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To adapt to Battery Electric Vehicle (BEV) integration, the significance of protective designs for battery packs against ground impact caused by road debris is very high, and there is also a keen interest in the feasibility assessment technique using Computer-Aided Engineering (CAE) tools for prototype-free evaluations. However, the challenge lies in obtaining real-world empirical data to verify the accuracy of the predictive CAE model. Collecting real-world data using actual battery pack can be time-consuming, costly, and accurately ascertaining the precise direction, magnitude, and location of the force applied from the road to the battery pack poses a challenging task. Therefore, in this study, we developed a methodology using machine learning, specifically Gaussian process regression (GPR), to perform inverse analysis of the direction, magnitude, and location of vehicle-road contact forces during rough road conditions.

The purpose of this study is to propose braking characteristics that are easy for drivers to handle in a system in which braking and driving operations are performed by hand. Genetic algorithm optimization of braking characteristics showed that the best deceleration tracking was achieved by an FG diagram with a logarithmic function shape. In contrast, the slope of the optimal FG diagram tended to decrease as the driver's proportional gain increased.

Reducing the carbon emissions associated with ICE- containing vehicles is a complimentary step towards carbon neutrality alongside the introduction of vehicles using newer energy vectors. In this study, the authors investigated emissions and efficiency impact of fully renewable E10-grade gasoline fuels blended with sustainable components at both 90 RON and 96 RON in comparison with reference regular E0 and premium certification gasolines across a range of ICE vehicle applications. Both renewable fuels were blended to the Japan JIS K2022 2012 E10 specification. The study shows very low carbon gasolines are technically feasible and potentially have an important role to play in decarbonizing both new advanced technology ICE vehicles and, critically, the existing ICE vehicle parc in the transition towards a zero emissions future.

The development of electric vehicles has been progressed, rapidly, to achieve Carbon neutrality by 2050. There have been increasing concerns about Electromagnetic Compatibility (EMC) performance due to increasing power for power trains of vehicles. Because same power train system expands to some vehicles, we have developed numerical simulations in order to predict the vehicle EMC performances. We modeled a vehicle which has inverter noises by numerical simulation to calculate electric fields based on GB/T18387. We simulated the common mode noise which flows through the shielding braid of the high voltage wire harnesses. As a result, it is confirmed a correlation between the electric fields calculated by numerical simulation and the measured one.

This paper describes the development of a new e-AWD hybrid system developed for SUVs. This hybrid system consists of a high-torque 2.4-liter turbocharged engine and a front unit that contains a 6-speed automatic transmission, an electric motor, and an inverter. It also includes a rear eAxle unit that contains a water-cooled high-power motor, an inverter, and a reduction gear, as well as a bipolar nickel-metal hydride battery. By combining a turbo engine that can output high torque across a wide range of engine rpm with two electric motors (front and rear), this system achieves both smooth acceleration with a torquey driving feeling and rapid response when the accelerator pedal is pressed. In addition, new AWD control using the water-cooled rear motor realized more stable cornering performance than the previous e-AWD system.

Global focus on CO2 reduction and environmental protection is increasing. To comply with stricter exhaust gas regulations and reduce real world emissions, it is becoming increasingly important to improve the performance of three-way catalysts. Therefore, highly efficient conversion of hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) is required. In general, the more active the precious metals used, the better the conversion performance. However, precious metals have supply risks, such as price fluctuation and the uneven distribution of production areas. Therefore, it is necessary to lower emissions while also lowering the amount of precious metals used. This paper focuses on how catalysts are used and describes the development of a new three-way catalyst for the purpose of strengthening cold conversion and decreasing the usage of precious metals.

Nitric Oxide (NO) can significantly influence the autoignition reactivity and this can affect knock limits in conventional stoichiometric SI engines. Previous studies also revealed that the role of NO changes with fuel type. Fuels with high RON (Research Octane Number) and high Octane Sensitivity (S = RON - MON (Motor Octane Number)) exhibited monotonically retarding knock-limited combustion phasing (KL-CA50) with increasing NO. In contrast, for a high-RON, low-S fuel, the addition of NO initially resulted in a strongly retarded KL-CA50 but beyond the certain amount of NO, KL-CA50 advanced again. The current study focuses on same high-RON, low-S Alkylate fuel to better understand the mechanisms responsible for the reversal in the effect of NO on KL-CA50 beyond a certain amount of NO.

Low frequency interior wind noise is typically dominated by underfloor flow noise. The source mechanisms are fluctuating surface pressure loading from both flow turbulence and acoustic field levels developed in the semi-reverberant cavity between floor and road. Previous studies have used computation fluid dynamics (CFD) to estimate the aero-acoustic loading applied to a vibro-acoustic model, which is then used to predict the transmitted interior wind noise. This paper reports a new perspective in two respects. First it uses novel surface pressure microphone arrays to directly measure the underfloor aero-acoustic loading in the wind tunnel. Second, it considers two different underfloor aerodynamic configurations - with and without lightweight aero cover panels, which are installed primarily to reduce aerodynamic drag.

