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This paper presents a custom integrated circuit (IC) on which circuit functions necessary for “Active Hydraulic Brake (AHB) system” are integrated, and its key component, “Current-to-Digital Converter” for solenoid current measurement. The AHB system, which realizes a seamless brake feeling for Antilock Brake System (ABS) and Regenerative Brake Cooperative Control of Hybrid Vehicle, and the custom IC are installed in the 4th-generation Prius released in 2015. In the AHB system, as linear solenoid valves are used for hydraulic brake pressure control, high-resolution and high-speed sensing of solenoid current with ripple components due to pulse width modulation (PWM) is one of the key technologies. The proposed current-to-digital converter directly samples the drain-source voltage of the sensing DMOS (double-diffused MOSFET) with an analog-to-digital (A/D) converter (ADC) on the IC, and digitizes it.

Merging a CAE shape optimization system and a concept Taguchi method SN-ratio index, a robustness-focused automated shape optimization method has been developed. Applying this method to diesel intake ports, with mold position tolerance set as the error factor, SN-ratio was defined for swirl stability. As a result of the optimization provided by a multi-objective genetic algorithm, simultaneous improvement of flux, swirl rotation and SN ratio was achieved.

Statistical Energy Analysis (SEA) is a promising tool for developing an efficient sound package design for reducing airborne interior noise at high frequencies. The optimal sound package, however, is not directly predicted by using the SEA vehicle model alone and therefore requires parametric studies of sound package configurations. This paper describes an effective method for using SEA modeling to achieve the desired interior noise level targets. A mathematical model, expressed by one equation, is derived on the assumption that the directions of the power flows are known in the SEA model. This equation describes the relationship between sound package properties and the resulting interior noise level. Using the relationship between weight and performance of sound package, an efficient configuration can be determined. The predicted sound pressure level of the vehicle interior with the optimized sound package correlated well to the experimental data for the case presented in this paper.

Previous studies have investigated the impacts of biofuel usage on the performance, drivability and durability of modern diesel engines and exhaust after-treatment systems including test work with different types, concentrations and mixtures of bio fuel components. During this earlier work vehicle fuel filter blocking issues were encountered during a field trial using various types of EN 14214 compliant Fatty Acid Methyl Ester (FAME) blended into EN 590 diesel. This paper summarises a subsequent literature review that was carried out looking into potential causes of this filter blocking and further work that was then carried out to expand on the findings. From this, a laboratory study was carried out to assess the increase in fuel filter blocking tendency (FBT) when various FAMEs from mixed sources were blended into EN 590 diesel at different concentrations, including levels above those currently allowed in the European market.

In the early stages of vehicle development, it is important for decision makers to understand a feasible constraint region that satisfies all system level requirements. The purpose of this paper is to propose a target cascading method to solve for a feasible design region which satisfies all constraints of the system based on model based simulation. In this method, the feasible design region is explored by using both global optimization methods and active learning techniques. In optimization problems, the inverse problem for understanding feasibility for specific designs is defined and solved. To determine the objective functions of the inverse problem, an index representing the achievement level of constraints from system requirements is introduced. To predict feasible regions in the specific design space, a surrogate model of minimized values of the index is trained by using a kriging model.

Reductions of hardware costs as well as implementations of new innovative functions are the main drivers of today's automotive electronics. Indeed more and more resources are spent on adapting existing solutions to different environments. At the same time, due to the increasing number of networked components, a level of complexity has been reached which is difficult to handle using traditional development processes. The automotive industry addresses this problem through a paradigm shift from a hardware-, component-driven to a requirement- and function-driven development process, and a stringent standardization of infrastructure elements. One central standardization initiative is the AUTomotive Open System ARchitecture (AUTOSAR). AUTOSAR was founded in 2003 by major OEMs and Tier1 suppliers and now includes a large number of automotive, electronics, semiconductor, hard- and software companies.

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.

