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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.

DENSO started a pilot demonstration of on-site methanation as “CO2 circulation plant” as proactive initiative for CO2 capture and storage/utilization (CCUS) technologies toward achievement of carbon neutrality by 2035 in our own business. The CO2 circulation plant was designed to capture CO2 primarily generated by the plant and recycle it as an energy source of the facility. We also started work on the development of electric swing CO2 adsorption (ESA) technology to achieve low-energy CO2 capture.

A hybrid powertrain offers the potential of a significant fuel saving for heavy-duty Diesel vehicles, which results in CO2 reduction of more than 20%, depending on the application. Using advanced future fuels, like HVO offers additional CO2 saving potential. In addition, the future Diesel engine needs to comply with the next generation of emission legislation, given by the European EUVII and the US EPA2027 regulatory frameworks. To achieve these limits, a combination of different technologies for the engine and the aftertreatment system are required. The proposed paper will present these technology solutions and their impact on CO2 and emissions by means of engine testing and simulation.

In case of electric vehicle (EV), as there are various thermal system configurations in each automotive manufacturer, suppliers should take a huge amount of time to select the best components for each OEM system. To solve this problem, a model-based development (MBD) method switching components easily and estimating their benefits efficiently is needed. In this study, the vehicle energy flow model was developed to select appropriate system configuration and components to balance cabin comfort and battery lifetime. To realize required accuracy and computing time, a 1D model, which has a motor, an air-cooling battery, a coolant circuit and heating ventilation and air-conditioning (HVAC) in a cabin, based on C-segment vehicle, was developed.

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.

Increasingly stringent regulations call for the reduction of emissions at engine startup to purify exhaust gas and reduce the amount of CO2 emitted. Air-fuel ratio (A/F) sensors detect the composition of exhaust gas and provide feedback to control the fuel injection quantity in order to ensure the optimal functioning of the catalytic converter. Reducing the time needed to obtain feedback control and enabling the restriction-free installation of A/F sensors can help meet regulations. Conventional sensors do not activate feedback control immediately after engine startup as the combination of high temperatures and splashes of condensed water in the exhaust pipe can cause thermal shock to the sensor element. Moreover, sensors need to be installed near the engine to increase the catalyst reaction efficiency. This increases the possibility of water splash from the condensed water in the catalyst.

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.

The subject of this paper is to discuss the use of advanced combustion controls of direct injection diesel engines, to achieve simultaneous improvements in thermal efficiency while maintaining minimum pollutant emissions. In recent years, the emissions produced in the transportation sector are becoming increasingly scrutinized, leading to significantly strengthened emissions legislations with regard to NOx and CO2, especially under Real Driving Emission (RDE) conditions. Therefore, diesel combustion improvements are key to overcoming these challenges. This paper reports the following two innovative Diesel combustion control technologies to realize the objectives mentioned above. 1 Combustion improvement by accurate Combustion Rate Shaping (CRS), CRS enables direct control of in-cylinder pressure trace and heat release rate.

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.

Diesel engines have smoke trade-offs with both NOx and combustion noise. Both the increment of air entrainment into the spray and deceleration of heat release rate slope which become quickly thanks to the increase of air entrainment are effective for overcoming the trade-off between smoke emission and combustion noise. In this study, effect of quick rising injection rate and pre-injection was focused as an enabler for the both. The mechanism of improvement in the trade-off caused by the quick rising injection rate and pre-injection was clarified by analyzing characteristics of spray and combustion, interaction of pre-injected spray to main-injected spray and behavior of smoke emission. Some visualization techniques were adapted to analysis of sprays and combustions. Spray momentum measurement was used for the air entrainment and mixture formation process analyzation.

The set-off length (also referred to as the “lift-off length”) is reduced by the re-entrainment of the burned gas by the backward flow surrounding a diesel spray jet produced by a multi-hole nozzle. In the present study, to estimate the equivalence ratio at the set-off length, a means of estimating the amount of burned gas that is re-entrained into the near-nozzle region of the diesel spray jet was established. The results revealed that the suppression of soot formation in quasi-steady diesel spray flames produced by a multi-hole nozzle and a high injection pressure is not attained by reducing the equivalence ratio at the set-off length. Analysis of the amount of soot along the spray axis using a two-color method revealed that the maximum soot amount position appears in a quasi-steady spray flame, after the collapse of the head vortex in which a dense soot cloud is formed. The maximum soot amount position does not change even if the injection pressure varies.

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.