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Hydrogen–diesel dual-fuel combustion processes were visualized using an optically accessible rapid compression and expansion machine (RCEM). A hydrogen-air mixture was introduced into the combustion chamber, and a pilot injection of diesel fuel was used as the ignition source. A small amount of diesel fuel was injected as the pilot fuel at injection pressures of 40, 80, and 120 MPa using a common rail injection system. The injection amounts of diesel fuel were varied as 3, 6, and 13 mm3. The amount of hydrogen was manipulated by varying the total excess air ratio (λtotal) at 3 and 4. The RCEM was operated at a constant speed of 900 rpm, and the in-cylinder pressure and temperature at the top dead center (TDC) were set as 5 MPa and 700 K, respectively. The combustion processes were visualized via direct photography and hydroxyl (OH*) chemiluminescence photography using a high-speed camera and an image intensifier.

In a rapid compression and expansion machine (RCEM), spray flames from a two-hole injector are injected toward a wall to achieve jet-jet interaction after spray flames impinge onto the wall. Simultaneous laser-induced incandescence (LII) and laser scattering (LS) measurements were performed to investigate the soot formation process in the jet-jet interaction zone. The results showed that high LII and LS signals were detected in the interaction region and persisted for a considerable period and that soot particle size in the interaction zone was independent of the time and injection pressure.

Steady advances in autonomous vehicle development are expected to lead to improved traffic flow in terms of string stability compared with that for human-driven vehicles. Fluctuation in intervehicle distances among a group of vehicles without string stability is amplified as it propagates upstream (rearward), which may cause traffic congestion. Since it will take a few decades for autonomous vehicles to replace all human-driven vehicles, it is important to tackle the problem of traffic congestion in a mixed flow of human-driven and autonomous vehicles. Communication technologies such as fifth-generation mobile communication systems, which are improving rapidly, enable vehicle-to-vehicle communication with a sufficiently small delay. We previously reported a strategy based on vehicle-to-vehicle communication for avoiding traffic congestion by using leader–follower control, which is a distributed autonomous control strategy.

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.

For the measurements of flow rate, pressure and/or temperature in an engine exhaust pipe, probes are often inserted into the exhaust pipe depending on the application. These measurement probes differ a lot in terms of their size and shape. The flow around the probes become further complicated due to the pulsation of engine exhaust flow. In this study, computational fluid dynamics (CFD) simulations were carried out and a zero-dimensional (0D) model was constructed to analyze the flow field around the probe and flow rate of a pulsating flow. The simulations and the measurements of the flow rate and pressure were performed on flows around a hexagonal prism inserted in a circular pipe which is intended to be a differential pressure flow meter. The velocity field was also measured using the particle image velocimetry (PIV) technique. The CFD simulation results were validated with the experiments for both steady and pulsating flows.

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.

The effects of jet-jet angle on the combustion process were investigated in an optical accessible rapid compression and expansion machine (RCEM) under various injection conditions and intake oxygen concentrations. The RCEM was equipped with an asymmetric six-hole nozzle having jet-jet angles of 30° and 45°. High-speed OH* chemiluminescence imaging and direct photo imaging using the Mie scattering method captured the transient evolution of the spray flame, characterized by lift-off length and liquid length. The RCEM operated at 1200 rpm. The injection timing was -5°ATDC, and the in-cylinder pressure and temperature were 6.1 MPa and 780 K at the injection timing, respectively, which achieved a short ignition delay. The effects of injection pressure, nozzle hole diameter, and oxygen concentration were investigated.

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.

The reduction of particulate emissions is one of the most important challenges facing the development of future gasoline engines. Several studies have demonstrated the impact of fuel chemical composition on the emissions of particulate matter, more particularly, the detrimental effect of high boiling point components such as heavy aromatics. Fuel contamination is likely to become a critical issue as new regulations such as Real Driving Emissions RDE involves the use of market fuel. The objective of this study is to investigate several experimental approaches to detect the presence of Diesel contamination in Gasoline which is likely to alter pollutant emissions. To achieve this, a fuel matrix composed of 12 fuels was built presenting diesel fuel in varying concentrations from 0.1 to 2% v/v. The fuel matrix was characterized using several original techniques developed in this study.

Natural gas/diesel dual fuel engines have potential for a high thermal efficiency and low NOx emissions. However, they have the disadvantages of high unburned species emissions and lower thermal efficiencies at low loads (at low equivalence ratio). A way to solve this problem is to properly distribute the pilot fuel vapor in a natural-gas premixture. The combustion chamber geometry affects the combustion process since it influences the distribution of the pilot fuel vapor. This study investigates the influence of injection conditions and the piston bowl geometry on the performance and emissions of a dual fuel engine. Experiments were carried out using two pistons with different bowl diameters, 52 mm and 58 mm, at single-and two-stage diesel-fuel injection. The results show that the larger bowl provides lower hydrocarbon emissions at a lower equivalence ratio in the case of single-stage injection.

The main objective of this study is to evaluate the characteristics of combustion that combine premixed charge compression ignition (PCCI)-based combustion with conventional mixing controlled combustion. In this type of combustion, it is supposed that the combustion duration is shortened due to the synchronization of the timing of two types of combustions. In addition, the cooling loss caused by spray impingement is expected to decrease by the reduction of the proportion of mixing controlled combustion. In this study, the effect of injection pressure, injection timing, and split injection on thermal efficiency and emissions were investigated in order to determine the appropriate injection parameters for PCCI-based combustion to realize the proposed combustion concept.

This work investigated the mechanism of oil dilution by post injection to remove accumulated particulate matter on the diesel particulate filter of diesel engines. We developed a model to simulate post injection spray under low ambient gas pressure conditions. The model can predict the quantity of fuel mass adhered on the cylinder wall. The adhered fuel enters oil sump through the piston ring and cause oil dilution. The fuel in diluted oil evaporates during normal engine operations. We focus on the mechanism of fuel evaporation from diluted oil. The effects of engine speed and oil temperature on the evaporation were investigated. The results showed that the fuel evaporation rate increases with increasing engine speed and oil temperature. Furthermore, we developed an empirical model to predict the fuel evaporation rate of diluted oil through regression analysis with measured data.

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.

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.

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.