Search Results

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.

In the pursuit of a sustainable transportation systems, Toyota is considering a comprehensive approach pursuing multiple advanced technologies to address three primary issues: GHG, Petroleum Use, and Air Quality. Vehicles must be ready for and affordable to the mass market to provide the customer choices to meet their transportation needs whether it is EV's, Hybrids, Plug-In Hybrids or Fuel Cell Hydrogen Hybrids. Our studies have shown that EVs have the potential to provide significant improvements in energy utilization especially combined with other advanced technologies. Toyota believes that a combination of these technolgies will provide complementary solution that enables a sustainable transportation system. Presenter Takehito Yokoo, Toyota Motor Corporation

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.

Toyota has developed a new 2.4L L4 turbo (2.4L-T) engine with 8AT and 1-motor hybrid electric powertrains for midsize pickup trucks. The aim of these powertrains is to fulfill both strict fuel economy and emission regulations toward “Carbon Neutrality”, while exceeding customer expectations. The new 2.4L L4 turbocharged gasoline engine complies with severe Tier3 Bin30/LEVIII SULEV30 emission regulations for body-on-frame midsize pickup trucks improving both thermal efficiency and maximum torque. This engine is matched with a newly developed 8-speed automatic transmission with wide range and close step gear ratios and extended lock-up range to fulfill three trade-off performances: powerful driving, NVH and fuel economy. In addition, a 1-motor hybrid electric version is developed with a motor generator and disconnect clutch between the engine and transmission.

Introducing effective technologies to reduce carbon emissions in the transport sector is a critical issue for automotive manufacturers to contribute to sustainable development. Unlike the plug-in electric vehicles (PEVs), whose effectiveness is dependent on the carbon intensity of grid electricity, the solar hybrid vehicle (SHV) can be an alternative electric vehicle because of its off-grid, zero-emission electric technology. Its usability is also advantageous because it does not require manual charging by the users. This study aims at evaluating the economic, environmental, and usability benefits of SHV by comparing it with other types of vehicles including PEVs. By setting cost and energy efficiency on the basis of the assumed technology level in 2030, annual cost and annual CO2 emissions of each vehicle are calculated using the daily mileage pattern obtained from a user survey of 5,000 people in Japan and the daily radiation data for each corresponding user.

In 2007, researchers at the Massachusetts Institute of Technology successfully completed a Wireless Power Transfer (WPT) experiment. Ever since, interest in WPT has been growing. At Toyota, we have been developing the underlying technology of a WPT system. Simultaneously we have been working with regulatory committees to create a standard for WPT. In particular, there are concerns that WPT’s radiated emissions could cause harm to humans and the neighboring electronic equipment. There are many challenges that need to be overcome, but a key concern is understanding WPT’s electromagnetic compatibility (EMI: Electro-Magnetic Interference and EMF: Electro-Magnetic Field). In this paper, we show the technical issues, the evaluation method, and the development status of EMI and EMF on PHVs/EVs when using WPT. For Electromagnetic interference (EMI) performance, we investigated both an open area test site and an electromagnetic anechoic chamber as evaluation environments.

In this paper, we will introduce a stereo vision system developed as a sensor for a vehicle's front monitor. This system consists of three parts; namely, a stereo camera that collects video images of the forward view of the vehicle, a stereo ECU that processes its output image, and a near-infrared floodlight for illuminating the front at night. We were able to develop an obstacle detection function for the Pre-Crash Safety System and also a traffic lane detection function for a Lane-Keeping Assist System. Especially in regard to the obstacle detection function, we were able to achieve real-time processing of the disparity image calculations that had formerly required long processing times by using two types of recently developed LSIs.

This paper describes a method for assisting pedestrians to cross a road. As motorization develops, pedestrian protection techniques are becoming more and more important. Advanced driving assistance systems (ADAS) are improving rapidly to provide even greater safety. However, since the accident risk of pedestrians remains high, the development of an advanced walking assistance system for pedestrian protection may be an effective means of reducing pedestrian accidents. Crossing a road is one of the highest risk events, and is a complex phenomenon that consists of many dynamically changing elements such as vehicles, traffic signals, bicycles, and the like. A road crossing assistance system requires three items: real-time situational recognition, a robust decision-making function, and reliable information transmission. Edge devices equipped with autonomous systems are one means of achieving these requirements.

