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A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An integral part of this System is an Intervention Strategy that uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. Through this strategy, the driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models. This work develops one means to alter the future vehicle states: modulating the driver's brake commands. This control strategy must be considered in relationship to changes in the throttle commands. Three key elements of this strategy are developed in this work.

A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An Intervention Strategy uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. The driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models which is the focus of this work. This work develops one means to alter the future vehicle states: modulating the driver's throttle commands. First, changes to the longitudinal force are translated to changes in engine torque based on the current operating state (torque and speed) of the engine.

Studying the kinetic and kinematics of the rim-tire combination is very important in full vehicle simulations, as well as for the tire design process. Tire maneuvers are either quasi-static, such as steady-state rolling, or dynamic, such as traction and braking. The rolling of the tire over obstacles and potholes and, more generally, over uneven roads are other examples of tire dynamic maneuvers. In the latter case, tire dynamic models are used for durability assessment of the vehicle chassis, and should be studied using high fidelity simulation models. In this study, a three-dimensional finite element model (FEM) has been developed using the commercial software package ABAQUS. The purpose of this study is to investigate the tire dynamic behavior in multiple case studies in which the transient characteristics are highly involved.

The road profile has been shown to have significant effects on various vehicle conditions including ride, handling, fatigue or even energy efficiency; as a result it has become a variable of interest in the design and control of numerous vehicle parts. In this study, an integrated state estimation algorithm is proposed that can provide continuous information on road elevation and profile variations, primarily to be used in active suspension controls. A novel tire instrumentation technology (smart tire) is adopted together with a sensor couple of wheel attached accelerometer and suspension deflection sensor as observer inputs. The algorithm utilizes an adaptive Kalman filter (AKF) structure that provides the sprung and unsprung mass displacements to a sliding-mode differentiator, which then yields to the estimation of road elevations and the corresponding road profile along with the quarter car states.

New engine controls have been developed for the turbocharged Lexus NX200t to improve driving power by reducing engine torque output lag. Drive power management functions have been centralized in an integrated drive power control system. The newly developed controls minimize the potential reduction in drivability associated with the adoption of a turbocharged engine while improving fuel efficiency. General driveability issues commonly associated with a turbocharged engine include sudden increases in drive power due to the response lag of the turbocharger, and higher shifting frequencies if this response lag triggers a disturbed accelerator operation pattern by the driver. The developed technologies detect and control sudden increases in drive power to create the optimum drive power map, and reduce unnecessary shifts even if the driver's accelerator operation is disturbed.

Modeling the tire forces and moments (F&M) generation, during combined slip maneuvers, which involves cornering and braking/driving at the same time, is essential for the predictive vehicle performance analysis. In this study, a new semi-empirical method is introduced to estimate the tire combined slip F&M characteristics based on flat belt testing machine measurement data. This model is intended to be used in the virtual tire design optimization process. Therefore, it should include high accuracy, ease of parameterization, and fast computational time. Regression is used to convert measured F&M into pure slip multi-dimensional interpolant functions modified by weighting functions. Accurate combined slip F&M predictions are created by modifying pure slip F&M with empirically determined shape functions. Transient effects are reproduced using standard relaxation length equations. The model calculates F&M at the center of the contact patch.

Intersection crashes are a frequent and dangerous crash mode in the U.S. Emerging Intersection Advanced Driver Assistance Systems (I-ADAS) aim to assist the driver to mitigate the consequences of vehicle-to-vehicle crashes at intersections. In support of the design and evaluation of such intersection assistance systems, characterization of the road, environment, and drivers associated with intersection crashes is necessary. The objective of this study was to characterize intersection crashes using nationally representative crash databases that contained all severity, serious injury, and fatal crashes. This study utilized four national crash databases: the National Automotive Sampling System, General Estimates System (NASS/GES); the NASS Crashworthiness Data System (CDS); and the Fatality Analysis Reporting System (EARS) and the National Motor Vehicle Crash Causation Survey (NMVCCS).

