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Reducing vehicle CO2 emissions is an important measure to help address global warming. To reduce CO2 emissions on a global basis, Toyota Motor Corporation is taking a multi-pathway approach that involves the introduction of the optimal powertrains according to the circumstances of each region, including hybrid electric (HEVs) and plug-in hybrid electric vehicles (PHEVs), as well as battery electric vehicles (BEVs). This report describes the development of a new PHEV system for the Toyota Prius. This system features a traction battery pack structure, transaxle, and power control unit (PCU) with boost converter, which were newly developed based on the 2.0-liter HEV system. As a result, the battery capacity was increased by 1.5 times compared to the previous model with almost the same battery pack size. Transmission efficiency was also improved, extending the distance that the Prius can be driven as an EV by 70%.

Driving Automation Systems (DAS) are subject to complex road environments and vehicle behaviors and increasingly rely on sophisticated sensors and Artificial Intelligence (AI). These properties give rise to unique safety faults stemming from specification insufficiencies and technological performance limitations, where sensors and AI introduce errors that vary in magnitude and temporal patterns, posing potential safety risks. The Safety of the Intended Functionality (SOTIF) standard emerges as a promising framework for addressing these concerns, focusing on scenario-based analysis to identify hazardous behaviors and their causes. Although the current standard provides a basic cause-and-effect model and high-level process guidance, it lacks concepts required to identify and evaluate hazardous errors, especially within the context of AI. This paper introduces two key contributions to bridge this gap.

For further increase in thermal efficiency of heavy-duty diesel engines, flexible regulation of the heat release rate (HRR) profile combined with higher compression ratio could have more rooms to improve indicated thermal efficiency by overcoming various drawbacks relevant to higher compression ratio. A new ideal HRR profile, which starts as a kind of delta shape to fulfil the isobaric cycle from top-dead-center (TDC) and is followed by the significant increase in HRR to reach the maximum cylinder pressure in the retarded timing, was proposed. We call it as ‘High-heels’ HRR profile from its two-step-increase delta shape. To confirm the potential of the ideal HRR profile by utilizing a single- cylinder heavy-duty diesel engine, a variable fuel injection rate equipment, novel combustion chamber designs, and an offset orifices nozzle were investigated as the technologies for modifying HRR profile.

In this study, a new method to calculate the spray collapse in multiple-hole gasoline injectors was developed. The theoretical calculation method was proposed by applying the extended spray momentum theory. In this theoretical calculation method, the deflection of the spray direction toward the injector axis was calculated serially based on the imbalance of the momentum of backward gas-flow surrounding sprays. The calculation and spray observation for validation against the calculation result were performed under conditions with and without flash boiling.

In general, automatic braking uses an electric stability control (ESC) hydraulic unit that can automatically increase the hydraulic pressure in the wheel cylinder (hereinafter called wheel pressure), independent of the driver’s braking operation. The hydraulic unit should have sufficient pressure response to apply autonomous emergency braking (AEB). It was necessary for the hydraulic unit to have a high flow rate for the pressure response. To satisfy the performance requirements of the AEB, a brushless motor, which has a high maximum rotational speed and good response, is adopted for the hydraulic unit. Furthermore, sensorless control, which does not require a rotation angle sensor, has been developed so that the motor size can be small and common to conventional units. The developed sensorless control can switch the driving methods in three states: pre-rotation, low speed, and high speed.

Toyota Motor Corporation has developed a new battery electric vehicle (BEV) on the dedicated e-TNGA platform for BEVs, which was designed to lower the center of gravity of the vehicle and increase body stiffness. In addition to a full-time 4WD system, another feature of this new BEV is its pleasurable driving experience. A new inverter drive unit was developed for this system. Unlike the previous inverter, the advantage of the new inverter is that it is small enough to be mounted inside the transaxle housing, thereby contributing to the availability of interior and luggage space. The temperature rise of the power semiconductors in the inverter was reduced considerably by the development of a new power semiconductor for BEVs. This enables a parallel layout of two power semiconductors instead of three. The components of the inverter were also downsized. A coreless current sensor was adopted, and capacitors were developed with significantly lower capacitance.

