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In this paper, a newly developed Active Noise Control (ANC) system is introduced, that effectively reduces road noise, which becomes a major issue with electrified vehicles, and that enhances vehicle interior sound levels matching seamless acceleration by electric drive. Conventionally, reducing road noise using ANC requires numerous sensors and speakers, as well as a processor with high computing power. Therefore, the increase in system cost and the complexity of the system are obstacles to its spread. To overcome these issues, this system is developed based on four concepts. The first is a modular system configuration with unified interface to apply to various vehicle types and grades. The second is the integration and optimal placement of noise source reference sensors to achieve both reduction in number of parts and noise reduction performance.

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.

Bioethanol is being used as an alternative fuel throughout the world based on considerations of reduction of CO2 emissions and sustainability. It is widely known that ethanol has an advantage of high anti-knock quality. In order to use the ethanol in ethanol-blended gasoline to control knocking, the research discussed in this paper sought to develop a fuel separation system that would separate ethanol-blended gasoline into a high-octane-number fuel (high-ethanol-concentration fuel) and a low-octane-number fuel (low-ethanol-concentration fuel) in the vehicle. The research developed a small fuel separation system, and employed a layout in which the system was fitted in the fuel tank based on considerations of reducing the effect on cabin space and maintaining safety in the event of a collision. The total volume of the components fitted in the fuel tank is 6.6 liters.

The reduction of cycle-to-cycle variations (CCV) is a prerequisite for the development and control of spark-ignition engines with increased efficiency and reduced engine-out emissions. To this end, Large-Eddy Simulations (LES) can improve the understanding of stochastic in-cylinder phenomena during the engine design process, if the employed modeling approach is sufficiently accurate. In this work, an inhouse code has been used to investigate CCV in a direct-injected spark ignition (DISI) engine under fuel-lean conditions with respect to a stoichiometric baseline operating point. It is shown that the crank angle when a characteristic fuel mass fraction is burned, e.g. MFB50, correlates with the equivalence ratio computed as a local average in the vicinity of the spark plug. The lean operating point exhibits significant CCV, which are shown to be correlated also with the in-cylinder subfilter-scale (SFS) kinetic energy.

Today’s progress in electronic technologies is advancing the process of making vehicles more intelligent, and this is making driving safer and more comfortable. In recent years, numerous vehicles equipped with high-level Advance Driving Assist System (ADAS) have been put on the market. High-level ADAS can detect impending lane deviation, and control the vehicle so that the driver does not deviate from the lane. Lane departure prevention systems are able to detect imminent departure from the road, allowing the driver to apply control to prevent lane departure. These systems possess enormous potential to reduce the number of accidents resulting from road departure, but their effectiveness is highly reliant on their level of acceptance by drivers.

In this research, a material model was developed that has orthotropic properties with respect to in-plane damage to support finite element strength analysis of components manufactured from a randomly oriented long-fiber thermoplastic composite. This is a composite material with randomly oriented bundles of carbon fibers that are approximately one inch in length. A macroscopic characteristic of the material is isotropic in in-plane terms, but there are differences in the tension and compression damage properties. In consideration of these characteristics, a material model was developed in which the damage evolution rate is correlated with thermodynamic force and stress triaxiality. In-plane damage was assumed to be isotropic with respect to the elements. In order to validate this material model, the results from simulation and three-point bending tests of closed-hat-section beams were compared and found to present a close correlation.

A rubber sealing for a water-cooled battery pack plays a significant role to prevent water immersion into the inside of the pack. The appropriate design including the adjacent parts achieves a weight reduction of the battery pack by reducing the battery tray thickness and the quantity of bolts used in the whole battery pack. Generally, finite element analysis (FEA) is effective for the design optimization before proto-typing. However, the application to the sealing for a battery pack requires a large scale analysis, including the complicated contacts and large deformation of the rubber sealing, and results in unpractically long computation time and frequent computation errors due to the finite element distortion. A multi-scale structural analysis and the process on the rubber sealing for the battery pack has been developed to solve the above issues. This approach consists of 3 steps, which are single-unit, entire-scale and detailed structural analysis.

The dynamic performance of battery electric vehicles (BEV) is affected by battery output power, which depends on state of charge (SOC) and the temperature of battery cells. The temperature of the batteries varies in particular with the environment, in which the user stores the vehicle, and the battery output power. It is therefore necessary to employ thermal management systems that can control the battery temperature within the optimal range under severely hot and cold conditions in BEVs. A highly sophisticated thermal management system and its operation strategy were developed to fulfill the above requirements. The powertrain components to be thermo-controlled were located into two coolant circuits having different temperature range. The compact and efficient front-end heat exchangers were designed to optimally balance the cooling performance of powertrain, cabin comfort, vehicle aerodynamics and the vehicle design.