In FOA (First Order Analysis) any vehicle body structure might be interpreted as a collective simple structure that can be decomposed into 3 fundamental structure types. The first structure is the “BEAM”, whose cross sectional properties as well as its material dominates the mechanical behavior, the second is the “PANEL (shear panel, plate, and shell)”, whose mechanical behavior can be varied by changing its geometrical properties in the thickness direction, i.e. adding beads or flanges. The third structure is the “JOINT”, which connects the proceeding structures, and transfer complex three-dimensional loads with three-dimensional deformation. In the present work, we shall propose a methodology to identify a portion of an arbitrary FE model of an automotive body structure, with a “BEAM” structure in the FOA approach. In the latter chapter of this paper, cross section loads will be related with cross sectional properties in the aspect of the element strain energy concept.

In a Diesel engine with a Diesel particulate filter (DPF) system, high-sulfur fuel causes white smoke containing odorous and harmful pollutants during DPF regeneration. This study investigates the conditions and mechanisms of sulfur-related white smoke generation. Engine and vehicle tests found that sulfur compounds emitted from the engine accumulated on the catalysts in the DPF system and were emitted as white smoke during DPF regeneration. The white smoke was observed when the catalyst temperature was more than 450°C, under conditions such as the early stage of DPF regeneration. Model gas tests were conducted to clarify the mechanism of the white smoke. It was found that SO2 emitted from the engine was oxidized to SO3 on the catalyst, which was then mainly absorbed on the oxidation catalyst support (Al2O3). Then, the absorbed SO3 was desorbed and converted into white smoke.

This paper considers an application of reference governor (RG) to automotive diesel aftertreatment temperature control. Recently, regulations on vehicle emissions have become more stringent, and engine hardware and software are expected to be more complicated. It is getting more difficult to guarantee constraints in control systems as well as good control performance. Among model-based control methods that can directly treat constraints, this paper focuses on the RG, which has recently attracted a lot of attention as one method of model prediction-based control. In the RG, references in tracking control are modified based on future prediction so that the predicted outputs in a closed-loop system satisfy the constraints. This paper proposes an online RG algorithm, taking account of the real-time implementation on engine embedded controllers.

Due to the global economic downturn and higher environmental awareness, the social demands for low cost and fuel efficient vehicles are increasing. At the same time the engine power is increasing and customer expectations of reliability and NVH levels are increasing. To meet all the requirements, engineers are challenged to design light weight parts with higher performance. However, unconsidered mass reduction carries a risk of compromised NVH, Functional Reliability, and other functional demands. In order to resolve this contradiction, it is important to establish a basic structure with minimum necessary mass at the concept design phase, when there are still many degrees of freedom in the design space. Hence, a multi-objective optimization CAE methodology applicable for designing the basic structure of the Engine system was developed and is detailed below.

The effects of intake dilution with various dilution gases including nitrogen, argon, and carbon dioxide on low temperature diesel combustion were investigated in a naturally aspirated DI diesel engine to understand the mechanism of the simultaneous reductions in smoke and NOx with ultra-high EGR. NOx almost completely disappears with the intake oxygen concentration diluted below 16% regardless of the kind of dilution gas. Smoke emissions decrease with increased heat capacity of the charged gas due to promotion of mixture homogeneity with longer ignition delays. Intake dilution with the 36% CO2 + 64% Ar mixture which has a similar specific heat capacity as N2 shows lower smoke emissions than with N2. Chemical kinetics analysis shows that carbon dioxide may help to reduce NOx and soot by lowering the reaction temperature as well as by changing the concentrations of some radicals or/and species related to soot and NOx formation.

Alcohol fuels that can be produced from cellulose continue to become more widely used in gasoline engines. This research investigated the application of alcohol to diesel engines with the aims of improving the combustion of diesel engines and of utilizing alternative fuels. Two methods were compared, a method in which alcohol is injected into the air intake system and a method in which alcohol is blended in advance into the diesel fuel. Alcohol is an oxygenated fuel and so the amount of soot that is emitted is small. Furthermore, blended fuels have characteristics that help promote mixture formation, which can be expected to reduce the amount of soot even more, such as a low cetane number, low viscosity, low surface tension, and a low boiling point. Ethanol has a strong moisture-absorption attribute and separates easily when mixed with diesel fuel. Therefore, 1-butanol was used since it possesses a strong hydrophobic attribute and does not separate easily.