The increase in automobile accidents has heightened the awareness of safety in the general public, and serious safety measures have been pushed forward in various countries. Although those efforts have achieved a certain level of success, more effective methods are needed to cope with further increases of automobile ownership.Besides the collision safety, measures that prevent accidents or reduce the possibility of accidents will now be necessary to reduce the number of injuries.Here, we will present the current development status and issues for an obstacle recognition system that reduces the likelihood of accidents by utilizing radars and image sensors.

To adapt to Battery Electric Vehicle (BEV) integration, the significance of protective designs for battery packs against ground impact caused by road debris is very high, and there is also a keen interest in the feasibility assessment technique using Computer-Aided Engineering (CAE) tools for prototype-free evaluations. However, the challenge lies in obtaining real-world empirical data to verify the accuracy of the predictive CAE model. Collecting real-world data using actual battery pack can be time-consuming, costly, and accurately ascertaining the precise direction, magnitude, and location of the force applied from the road to the battery pack poses a challenging task. Therefore, in this study, we developed a methodology using machine learning, specifically Gaussian process regression (GPR), to perform inverse analysis of the direction, magnitude, and location of vehicle-road contact forces during rough road conditions.

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.

The strict CO2 emission limit for passenger cars have been set by US, EU, Japan, China and other countries. In order to meet the requirement, it is essential to develop an alternative power source for the future cars. Power generation by solar panels is a promising renewable energy candidate because the most environmentally friendly vehicles such as electric vehicles and plug-in hybrid vehicles are equipped with large-capacity batteries that can be charged with electricity generated by solar panels. The requirements for the solar panels are paintable with desired color and to be lightweight. In this study, we developed a simple lift-off process for producing colorful and lightweight Cu(In,Ga)Se2 (CIGS) solar cells for future automotive application. Our measurements show that the developed lift-off process can provide the lightweight solar panel that have nearly identical performance compared to that of the cell before the lift-off process.

This study characterizes the response of the human cadaver abdomen to high-speed seatbelt loading using pyrotechnic pretensioners. A test apparatus was developed to deliver symmetric loading to the abdomen using a seatbelt equipped with two low-mass load cells. Eight subjects were tested under worst-case scenario, out-of-position (OOP) conditions. A seatbelt was placed at the level of mid-umbilicus and drawn back along the sides of the specimens, which were seated upright using a fixed-back configuration. Penetration was measured by a laser, which tracked the anterior aspect of the abdomen, and by high-speed video. Additionally, aortic pressure was monitored. Three different pretensioner designs were used, referred to as system A, system B and system C. The B and C systems employed single pretensioners. The A system consisted of two B system pretensioners. The vascular systems of the subjects were perfused.

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.

Temperature stratification plays an important role in HCCI combustion. The onsets of auto-ignition and combustion duration are sensitive to the temperature field in the engine cylinder. Numerical simulations of HCCI engine combustion are affected by the use of wall boundary conditions, especially the temperature condition at the cylinder and piston walls. This paper reports on numerical studies and experiments of the temperature field in an optical experimental engine in motored run conditions aiming at improved understanding of the evolution of temperature stratification in the cylinder. The simulations were based on Large-Eddy-Simulation approach which resolves the unsteady energetic large eddy and large scale swirl and tumble structures. Two dimensional temperature experiments were carried out using laser induced phosphorescence with thermographic phosphors seeded to the gas in the cylinder.

This paper describes the development of a fatigue life prediction method for Laser Screw Welding (LSW). Fatigue life prediction is used to assess the durability of automotive structures in the early design stages in order to shorten the vehicle development time. The LSW technology is a spot-type joining method similar to resistance spot welding (RSW), and has been developed and applied to body-inwhite structures in recent years. LSW can join metal panels even when a clearance exists between the panels. However, as a result of this favorable clearance-allowance feature of LSW, a concave shape may occur at the nugget part of the joint. These LSW geometric features, the concavity of nuggets and the clearance between panels, are thought to affect the local stiffness behavior of the joint. Therefore, while assessing the fatigue life of LSW, it is essential to estimate the influence of these factors adequately for the representation of the local stiffness behavior of the joint.

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.