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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 development of electric vehicles has been progressed, rapidly, to achieve Carbon neutrality by 2050. There have been increasing concerns about Electromagnetic Compatibility (EMC) performance due to increasing power for power trains of vehicles. Because same power train system expands to some vehicles, we have developed numerical simulations in order to predict the vehicle EMC performances. We modeled a vehicle which has inverter noises by numerical simulation to calculate electric fields based on GB/T18387. We simulated the common mode noise which flows through the shielding braid of the high voltage wire harnesses. As a result, it is confirmed a correlation between the electric fields calculated by numerical simulation and the measured one.

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.

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.

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.

This study investigates a methodology in which the general public's subjective interpretation of vehicle handling and performance can be predicted. Several vehicle handling measurements were acquired, and associated metrics calculated, in a controlled setting. Human evaluators were then asked to drive and evaluate each vehicle in a winter driving school setting. Using the acquired data, multiple linear regression and artificial neural network (ANN) techniques were used to create and refine mathematical models of human subjective responses. It is shown that artificial neural networks, which have been trained with the sets of objective and subjective data, are both more accurate and more robust than multiple linear regression models created from the same data.

With the current increase in concern and awareness regarding sustainability and energy, a new focus has been placed on the field of engineering. In this realm of focus, how to educate engineers, more specifically how to continually educate engineers to keep up with technology and the changing workforce has become a very important topic of interest. There exists a gap between graduate studies and professional implementation of technology which the Energy Systems Engineering [ESE] program currently in deployment and development between the University of Michigan and General Motors seeks to address. This work outlines current efforts in encouraging new engineers to enter the field, but focuses primarily on continuing and re-educating the workforce to meet the needs of new technologies. Examples of academic-industry cooperation will be discussed, with some focus on the benefit and experience of the student.

Knowledge of experts is necessary for judging motor current waveforms. Here, we develop an automatic judgement system for motor current waveform by establishing an AI model trained by knowledge of experts and CAE technology.

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.

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.

This study evaluated the effectiveness of alternative workload-based interventions intended to restore driver alertness following drowsy episodes. Unlike traditional drowsy driving studies, this experiment did not target sleep-deprived individuals, but rather studied normally rested drivers under the assumption that low-workload environments could trigger drowsy driving episodes. The study served as a proof of concept for varying the nature and onset of countermeasure interventions intended to disrupt the drowsiness cycle. Interventions to combat drowsiness attempted to target driver workload, either physical or cognitive, and included two primary treatment conditions: 1) physical workload to increase driver steering demands and 2) trivia-based interactive games to mentally challenge drivers. A benchmark comparison condition using music was also investigated to contrast the relative influence of workload-based interventions with passive listening to musical arrangements.

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.

A vehicle parking manoeuvre is characterized by low or zero speed, small turning radius and large yaw velocity of the steered wheels. To predict the forces and moments generated by a wheel under these conditions, the Pacejka Magic Formula model has been extended to incorporate the effect of spin (turn slip model) in the past years. The extensions have been further developed and incorporated in the MFTyre/MF-Swift 6.2 model. This paper describes the development of a method for the identification of the turn slip parameters. Based on the operating conditions of a typical parking manoeuvre, the dominant parameters of the turn slip model are firstly defined. At an indoor test facility, the response of a tyre under the identified operating conditions is measured. An algorithm is developed to identify the dominant turn slip parameters from the measured responses.

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.

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.

This paper describes a design tool and a software platform for FlexRay systems that are investigated in Nagoya University and are proposed to JasPar. The design tool reads the specification of a system as a task graph that consists of a set of tasks and messages among them. The design tool, then, allocates the tasks to ECUs and schedules the messages on a FlexRay network. The software platform consists of a middleware called time-trigger module (TTM) which dispatches time-triggered tasks, a communication middleware for a time-triggered network (TT-COM), a network management middleware for FlexRay (FlexRay-NM), and a device driver for FlexRay controller.

Vehicle dynamics simulation with Hardware In the Loop (HIL) has been demonstrated to reduce development and validation time for dynamic control systems. For dynamic control systems such as Anti-lock Braking System (ABS) and Electronic Stability Control (ESC), an accurate vehicle dynamics performance simulation system requires the Electronic Brake Control Module (EBCM) coupled with the vehicles brake system hardware. This kind of HIL simulation-specific software tool can further increase efficiency by means of automation and optimization of the development and validation process. This paper presents a method for HIL vehicle dynamics simulator optimization through Brake Response Time (BRT) correlation. The paper discusses the differences between the physical vehicle and the HIL vehicle dynamics simulator. The differences between the physical and virtual systems are used as factors in the development of a Design Of Experiment (DOE) quantifying HIL simulator performance.

An interactive tool for predicting the performance of vehicle designs in the pedestrian leg impact test has been developed. This tool allows users to modify the design of a vehicle front structure through the use of a graphical interface, and then evaluates the performance of the design with a response surface. This performance is displayed in the graphical interface, providing the user with nearly instantaneous feedback to his design changes. An example is shown that demonstrates how the tool can be used to help guide the user towards vehicle designs that are likely to improve performance. As part of the development of this tool, a simplified, parametric finite element model of the front structure of the vehicle was created. This vehicle model included eleven parameters that could be adjusted to change the structural dimensions and structural behavior of the model.

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.