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To prevent global warming, further reductions in carbon dioxide are required. It is therefore important to promote the spread of electric vehicles powered by internal combustion engines and electric vehicles without internal combustion engines. As a result, emissions from hybrid electric vehicles equipped with internal combustion engines should be further reduced. Interest in catalytic reactions in an electric field with a higher catalytic activity compared to conventional catalysts has increased because this technology consumes less energy than other electrical heating devices. This study was therefore undertaken to apply a catalytic reaction in an electric field to an exhaust emission control. First, the original experimental equipment was built with a high voltage system used to conduct catalytic activity tests.

Our L2-automated driving system enabling a driver to take his/her hands off from the steering wheel is self-operating on a highway, allowing the vehicle to automatically change lanes and overtake slow-speed leading vehicles. It includes an OTA function, which can extend the ODD after the market launch. To realize these features in reasonably safer and more reliable ways, system architecture must be designed well under hardware and software implementation constraints. One such major constraint is the system must be designed to make the most out of the existing sensor configuration on the vehicle, where five peripheral radars and a front camera for ADAS as well as panoramic-view and rear-view cameras for monitoring are available. In addition, four LiDARs and a telephoto camera are newly adopted for ADS. Another constraint is the system must consist of reliable redundant components for fail-safe operation.

Premixed charge compression ignition (PCCI) combustion is effective in reducing harmful exhaust gas and improving the fuel consumption of diesel engines [1]. However, PCCI combustion has a problem of exhibiting lower combustion stability than diffusive combustion [2, 3], which makes it challenging to apply to mass production engines. Its low combustion stability problem can be overcome by implementing complicated injection control strategies that account for variations in environmental and engine operating conditions as well as transient engine conditions, such as turbocharging delay, exhaust gas recirculation (EGR) delay, and intake air temperature delay. Although there is an example where the combustion mode is switched according to the intake O2 fraction [4], it requires a significant number of engineering-hours to calibrate multiple combustion modes. And besides, such switching combustion modes tends to have a risk of discontinuous combustion noise and torque.

It is well understood that using lower viscosity engine oils can greatly improve fuel economy [1, 2, 3, 4]. However, it has been impossible to evaluate ultra-low viscosity engine oils (SAE 0W-12 and below) utilizing existing fuel economy test methods. As such, there is no specification for ultra-low viscosity gasoline engine oils [5]. We therefore developed firing and motored fuel economy test methods for ultra-low viscosity oils using engines from Japanese automakers [6, 7, 8]. This was done under the auspices of the JASO Next Generation Engine Oil Task Force (“TF” below), which consists mainly of Japanese automakers and entities working in the petroleum industry. Moreover, the TF used these test methods to develop the JASO GLV-1 specification for next-generation ultra-low viscosity automotive gasoline engine oils such as SAE 0W-8 and 0W-12. In developing the JASO GLV-1 specification, Japanese fuel economy tests and the ILSAC engine tests for evaluating engine reliability were used.

Engine starting vibration of hybrid vehicle with Toyota hybrid system has variations even in the same vehicle, and a large vibration that occurs rarely may cause stress to the passengers. The contribution analysis based on the vibration theory and statistical analysis has been done, but the primary factor of the rare large vibration has not been clarified because the number of factors is enormous. From this background, we apply machine learning that can reproduce multivariate and complicated relationships to analysis of variation factors of engine starting vibration. Variations in magnitude of the exciting force such as motor torque for starting the engine and in-cylinder pressure of the engine and timing of these forces are considered as factors of the variations. In addition, there are also nonlinear factors such as backlash of gears as a factor of variations.

Next generation vehicles driven by motor such as electric vehicles and fuel cell vehicles have no engine noise. Therefore the balance of interior noise is different from the vehicles driven by conventional combustion engine. In particular, road induced noise tends to be conspicuous in the low to middle vehicle speed range, therefore, technological development to reduce it is important task. The purpose of this research is to predict the road induced noise from the signals of sensors adopted for automatic driving for utilizing the prediction result as a reference signal to reduce road induced noise by active noise control (ANC). Using the monocular camera which is one of the simplest image sensors, the road induced noise is predicted from the road surface image ahead of the vehicle by machine learning.

Historically, greenhouse gas (GHG) emissions standards for vehicles have focused on tailpipe emissions. However, sound environmental policy requires a more holistic well-to-wheels (WTW) assessment that includes both production of the fuel and its use in the vehicle. The present research explores the net change in WTW GHG emissions associated with moving from regular octane (RO) to high octane (HO) gasoline. It considers both potential increases in refinery emissions from producing HO fuel and potential reductions in vehicle emissions through the use of fuel-efficient engines optimized for such fuel. Three refinery configurations of varying complexity and reforming capacity were studied. A set of simulations covering different levels of HO gasoline production were run for each refinery configuration.