There is increasing demand for highly functional diesel engine turbochargers capable of meeting Euro 6 emissions regulations while improving dynamic performance and fuel economy. However, since these requirements cannot be easily satisfied through refinements of existing technology, Toyota Motor Corporation has developed the new D-series turbocharger for initial installation in its GD diesel engine. The higher efficiency and wider operation range of the new turbocharger enabled the amount of the turbine flow capacity to be reduced by 30%, while helping to improve dynamic response and fuel economy. The mechanism causing the generation of fuel deposits in the fuel injection system upstream of the turbocharger, which was adopted for compliance with emissions regulations, was analyzed and fundamental countermeasures were applied. The result is a new highly functional turbocharger with greatly enhanced reliability.

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 real-world automotive control, there are many constraints to be considered. In order to explicitly treat the constraints, we introduce a model-prediction-based algorithm called a reference governor (RG). The RG generates modified references so that predicted future variables in a closed-loop system satisfy their constraints. One merit of introducing the RG is that effort required in control development and calibration would be reduced. In the preceding research work by Nakada et al., only a single reference case was considered. However, it is difficult to extend the previous work to more complicated systems with multiple references such as the air path control of a diesel engine due to interference between the boosting and exhaust gas recirculation (EGR) systems. Moreover, in the air path control, multiple constraints need to be considered to ensure hardware limits. Hence, it is quite beneficial to cultivate RG methodologies to deal with multiple references and constraints.

Plugin hybrid electric vehicles (PHEVs) have several attractive features in terms of reduction of greenhouse gas (GHG) emissions. Compared to conventional vehicles (CVs) that only have an internal combustion engine (ICE), PHEVs have better energy efficiency like regular hybrids (HEVs), allow for electrifying an appreciable portion of traveled miles, and have no range anxiety issues like battery-only electric vehicles (BEVs). However, in terms of criteria emissions (e.g., NOx, NMOG, HC), it is unclear if PHEVs are any better than HEVs or CVs. Unlike GHG emissions, criteria emissions are not continuously emitted in proportional quantities to fossil fuel consumption. Rather, the amount and type of criteria emissions is a rather complex function of many factors, including type of fuel, ICE temperature, speed and torque, catalyst temperature, as well as the ICE controls (e.g., fuel-to-air ratio, valve and ignition timing).

Conventional CFD-based shape optimization technology that uses parametric shape modification and optimal solutions searching algorithms has the two problems: (1) outcome of optimized shapes depend on the selection of design parameters made by the designer, and (2) high computational costs. To resolve those problems, two innovative inverse analysis technologies based on the Adjoint Method were developed in previous study: surface geometry deformation sensitivity analysis to identify the locations to be modified, and topology optimization to generate an optimal shape for maximizing the cost function in the constrained design space. However, these technologies are only applicable to steady flows. Since most flows in a vehicle (such as engine in-cylinder flow) are transient, a practical technology for surface geometry sensitivity analysis has been developed based on the Transient Adjoint Method.

Improving vehicle fuel economy is a central part of efforts toward achieving a sustainable society, and an effective way of accomplishing this aim is to enhance the engine thermal efficiency. Measures to mitigate knocking and reduce engine cooling heat loss are important aspects of enhancing the engine thermal efficiency. Cooled exhaust gas recirculation (EGR) is regarded as a key technology because it is capable of achieving both of these objectives. For this reason, it has been adopted in a wide range of both hybrid vehicles and conventional vehicles in recent years. Cooled EGR has the potential to achieve further lower fuel consumption if the EGR ratio can be increased. Fast combustion is an important and effective way for expanding the EGR ratio. The engine combustion enhancement can be categorized into measures to improve ignition characteristics and methods to promote flame propagation.