Safety assurance is a central concern for the development and societal acceptance of automated driving (AD) systems. Perception is a key aspect of AD that relies heavily on Machine Learning (ML). Despite the known challenges with the safety assurance of ML-based components, proposals have recently emerged for unit-level safety cases addressing these components. Unfortunately, AD safety cases express safety requirements at the system level and these efforts are missing the critical linking argument needed to integrate safety requirements at the system level with component performance requirements at the unit level. In this paper, we propose the Integration Safety Case for Perception (ISCaP), a generic template for such a linking safety argument specifically tailored for perception components. The template takes a deductive and formal approach to define strong traceability between levels.

Conventional methods of physicochemical models require various experts and a high measurement demand to achieve the required model accuracy. With an additional request for faster development time for diagnostic algorithms, this method has reached the limits of economic feasibility. Machine learning algorithms are getting more popular in order to achieve a high model accuracy with an appropriate economical effort and allow to describe complex problems using statistical methods. An important point is the independence from other modelled variables and the exclusive use of sensor data and actuator settings. The concept has already been successfully proven in the field of modelling for exhaust gas aftertreatment sensors. An engine-out nitrogen oxide (NOX) emission sensor model based on polynomial regression was developed, trained, and transferred onto a conventional automotive electronic control unit (ECU) and also proves real-time capability.

Automotive manufacturers are working towards protecting the global environment by using filters to reduce particulate matter (PM) emissions from their vehicles. There is a growing demand for sensors that detect the small amounts of PM leaking through these filters, as they can aid in performing on-board diagnostics (OBD) and monitoring the function of these filters. Currently, vehicles predominantly use an electric resistance type PM sensor, which applies a voltage between electrodes, collects PM, and senses the generation of PM path. However, in response to tightening regulations on PM-OBD, the response time of the sensor needs to be optimized. Furthermore, the fast response time must not degrade the poisoning resistance in order to ensure durability. To shorten sensor response time, we have developed a 20 μm-gap electrode structure using a cross-section of laminated alumina sheets with printed electrodes, which can form PM paths at small PM amounts.

This paper describes an exhaust system using a new air-fuel ratio (hereinafter, A/F) sensor that contributes to low emissions and low fuel consumption of gasoline engines. As the first technical feature, the water splash resistance of the A/F sensor has been substantially improved which allows A/F control to be enabled without delay during engine cold start. To realize this capability, it is important that the sensor characteristics are not affected by the condensed water generated in the exhaust pipe. Therefore, a technique that has the effectiveness of a water splash resistance layer with water repellent function is demonstrated. As the second technical feature, the power consumption of the sensor has been substantially reduced. This is achieved by improving thermal efficiency of the sensor that the element can be activated at a low temperature.

This paper proposes an oil degradation sensor that informs the best time for oil replacement to achieve the right balance with oil conservation and engine protection. We found that free radicals in the engine oil generate by chain decomposition reactions of hydrocarbons by heat and the amount of them increases with an increase in running distance. Based on theoretical analysis and experiment results, the free radical concentrations have high correlations with pH and base number. The sensor using the principle of electron spin resonance (ESR) can measure the amount of free radical molecules in a non-contact method. The sensor successfully detected free radicals produced by the degradation of actual engine oil.

In the field of heavy-duty diesel engines, which require lifetime durability and high fuel efficiency, there is a growing demand for increased injection pressure and increased flow rate inside injection holes. This trend makes it important to prevent cavitation erosion of injector nozzles. This paper aims to clarify the relation between cavitation behavior and erosion damage experimentally by visualizing the flow inside diesel nozzles and to establish a new method for predicting cavitation erosion. To visualize internal flow, authors used the large-scale transparent nozzle whose Reynolds number and Cavitation number were matched with those of the actual real-size nozzle. Direct observation showed that the form of the cavitation changed from string-type cavitation to film-type cavitation with increasing needle lift.

Biofuels are expanding continuously in global market as one of renewable options to replace fossil fuels. Biodiesel is the most commonly used biofuel that can be blended into conventional diesels in any proportion. However, higher biodiesel blends may cause problems. One of its problems is precipitation formation arise from biodiesel may clog fuel filter at low temperature. This study focuses on fuel and environment factors on biodiesel precipitation and their influence degree on fuel filter clogging. The results indicate that monoglycerides and temperature have strong correlation with precipitate weight. Moreover, quantitative effect of precipitate weight on filter clogging was clarified.