Road Departure Mitigation System (RDMS) is a new feature in vehicle active safety systems. It may not rely only on the lane marking for road edge detection, but other roadside objects This paper discusses the radar aspect of the RDMS testing on roads with grass road edges. Since the grass color may be different at different test sites and in different seasons, testing of RDMS with real grass road edge has the repeatability issue over time and locations. A solution is to develop surrogate grass that has the same characteristics of the representative real grass. Radar can be used in RDMS to identify road edges. The surrogate grass should be similar to representative real grass in color, LIDAR characteristics, and Radar characteristics. This paper provides the 24 GHz and 77 GHz radar characteristic specifications of surrogate grass.

This paper describes the development of an innovative AWD system called Dynamic Torque Vectoring AWD for all-wheel drive (AWD) vehicles based on a front-wheel drive configuration. The Dynamic Torque Vectoring AWD system helps to achieve high levels of both dynamic performance and fuel efficiency. Significant fuel economy savings are achieved by using a new compact disconnection mechanism at the transfer and rear units, which prevents any unnecessary rotation of the propeller shaft. In addition, the system is also capable of independently distributing torque to the rear wheels by utilizing electronically controlled couplings on the left and right sides of the rear differential. This greatly enhances both on-road cornering performance and off-road driving performance.

In recent years Road Departure Mitigation Systems (RDMS) is introduced to the market for avoiding roadway departure collisions. To support the performance testing of the RDMS, the most commonly seen road edge, grass, is studied in this paper for the development of standard surrogate grass. This paper proposes a method for defining the resembling grass color and height features due to significant variations of grass appearances in different seasons, temperatures and environments. Randomly selected Google Street View images with grass road edges are gathered and analyzed. Image processing techniques are deployed to obtain the grass color distributions. The height of the grass is determined by referencing the gathered images with measured grass heights. The representative colors and heights of grass are derived as the specifications of surrogate grass for the standard evaluation of RDMS.

Intersection collisions currently account for approximately one-fifth of all crashes and one-sixth of all fatal crashes in the United States. One promising method of mitigating these crashes and fatalities is to develop and install Intersection Advanced Driver Assistance Systems (I-ADAS) on vehicles. When an intersection crash is imminent, the I-ADAS system can either warn the driver or apply automated braking. The potential safety benefit of I-ADAS has been previously examined based on real-world cases drawn from the National Motor Vehicle Crash Causation Survey (NMVCCS). However, these studies made the idealized assumption of full installation in all vehicles of a future fleet. The objective of this work was to predict the reduction in Straight Crossing Path (SCP) crashes due to I-ADAS systems in the United States over time. The proportion of new vehicles with I-ADAS was modeled using Highway Loss Data Institute (HLDI) fleet penetration predictions.

Toyota Motor Corporation has been actively pursuing the development of fuel cell vehicles (FCVs) to respond to global environmental concerns and demands for clean energy. Toyota developed the first fuel cell (FC) bus to receive vehicle type certification in Japan. Subsequently, a new FC bus has been developed, which adopts two FC systems and four high-voltage batteries to achieve the required high power performance and durability. For enhanced durability, the FC system is controlled to maximize usage of the high-voltage batteries and to reduce the number of electric potential changes of the fuel cell. To accomplish this, the voltage of the FC stack must be kept high and FC power must be kept low. The high-voltage batteries were used to actively minimize FC power during acceleration.

This paper presents an improvement in the accuracy of NOx sensors at high NOx concentration regions by optimizing the manufacturing process, sensor electrode materials and structure, in order to suppress the deterioration mechanism of sensor electrodes. Though NOx sensors generally consist of Pt/Au alloy based oxygen pump electrodes and Pt/Rh alloy based sensor electrodes, detailed experimental analysis of aged NOx sensors showed changes in the surface composition and morphology of the sensor electrode. The surface of the sensor electrode was covered with Au, which is not originally contained in the electrode, resulting in a diminished active site for NOx detection on the sensor electrode and a decrease in sensor output. Theoretical analysis using CAE with molecular dynamics supported that Au tends to be concentrated on the surface of the sensor electrode.