Collisions between opened doors and approaching vehicles such as bicycles are common occurrences in urban areas around the world. For example, in Chicago, 20% of all bicycle accidents involve collisions with doors, which occur over 300 times a year. In addition, there are concerns about a further rise in accidents due to the recent increase in home delivery services and bicycle commuting during the COVID-19 pandemic. Some advanced driver assistance systems (ADAS) that are designed to help prevent this type of accident have already been introduced. These systems detect approaching vehicles with sensors and alert the person opening the door via LED lights or a buzzer when the door is opened. The occupant must understand the meaning of the alert and stop opening the door quickly to prevent an accident. However, if the occupant is an elderly person or a child, it is difficult to stop opening the door quickly.

This paper presents a design method for continuous fiber composites in three-dimensional space with locally varying orientation distribution and their fabrication method. The design method is formulated based on topology optimization by augmented tensor field design variables. The fabrication method is based on Tailored Fiber Placement technology, whereby a CNC embroidery machine prepares the preform. The fiber path is generated from an optimized orientation distribution field. The preform is formed with vacuum-assisted resin transfer molding. The fabricated prototype weighs 120 g, a 70% weight reduction, achieving 3.5× mass-specific stiffness improvement.

The reduction of CO2 emissions is one of the most important challenges for the automotive industry to contribute to address global warming. Reducing friction of internal combustion engines (ICEs) is one effective countermeasure to realize this objective. The improvement of engine oil can contribute to reduce fuel consumption by reducing friction between engine parts. Electrification of ICE powertrains increases the overall efficiency of powertrains and reduces the average engine oil temperature during vehicle operation, due to intermittent engine operation. An effective way of reducing engine friction is to lower the viscosity of the engine oil in the low to medium temperature range. This can be accomplished while maintaining viscosity at high temperatures by reducing the base oil viscosity and increasing the viscosity modifier (VM) content to raise the viscosity index (so-called “flat viscosity” concept).

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.

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.

Routing quality always dominates the top 20% of in vehicle- navigation customer complaints. In vehicle navigation routing engines do not customize results based on customer behavior. For example, some users prefer the quickest route while some prefer direct routes. This is because in vehicle navigation systems are traditionally embedded systems. Toyota announced that new model vehicles in JP, CN, US will be connected with routing function switching from the embedded device to the cloud in which there are plenty of probe data uploaded from the vehicles. Probe data makes it possible to analyze user preferences and customize routing profile for users. This paper describes a method to analyze the user preferences from the probe data uploaded to the cloud. The method includes data collection, the analysis model of route scoring and user profiling. Furthermore, the evaluation of the model will be introduced at the end of the paper.

Silver metallic colors with thin and smooth aluminum flake pigments have been introduced for luxury brand OEMs. Regarding the paint formulation for these types of colors, low non-volatile(NV) and high aluminum flake pigment contents are known as technology for high metallic appearance designs. However, there are two technical concerns. First is mottling which is caused by uneven distribution of the aluminum flake pigments in paint film and second is poor film property due to high aluminum pigment concentration in paint film. Therefore, current paint systems have limitation of paint design. As a countermeasure for those two concerns, we had investigated cellulose nanofiber (CNF) dispersion liquid as both the coating binder and rheology control agent in a new type of waterborne paint system. CNF is an effective rheology control agent because it has strong hydrogen bonds with other fiber surfaces in waterborne paint.

Knowledge of experts is necessary for judging motor current waveforms. Here, we develop an automatic judgement system for motor current waveform by establishing an AI model trained by knowledge of experts and CAE technology.

As part of efforts to address climate change and improve energy security, researchers have improved the thermal efficiency of engines by expanding the lean combustion limit. To further expand the lean combustion limit, the authors focused not only on engine technology but the chemical reactivity of various fuel molecules. Furan and anisole were among the fuel molecules selected, based on the idea that promising candidates should enhance the flame propagation speed and have good knocking resistance. Engine testing showed that the lean limit can be expanded by using fuels with the right molecular structures, resulting in higher thermal efficiency.

Fuel economy measurement test is one of important engine tests to establish fuel economy engine oil performance standard to support CO2 emission reduction efforts in the automotive industry. On the other hand, it is difficult to develop an engine test without appropriate engine hardware that is designed to utilize low viscosity engine oils. A new firing fuel economy test was developed based on 2ZR-FXE engine designed for hybrid powertrain. The new test procedure aimed to provide the tool to evaluate new low viscosity grades such as 0W-8 and 0W-12 that were adapted in SAE J300 in 2015.

The research described in this paper focused on improving occupant ride comfort and road holding by suppressing sprung and unsprung vibration using a semi-active suspension system. It has been reported that occupants tend to perceive vertical vibrations in a frequency range between 4 and 8 Hz as uncomfortable (described below as the “mid-frequency range”). Previous research into semi-active suspension system has focused on reducing vibration in this mid-frequency range, as well as close to the sprung resonance frequency of between 1 and 2 Hz. Skyhook damper (SH) control is a typical ride comfort control used to damp vibration close to the sprung resonance frequency. However, since SH control is not capable of damping vibration in the mid-frequency range, the shock absorbers are configured with a lower damping factor. This helps to achieve a good balance between reducing vibration close to the sprung mass resonance and in the mid-frequency range.

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.