A new concept of an electromagnetic torque converter for hybrid electric vehicles is proposed. The electromagnetic torque converter, which is an electric system comprised of a set of double rotors and a stator, works as a high-efficiency transmission in the driving conditions of low gear ratio including a vehicle moving-off and as a starting device for an internal combustion engine. Moreover, it can be used for an electric vehicle driving as well as for a regenerative braking. In this concept, a high-efficiency drivetrain system for hybrid electric vehicles is constructed by replacing a fluid-type torque converter with the electromagnetic torque converter in the automatic transmission of a conventional vehicle. In this paper, we present the newly developed electromagnetic torque converter with a compact structure that enables mounting on a vehicle, and we evaluate its transmission efficiency by experiment.

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.

1 Inside a paint booth to spray paint on vehicle bodies, bumpers, and other parts (hereinafter referred to as “works”), air whose temperature and humidity are controlled by air-conditioner is supplied by blower fans through filters. Dust-eliminated and regulated air flow is sent downward from top to bottom (hereinafter referred to as “downflow”) in the painting booth. Conventionally, paint which does not adhere to work in spraying (hereinafter referred to as “paint mist”) is collected while flowing at a high speed through a slit opening called venturi scrubber in a mixture of air and water. However, this mist collecting system using venturi scrubber requires a large space with a large amount of pressure loss while consuming substantial energy. By radically changing the mist collecting principle, we developed a new compact system with less pressure loss aiming to reduce energy consumption by 40% in a half-size booth.

In the present paper, we introduce a drivetrain system using an electromagnetic coupling for hybrid electric vehicles, and propose a new control concept of vibration torque interception. The electromagnetic coupling is an electric machine that is composed of a pair of rotors, and electromagnetic torque acts mutually between the rotors. In the drivetrain system, the electromagnetic coupling works as a torque transmission device with a rotational-speed-converting function. We demonstrate that, by using this control, the electromagnetic coupling also works as a damping device that intercepts the vibration torque of the internal combustion engine, while transmitting the smooth torque to its drive line. Using a model of a two-inertia resonance system, a control system is designed such that a transfer function representing input-to-output torque is shaped in the frequency domain.

With the goal of improving drivability, this research aimed to clarify the mechanism of vehicle longitudinal acceleration, focusing on tip-in acceleration. Conventional typical analysis methods include experimental modal and model-based analysis. However, since the former requires the measurement of impulses and other input forces while the vehicle is stopped, measurement under actual driving conditions is difficult. The latter requires characteristic values such as the stiffness and damping coefficients to be identified in advance, which cannot be achieved either easily or precisely. Therefore, this paper proposes a new experiment-based analysis method. This method enables the acquisition of engine torque and transmission torque/force by measuring only the acceleration values of some components under driving conditions.

This paper describes the development of a fracture finite element (FE) model for laser screw welding (LSW) and validation of the model with experimental results. LSW was developed and introduced to production vehicles by Toyota Motor Corporation in 2013. LSW offers superb advantages such as increased productivity and short pitch welding. Although the authors had previously developed fracture FE models for conventional resistance spot welding (RSW), a fracture model for LSW has not been developed. To develop this fracture model, many comprehensive experiments were conducted. The results revealed that LSW had twice as many variations in fracture modes compared to RSW. Moreover, fracture mode bifurcations were also found to result from differences in clearance between welded plates. In order to analyze LSW fracture phenomena, detailed FE models using fine hexahedral elements were developed.

High frequency wind noise caused by turbulent flow around the front pillars of a vehicle is an important factor for customer perception of ride comfort. In order to reduce undesirable interior wind noise during vehicle development process, a calculation and visualization method for exterior wind noise with an acceptable computational cost and adequate accuracy is required. In this paper an index for prediction of the strength of exterior wind noise, referred to as Exterior Noise Power (ENP), is developed based on an assumption that the acoustic power of exterior wind noise can be approximated by the far field acoustic power radiated from vehicle surface. Using the well-known Curle’s equation, ENP can be represented as a surface integral of an acoustic intensity distribution, referred to as Exterior Noise Power Distribution (ENPD). ENPD is estimated from turbulent surface pressure fluctuation and mean convective velocity in the vicinity of the vehicle surface.