This report describes the implementation of the spark channel short circuit and blow-out submodels, which were described in the previous report, into a spark ignition model. The spark channel which is modeled by a particle series is elongated by moving individual spark particles along local gas flows. The equation of the spark channel resistance developed by Kim et al. is modified in order to describe the behavior of the current and the voltage in high flow velocity conditions and implemented into the electrical circuit model of the electrical inductive system of the spark plug. Input parameters of the circuit model are the following: initial discharge energy, inductance, internal resistance and capacitance of the spark plug, and the spark channel length obtained by the spark channel model. The instantaneous discharge current and the voltage are obtained as outputs of the circuit model.

The use of exhaust gas recirculation (EGR) in spark ignition engines has been shown to have a number of beneficial effects under specific operating conditions. These include reducing pumping work under part load conditions, reducing NOx emissions and heat losses by lowering peak combustion temperatures, and by reducing the tendency for engine knock (caused by end-gas autoignition) under certain operating regimes. In this study, the effects of EGR addition on knocking combustion are investigated through a combined experimental and modeling approach. The problem is investigated by considering the effects of individual EGR constituents, such as CO2, N2, and H2O, on knock, both individually and combined, and with and without traces species, such as unburned hydrocarbons and NOx. The effects of engine compression ratio and fuel composition on the effectiveness of knock suppression with EGR addition were also investigated.

Ongoing research on active stabilizers involves not only control of the roll angle of the vehicle based on steering input but also improving ride comfort by reducing roll vibration caused by the antiphase road surface input. In that context, roll skyhook control, which applies skyhook theory to provide feedback on the vehicle roll and drive the actuators, has already been presented. Although vibration in all frequency bands can be reduced if there is no control delay, time lags or phase delays in control elements such as the communication, computation, low-pass filter, or actuators can amplify vibration. Consequently, a sufficient effect of controlling cannot be obtained. This paper will address wheelbase filtering, which produces a frequency that minimizes roll oscillation, and is used to suppress the influence of the undesirable vibration.

Roadway departure mitigation systems for helping to avoid and/or mitigate roadway departure collisions have been introduced by several vehicle manufactures in recent years. To support the development and performance evaluation of the roadway departure mitigation systems, a set of commonly seen roadside surrogate objects need to be developed. These objects include grass, curbs, metal guardrail, concrete divider, and traffic barrel/cones. This paper describes how to determine the representative color of these roadside surrogates. 24,762 locations with Google street view images were selected for the color determination of roadside objects. To mitigate the effect of the brightness to the color determination, the images not in good weather, not in bright daylight and under shade were manually eliminated. Then, the RGB values of the roadside objects in the remaining images were extracted.

To improve the thermal efficiency of an engine, it is particularly important to reduce the cooling loss from the combustion gas to the combustion chamber wall, which constitutes a major proportion of the total loss [1]. Previous studies addressing cooling loss reduction attempted to use ceramic in place of the conventional aluminum or iron alloys, but this led to a reduction in the volumetric efficiency and increased smoke emissions. This was caused by the ceramics having both a low thermal conductivity and high heat capacity, relative to aluminum and iron. These characteristics cause the piston wall temperature, which rises during combustion, to remain high during the intake stroke, thus increasing the intake temperature and reducing the volumetric efficiency. This increases the smoke emissions [2].

For the launch of the redesigned Lexus LS, a new 3.5 L V6 twin turbo engine has been developed aiming at unparalleled performance on four axes, “driving pleasure”, “power-performance”, “quietness” and “fuel economy”. To achieve outstanding power-performance and high thermal efficiency, the specifications have been optimized for high speed combustion. The maximum torque of 600 Nm, power of 310 kW (yielding specific power of 90 kW/L), and the maximum thermal efficiency of 37% have been achieved using several new technologies including a high efficiency turbocharger. A prototype vehicle equipped with this engine and Direct-Shift 10AT achieved a 0-60 mph acceleration time of 4.6 sec, with extremely good CAFE combined fuel economy of 23 mpg and power-performance aligned with V8 turbocharged offerings from competing OEM’s.

In order to adapt to energy security and the changes of global-scale environment, further improvement of fuel economy and adaptation to each country’s severer exhaust gas emission regulation are required in an automotive engine. To achieve higher power performance with lower fuel consumption, the engine’s basic internal design such as an engine block and cylinder head were changed and the combustion speed was dramatically increased. Consequently, stroke-bore ratio and valve layout were optimized. Also, both flow coefficient and intake tumble ratio port were improved by adopting a laser cladded valve seat. In addition, several new technologies were adopted. The Atkinson cycle using a new Electrical VVT (Variable Valve Timing) and new combustion technology adopting new multi-hole type Direct fuel Injector (DI) improved engine power and fuel economy and reduced exhaust emissions.