able to reproduce a driving environment that is very similar to real driving.

We investigated and analyzed the average vehicle-driver's braking behavior in panic situations by conducting vehicle tests that duplicated real world conditions that would require emergency braking performance. From our investigation, we have noticed that when panic braking is recognized, supplying additional braking power is effective for active safety. The Brake Assist System, which supplies full constant braking force when panic braking is recognized, is effective for drivers who cannot apply enough braking effort. However, in some case, such a system makes more experienced drivers uncomfortable because the deceleration caused by this full constant braking force might be different from their intentions. Considering these issues, we have developed the Brake Assist System that increases its controllability while reducing its discomfort. The TOYOTA RAUM has been available with the Brake Assist System since May 1997.

With the support of Horiba and Horiba STEC, Toyota Motor Corporation has developed an exhaust emissions simulator to verify the accuracy of extremely low emissions measurement systems. It can reliably verify the accuracy (correlation) of each SULEV emission measurement system to within 5% under actual conditions. The simulator's method of simulating SULEV gasoline engine cold-start emissions is to inject bottled gases with known concentrations of each emission constituent to the base gas, which is clean exhaust gas from a SULEV vehicle with new fully warmed catalysts. First, the frequencies and dynamic ranges of the SULEV cold-start emissions were analyzed and the method of 2 injecting the bottled gases was considered based on the results of that analysis. A high level of repeatability and accuracy was attained for all injection flow ranges in the SULEV cold-start emission simulation by switching between high-response digital Mass Flow Controllers (MFCs) of different full scales.

We have developed a novel engine cycle simulation program (UniDES: universal diesel engine simulator) to reproduce the diesel combustion process over a wide range of engine operating parameters, such as the amount of injected fuel, the injection timing, and the EGR ratio. The approach described in this paper employs a zoning model, where the in-cylinder region is divided into up to five zones. We also applied a probability density function (PDF) concept to each zone to consider the effect of spatial non-homogeneities, such as local equivalence ratios and temperature, on the combustion characteristics. We linked this program to the commonly used commercial GT-Power® software (UniDES+GT). As a result, we were able to reproduce transient engine behavior very accurately.

Recently, the development of advanced automotive technology for excellent safety and convenience has become more active. Efforts have focused on the development of active safety technology. Pre-Crash Systems, such as passenger protection systems activated before a collision or collision speed reduction system, which are categorized between active safety systems and passive safety systems, have been a subject of focus. In such systems, surround sensing technology to predict a collision is the key issue. We developed an electronically scanning millimeter-wave (MMW) RADAR, which uses Digital Beam Forming (DBF) technology, as one of the first in the world for automotive applications.

We developed a progressive system, “virtual and real simulator (V&R-S)” for engine. To innovate the process of engine development, the test system creates dynamic load of drivetrain, wheel, body and road with the virtual vehicle model. We set the phenomena such as drivetrain vibration for reproducing object of this system. The load is transmitted to the engine crankshaft end as torque with the connecting shaft made of fiberglass. The mainly developed technologies are the dynamometer with rotational inertia as low as engine, correction method of transmitted torque error of connecting shaft by H-infinity control. Thanks to these, we achieved the capability of optimization for most of dynamic characteristics (emission, fuel consumption, drivability) on engine test bench. And we now be able to limit real vehicle test to the final tuning. As a result, we have realized new engine evaluation and optimization process.

As part of active safety systems for reducing bicyclist fatalities and injuries, Bicyclist Pre-Collision System (BPCS), also known as Bicyclist Autonomous Emergency Braking System, is being studied currently by several vehicles manufactures. This paper describes the development of a surrogate bicyclist which includes a surrogate bicycle and a surrogate bicycle rider to support the development and evaluation of BPCS. The surrogate bicycle is designed to represent the visual and radar characteristics of real bicyclists in the United States. The size of bicycle surrogate mimics the 26 inch adult bicycle, which is the most popular adult bicycle sold in the US. The radar cross section (RCS) of the surrogate bicycle is designed based on RCS measurement of the real adult sized bicycles.

Pedestrian Automatic Emergency Braking (PAEB) for helping avoiding/mitigating pedestrian crashes has been equipped on some passenger vehicles. Since approximately 70% pedestrian crashes occur in dark conditions, one of the important components in the PAEB evaluation is the development of standard testing at night. The test facility should include representative low-illuminance environment to enable the examination of the sensing and control functions of different PAEB systems. The goal of this research is to characterize and model light source distributions and variations in the low-illuminance environment and determine possible ways to reconstruct such an environment for PAEB evaluation. This paper describes a general method to collect light sources and illuminance information by processing large amount of potential collision locations at night from naturalistic driving video data.