In diesel engines with a straight intake port and a lipless cavity to restrict in-cylinder flow, an injector with numerous small-diameter orifices with a narrow angle can be used to create a highly homogeneous air-fuel mixture that, during PCCI combustion, dramatically reduces the NOX and soot without the addition of expensive new devices. To further improve this new combustion concept, this research focused on cooling losses, which are generally thought to account for 16 to 35% of the total energy of the fuel, and approaches to reducing fuel consumption were explored. First, to clarify the proportions of convective heat transfer and radiation in the cooling losses, a Rapid Compression Machine (RCM) was used to measure the local heat flux and radiation to the combustion chamber wall. The results showed that though larger amounts of injected fuel increased the proportion of heat losses from radiation, the primary factor in cooling losses is convective heat transfer.

This research investigates the influences of the injection timing, injection pressure, and compression ratio on the combustion and exhaust emissions in a single cylinder 1.0 L DI diesel engine operating with ultra-high EGR. Longer ignition delays due to either advancing or retarding the injection timing reduced the smoke emissions, but advancing the injection timing has the advantages of maintaining the thermal efficiency and preventing misfiring. Smokeless combustion is realized with an intake oxygen content of only 9-10% regardless of the injection pressure. Reduction in the compression ratio is effective to reduce the in-cylinder temperature and increase the ignition delay as well as to expand the smokeless combustion range in terms of EGR and IMEP. However, the thermal efficiency deteriorates with excessively low compression ratios.

Due to new CO2 regulations and increasing demand for improved fuel economy, reducing aerodynamic drag has become more critical. Aerodynamic drag at the rear of the vehicle accounts for approximately 40% of overall aerodynamic drag due to low base pressure in the wake region. Many studies have focused on the wake region structure and shown that drag reduction modifications such as boattailing the rear end and sharpening the rear edges of the vehicle are effective. Despite optimization using such modifications, recent improvements in the aerodynamic drag coefficient (Cd) seem to have plateaued. One reason for this is the fact that vehicle design is oriented toward style and practicality. Hence, maintaining flexibility of design is crucial to the development of further drag reduction modifications. The purpose of this study was to devise a modification to reduce rear drag without imposing additional design restrictions on the upper body.

Technological development of materials derived from plants (e.g., polylactic acid (PLA), and the like) is required to break dependence on fossil fuels and reduce CO2. PLA has inferior hydrolysis resistance, impact resistance, and molding ability than polypropylene (PP), and in order to overcome these disadvantages, a novel PP/PLA alloy has been conceived where PLA is incorporated into a PP matrix. By optimizing compatibilizer and elastomer addition, PLA has been successfully dispersed into a PP matrix at a sub-micron order, and interior parts have been successfully developed that fulfill the performance, appearance, and mass-production capability requirements for practical application.

To resolve two major problems of conventional CFD-based shape optimization technology: (1) dependence of the outcome on the selection of design parameters, and (2) high computational costs, two types of innovative inverse analysis technologies based on a mathematical theory called the Adjoint Method were developed in previous studies for maximizing an arbitrary hydrodynamic performance aspect as the cost function: surface geometry deformation sensitivity analysis to identify the locations to be modified, and topology optimization to generate an optimal shape. Furthermore, these technologies were extended to transient flows by the application of the transient Adjoint Method theory. However, there are many cases around flow path shapes in vehicles where performance with respect to heat or concentration, such as the total amount of heat transfer or the flow rate of a specific gas component, is very important.

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.

In recent years, GPFs (Gasoline particulate filters) have been installed in gasoline engines to comply with stricter environmental regulations in China and Europe. In particular, coated-GPFs having a catalytic purification function are required to have high conversion performances, high filter efficiencies in the sense of a high collection efficiency, and low pressure loss. It is not easy to design a filter that satisfies all these parameters. Experimental studies are being conducted, but it is costly to study in trial productions. In this technical paper, a GPF design optimization method will be proposed that combines multi-scale simulation, surrogate models by machine learning, and an optimization algorithm. By using this method, a GPF design that minimizes pressure loss while providing high conversion performance and particle collection rates that satisfy current regulations can be created.