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.

A compact intelligent power unit capable of being installed under the rear seating was developed for the 2018 model year Accord Hybrid that is to be equipped with the SPORT HYBRID Intelligent Multi Mode Drive (i-MMD) system. The space under the rear seat features multiple constraints on dimensions. In the longitudinal direction, it is necessary to attempt to help ensure occupant leg room and to position the fuel tank; in the vertical direction, it is necessary to attempt to help ensure occupants comfort and a minimum ground clearance; and in the lateral direction, it is necessary to avoid the position of the body side frames and the penetrating section of the exhaust pipe. The technologies described below were applied in order to reduce the size of components, making it possible to position the IPU amid these constraint conditions.

It is experimentally known that the surface color of bearing balls gradually becomes brown during long term operation of the bearings under appropriate lubrication conditions. That exhibits the possibility of an estimation method for residual life of ball bearings without any abnormal wear on the surfaces by precise color measurements. Therefore, we examined what set colors on bearing balls by surface observation using scanning electron microscopy and subsurface analysis using transmission electron microscopy. Results showed that an amorphous carbon layer had gradually covered ball surfaces during operation of the bearings. The layer not only changed ball color but also made overall ball shapes closer to a complete sphere. The report also introduces a uniquely developed color analyzer which enabled color measurements on metallic surfaces, such as the above-mentioned balls.

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.

With accelerating exhaust gas regulations in recent years, not only CO / HC / NOx but also PN regulation represented by Euro 6 d, China 6 are getting stricter. PN reduction by engine combustion technology development also progresses, but considering RDE, PN reduction by after treatment technology is also indispensable. To reduce PN exhausted from the gasoline engine, it is effective to equip GPF with a filter structure. Considering the installation of GPF in limited space, we developed a system that so far replaces the second TWC with GPF for the TWC 2 bed system. In order to replace the second TWC with GPF, we chose the coated GPF with filtering and TWC functions. Since the initial pressure drop and the catalyst amount (purification performance) of coated GPF have a conflicting relationship, we developed the coated GPF that can achieve both the low initial pressure drop and high purification performance.

In recent years along with stringent the regulations, vehicles equipped with gasoline particulate filter (GPF) have started to launch. Compared to bare GPF, coated GPF (cGPF) requires not only PN filtration efficiency, low pressure drop, but also purification performance. In the wall flow type cGPF having a complicated the pore shape, the pore structure further irregularly changes depending on the coated state of the catalyst, so it is difficult to understand the matter of in-wall. In order to advance of cGPF function, it was researched that revealing the relevance between pore structure change in the wall and GPF function. Therefore, to understand the catalyst coated state difference, cGPF of several coating methods were prepared, and their properties were evaluated by various analyses, and performance was tested.

To evaluate the relationship between the exhaust gas purification performance and the catalyst pore properties related to gas diffusion, an elementary reaction model was combined with gas diffusion into catalyst pores, referred to as the pseudo-2D gas diffusion/reaction model. It was constructed for Pt/Al2O3 + CeO2 catalyst as lean NOx catalyst. The gas diffusion was described as macro pore diffusion between the catalyst particles and meso pore diffusion within the particle. The kinetic model was composed of 26 reactions of NO/CO/O2 chemistry including 17 Pt/Al2O3 catalyst reactions and 9 CeO2 reactions. Arrhenius parameters were optimized using activity measurement results from various catalysts with various pore properties, meso pore volume and diameter, macro pore volume and diameter, particle size, and washcoat thickness. Good agreement was achieved between the measured and calculated values.

Adhesive bonding is a key technology for the lighter weight of battery pack trays using aluminum material. A robust design method of adhesive bonding with the required strength for battery pack structure after degradation was developed to minimize variability of strength under various noise conditions. The parameter design based on Taguchi methods determined the optimum adhesive condition of the bonding process. To guarantee strength after degradation, it is essential to select a robust adhesive material and to minimize the strength variation derived from the adhesive material. The functional evaluation, which includes experimental design method, determined adhesive material with the minimum strength variation among material candidates. Then, robustness of the adhesive material itself has been evaluated as the result of collaboration with the adhesive material supplier. This analysis was able to regulate the compound ratio of raw materials without reducing the adhesive strength.

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.