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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.

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.

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 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.

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.

A dynamics model considering series rigidity was constructed to examine suspension friction, which has a major effect on ride comfort on paved roads. The friction characteristics of the bushings, ball joints, and shock absorbers are expressed with series elastic elements such as arm rigidity and the spring constant of the oil seals. It was confirmed that the calculated values for the overall spring constant and damping coefficient of the suspension virtually matched values measured in a 4-post shaker test. In addition, the results of analysis using this dynamics model confirmed that the degree of friction affects both the damping coefficient and the spring constant of the suspension, especially when the series rigidity is high. Also highly rigid friction has an adverse effect on sprung motion in frequency ranges above 15 Hz. After suspension enhancements were adopted based on these findings, 4-post shaker tests confirmed that sprung motion above 2 Hz improved..

Injuries in car to pedestrian collisions are affected by various factors such as the vehicle body type, pedestrian body size and impact location as well as the collision speed. This study aimed to investigate the influence of such factors taking a Finite Element (FE) approach. A total of 72 collision cases were simulated using three different vehicle FE models (Sedan, SUV, Mini-Van), three different pedestrian FE models (AM50, AF05, AM95), assuming two different impact locations (center and the corner of the bumper) and at four different collision speeds (20, 30, 40 and 50 km/h). The impact kinematics and the responses of the pedestrian model were validated against those in the literature prior to the simulations. The relationship between the collision speed and the predicted occurrence of head and chest injuries was examined for each case, analyzing the impact kinematics of the pedestrian against the vehicle body and resultant loading to the head and the chest.

When a car collides against a pole-like obstacle, the deformation pattern of the vehicle body-side tends to extend to its upper region. A possible consequence is an increase of loading to the occupant thorax. Many studies have been conducted to understand human thoracic responses to lateral loading, and injury criteria have been developed based on the results. However, injury mechanisms, especially those of internal organs, are not well understood. A human body FE model was used in this study to simulate occupant kinematics in a pole side impact. Internal organ parts were introduced into the torso model, including their geometric features, material properties and connections with other tissues. The mechanical responses of the model were validated against PMHS data in the literature. Although injury criterion for each organ has not been established, pressure level and its changes can be estimated from the organ models.

The aim of this study was to investigate the sacroiliac joint injury mechanism. Two test configurations were selected from full scale car crashes conducted with the WorldSID 50th dummy resulting in high sacroiliac joint loads and low pubic symphysis force, i.e. severe conditions for the sacroiliac joint. The two test conditions were reproduced in laboratory using a 150-155 kg guided probe propelled respectively at 8 m/s and 7.5 m/s and with different shapes and orientations for the plate impacting the pelvis. Nine Post Mortem Human Subject (PMHS) were tested in each of the two configurations (eighteen PMHS in total). In order to get information on the time of fracture, eleven strain gauges were glued on the pelvic bone of each PMHS. Results - In the first configuration, five PMHS out of nine sustained AIS2+ pelvic injuries. All five presented sacroiliac joint injuries associated with pubic area injuries.

Injuries of the human brain and spinal cord associated with the central nervous system (CNS) are seen in automotive accidents. CNS injuries are generally categorized into severe injuries (AIS 3+). However, it is not clear how the restraint conditions affect the CNS injuries. This paper presents a newly developed three-dimensional (3D) finite element head-neck model in order to investigate the biomechanical responses of the brain-spinal cord complex. The head model consists of the scalp, skull, and a detailed description of the brain including the cerebrum, cerebellum, brainstem with distinct white and gray matter, cerebral spinal fluid (CSF), sagittal sinus, dura, pia, arachnoid, meninx, falx cerebri, and tentorium. Additionally, the neck model consists of the cervical vertebral bodies, intervertebral discs, muscles, ligaments, spinal cord with white and gray matter, cervical pia, and CSF.

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.

Lower extremities are the most frequently injured body regions in vehicle-to-pedestrian collisions and such injuries usually lead to long-term loss of health or permanent disability. However, influence of pre-impact posture on the resultant impact response has not been understood well. This study aims to investigate the effects of preimpact pedestrian posture on the loading and the kinematics of the lower extremity when struck laterally by vehicle. THUMS pedestrian model was modified to consider both standing and mid-stance walking postures. Impact simulations were conducted under three severities, including 25, 33 and 40 kph impact for both postures. Global kinematics of pedestrian was studied. Rotation of the knee joint about the three axes was calculated and pelvic translational and rotational motions were analyzed.

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.

Since drowsy driving is a major cause of serious traffic accidents, there is a growing requirement for drowsiness prevention technologies. This study proposes a drowsy driving prediction method based on eye opening time. One issue of using eye opening time is predicting strong drowsiness before the driver actually feels sleepy. Because overlooking potential hazards is one of the causes of traffic accidents and is closely related to driver cognition and drowsiness, this study focuses on eye opening movements during driving. First, this report describes hypotheses concerning drowsiness and eye opening time based on the results of previous studies. It is assumed that the standard deviation of eye opening time (SDEOP) indicates driver drowsiness and the following two transitions are considered: increasing and decreasing SDEOP. To confirm the hypotheses, the relationship between drowsiness and SDEOP was investigated.

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.

In this paper, we present an implementation of smart charging systems for plug-in electric vehicles based on off-the-shelf communication protocols for smart grids including SAE J2836/2847/J2931 standards and SEP 2.0. In this system, the charging schedule is optimized so that it supplies sufficient electricity for the next trip and also minimizes the charging cost under given time-of-use rate structures while it follows demand response events requested by a utility. Also, users can control charging schedule and check the current status of charging through application software of tablet computers. To validate the effectiveness of the developed smart charging system, we conducted experimental demonstration in which a total of 10 customers of Duke Energy regularly used our developed system for approximately one year with simulated time-of-use rate structures and demand response events.