According to the U.S. National Highway Traffic Safety Administration, 743 pedal cyclists were killed and 48,000 were injured in motor vehicle crashes in 2013. As a novel active safety equipment to mitigate bicyclist crashes, bicyclist Pre-Collision Systems (PCSs) are being developed by many vehicle manufacturers. Therefore, developing equipment for evaluating bicyclist PCS is essential. This paper describes the development of a bicycle carrier for carrying the surrogate bicyclist in bicyclist PCS testing. An analysis on the United States national crash databases and videos from TASI 110 car naturalistic driving database was conducted to determine a set of most common crash scenarios, the motion speed and profile of bicycles. The bicycle carrier was designed to carry or pull the surrogate bicyclist for bicycle PCS evaluation. The carrier is a platform with a 4 wheel differential driving system.

This paper proposes a theory to analyze the collision avoidance capability of automated driving technologies. The theory gives answers to a fundamental question whether automated vehicles fall into extreme conditions at all rather than another question how a vehicle reacts under extreme conditions (is it as safe as driver?). The theory clarifies the following matters: There are two types of hazards to cause collisions, cognitive hazards and behavioral hazards. Cognitive hazards are handled by controlling the upper limit speed of the automated vehicle including when stopped. There are two methods for handling behavioral hazards, preparation and response. The response known well is the coping method activated when the hazard is detected in the dynamic (operational) level. The preparation is the coping method operating at all time in the semantic (tactical) level.

Future Automotive Systems Technology Simulator (FASTSim) is a free and open-source tool developed by National Renewable Energy Lab (NREL). Among the attractive capabilities of the FASTSim is that it can perform computationally efficient fuel economy simulations of automotive vehicles with reasonable accuracy for standard or arbitrary drive cycles. The modeling capability includes vehicles with various types of powertrains such as: conventional vehicles (CVs), hybrid-electric vehicles (HEVs), plugin hybrid electric vehicles (PHEVs) and battery-only electric vehicles (BEVs). The public version of FASTSim available from NREL is implemented in Excel, which achieves the goal of good accessibility to a broad audience, but has some limitations, including: i) bottleneck in computations when importing arbitrary drive cycles, ii) slower computations in general than other scripting or programming languages, and iii) less portable to integration with other applications and/or other platforms.

In order to reduce CO₂, Electric Vehicles (EV) and Hybrid Vehicles (HV) are effective. Those types of vehicles have powertrains from conventional vehicles. Those new powertrains drastically improve their efficiency from conventional vehicles keeping the same or superior power performance. On the other hand, those vehicles have an issue for thermal energy shortage during warming up process. The thermal energy is very large, and seriously affects the fuel economy for HV and the mileage for EV. In this paper, we propose VHDL-AMS multi-domain simulation technique for the estimation of the vehicle performance at the concept planning stage. The VHDL-AMS is IEEE and IEC standardized language, which supports not only multi-domain (physics) but also encryption. The common modeling language and encryption standard is indispensable for full-vehicle simulation.

Systems already exist that reduce collision damage through collision-danger alarms and by operating such features as pre-tensioning seat belts and collision mitigation brakes when the system has determined the possibility of a collision by using millimeter-wave radar. Conversely, at present, carelessness in observing oncoming traffic accounts for a large percentage of head-on collisions. Timely collision warnings are effective in avoiding accidents and for mitigating the severity of the collision. However, warnings given too early even before the driver has had a chance to carry out normal evasive maneuvers, can annoy the driver. Accordingly, by adding a driver face direction sensor, the authors have developed in the present research a system that will only hasten the timing of warnings when the system has detected the direction of the driver's face and determined that they are not facing the front of the vehicle.

This paper describes a new method to predict the rupture of spot welds, suitable for vehicle crash simulation. In a crash simulation used for vehicle development process, the calculation is performed assuming that the spot welds in the vehicle do not rupture. However, if some spot welds rupture in test of a prototype vehicle, the simulated deformation and test deformation may not match, resulting in inaccurate estimation of deformation from simulation. Therefore accuracy of predicting the rupture of spot welds is crucial in accurately estimating the deformation and improving reliability of vehicle crash simulation results. The new method to predict the rupture of spot welds which relates axial and shear forces and bending moment of spot weld to stress around nugget has been developed by authors. Based on developed method, the rupture risk of spot welds has been estimated. The new method was applied to estimate the spot weld rupture using three types of specimens.