Future diesel engine legislation Tier 4 / Stage V and EU6d demand further improvements to reduce CO2 while keeping the already low NOx emissions levels. For US trucks a more strict limit of 0.2 g/bhp-hr NOx emissions need to be achieved. In this trade-off, system costs and complexity of the after-treatment are defining the constraint in which the common rail fuel injection system layout has to be defined. The increase of rail pressure was in the past the major step to control the soot emissions in view of low engine-out NOx emissions by applying massive EGR. With the on-going development of NOx-aftertreatment by Selective Catalytic Reduction (SCR), conversion efficiencies of up to 97% allow to reduce the EGR usage and rail pressure usage. In that context, the steepness of injection rate, the nozzle flow rate and the injection pressure are remaining parameters to control the NOx emissions.

The purpose of this study is to elucidate flame propagation behavior of homogeneous propane-air mixture under application of non-uniform electric field. A needle-shaped electrode was attached to the ceiling and a plate electrode was set at bottom of combustion chamber, so that the electric field was applied in the direction of the chamber's vertical axis. A homogeneous propane-air mixture was supplied at equivalence ratio of 1.0 and was ignited by leaser induced breakdown under atmospheric pressure and room temperature. It was found that the flame front and plate electrode were repelled each other and a thin air layer was formed between the flame and plate electrode when a relatively low positive DC non-uniform electric field was applied to the needle-shaped electrode. It might be thought that the induced current was generated in the flame front, so that the flame front and plate electrode repelled each other.

With the diesel emissions and fuel consumption regulations and laws being tightened up, Common Rail System (CRS), capable of accurate and high-pressure diesel fuel injection, has become very popular in the world, and this CRS market is expected to continue to grow in the future. As use of the CRS becomes widespread, CRS is supposed to be used in a wide variety of environment, e.g. bad fuel (for example, much dust [1] and/or water), which increases concerns of CRS reliability. In an attempt to cope with such bad fuel properties, CRS and Fuel collected from the market was investigated. And based on this result, a new test method was worked out to simulate fuel stresses in the market. This test method verified the improved design of CRS with enhanced fuel robustness. This paper describes the new test method and the fuel robustness-enhancing effect of CRS based on the test method.

Diesel injection equipment is required to be more accurate and higher in pressure to meet the increasingly strict emission, fuel consumption regulations and higher engine performance. It also needs to achieve a number of requirements such as robustness against diversified market fuels, pressure maintenance characteristics in the idle stop system (ISS), easy installation to engine, etc. One of the key component to meet these demands is injector.

A response surface model of a diesel spray, parameterized by the internal geometries of a nozzle, is established in order to design the nozzle geometries optimally for spray mixing. The explanatory variables are the number of holes, the hole diameter, the inclined angle, the hole length, the hole inlet radius, K-factor and the sac diameter. The model is defined as a full second-order polynomial model including all the first-order interactions of the variables, and a total of 40 sets of numerical simulations based on D-optimal design are carried out to calculate the partial regression coefficients. Partial regression coefficients that deteriorate the estimate accuracy are eliminated by a validation process, so that the estimate accuracy is improved to be ±3% and ±15% for the spray penetration and the spread, respectively. Then, the model is applied to an optimization of the internal geometries for the spray penetration and the spray spread through a multi-objective genetic algorism.

We have developed a novel wafer process for capacitive sensing accelerometer using surface Micro Electrical Mechanical Systems (MEMS) technology and successfully applied to the fabrication process. Our new process combines with a single crystal SOI (Si on Insulator) wafer, high aspect ratio silicon etching and newly developed anhydrous HF/Alcohol etch process of silicon oxides. Although wet conditions such as HF/water etch occurs stiction of mobile structure, our anhydrous HF/Alcohol etch process technology occurs no stiction of mobile structures, because of gas phase (dry) process. In our process, we have achieved smaller-sized sensor chip compared to our conventional 2 axes accelerometer.

Increased interest in global warming issues requires rapid improvements in reduction of CO2 emissions. The automotive industry is placing high importance on improving fuel economy performance across their entire product lines. Charging Management System is a necessary element towards fuel economy improvement. Many of today's charging management systems perform at least two important functions: improving efficiency based on vehicle motion, and detecting battery state of charge. These systems become more complicated as more components (i.e. generators, current sensors and ECU) and software are added. Therefore, it is difficult to develop charging management systems for an entire product line and difficult to retrofit the system for vehicles already in production. A stand-alone charging management system solves these issues. This system is independent of the other vehicle systems. The software for improving fuel economy is installed in the generator or current sensor.