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Carbon neutrality has become a significant target. One essential parameter regarding energy consumption and emissions is the mass of vehicles. Lightweight design improves the result of vehicle life cycle assessment (LCA), increases efficiency, and can be a step towards sustainability and CO2 neutrality. Weight reduction through structural optimization is a challenging task. Typical design development procedures have to be overcome. Instead of just a facelift or the creation of a derivative of the predecessor design, completely alternative design creation methods have to be applied. Automated structural optimization is one tool for exploring completely new design approaches. Different methods are available and weight reduction is the focus of topology optimization. This paper describes a fatigue life homogenization method that enables the weight reduction of vehicle parts. The applied CAE process combines fatigue life prediction and topology optimization.

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.

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.

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.

Teammate Advanced Drive is a driving support system with state-of-the-art automated driving technology that has been developed for customers’ safe and secure driving on highways based on the Toyota’s Mobility Teammate Concept. This SAE Level 2 (L2) system assists overtaking, lane changes, and branching to the destination, in addition to providing hands-free lane centering and car following. The automated driving technology includes self-localization onto a High Definition Map, multi-modal sensing to cover 360 degrees of the surrounding environment using fusion of LiDARs, cameras, and radars, and a redundant architecture to realize fail-safe operation when a malfunction or system limitation occurs. High-performance computing is provided to implement deep learning for predicting and responding to various situations that may be encountered while driving.

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.

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.

Since bumper reinforcements are positioned at front/rear ends of vehicles, weight reduction of the bumper reinforcements enhances vehicle dynamic performance by reducing a yaw moment of inertia. CFRP (Carbon Fiber Reinforced Plastic) composites are attractive lightweight materials due to their excellent specific strength and rigidity. However, because of their relatively high cost, applications of CFRP materials to vehicle structural parts are limited. In this study we have developed a lightweight, structural part, which consists of a thin-walled Al (Aluminum) bumper reinforcement with a UD (Unidirectional)-CFRP sheet. The intention is to prevent an increased part cost by reducing the amount of Al and by minimizing the amount of CFRP. Compared to Al, UD-CFRP sheets have even higher tensile strength and modulus. When vehicles crash, bumper reinforcements may be subjected to bending force.

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.

Given a forecast of speed and load demands during a trip, a hybrid powertrain power-split Trajectory Optimization Problem (TOP) can be solved to optimize fuel consumption. This can be done on desktop to set performance benchmarks; however, it has been believed that the TOP could not be solved in real-time and is not a realizable controller. As such, several approximations of the TOP have been made in the interest of obtaining a real-time near-optimal controller, for example, Equivalent Consumption Minimization Strategies (ECMS) and their adaptive counterparts. These strategies decide on the power-split by, at each sampled time instant, minimizing a Horizon-0 (without predicting forward in time) composite function of fuel consumption and equivalent battery energy. The fuel economy that results from these strategies is highly sensitive to the calibration of the associated equivalence factor, and furthermore, must be chosen differently for different drive cycles.

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.

This paper presents the thermal management of a hybrid vehicle (HV) using a heat pump system in cold weather. One advantage of an HV is the high efficiency of the vehicle system provided by the coupling and optimal control of an electric motor and an engine. However, in a conventional HV, fuel economy degradation is observed in cold weather because delivering heat to the passenger cabin using the engine results in a reduced efficiency of the vehicle system. In this study, a heat pump, combined with an engine, was used for thermal management to decrease fuel economy degradation. The heat pump is equipped with an electrically driven compressor that pumps ambient heat into a water-cooled condenser. The heat generated by the engine and the heat pump is delivered to the engine and the passenger cabin because the engine needs to warm up quickly to reduce emissions and the cabin needs heat to provide thermal comfort.

Environmental awareness has increased on a global scale which pushed for a heavier demand for weight reduction and high transmission efficiency on manual transmissions (hereafter referred to as the “MT”) in improving vehicle driving and fuel economy performance. Comfortable shift feel is also continuously in demand by the customer because its sensitive performance can be directly recognized by the driver which may determine the transmission’s merchantability. The newly developed 6-speed MT (hereafter referred to as the “6MT”) has achieved size reduction (compact size), weight reduced, better fuel efficiency, and improvement in the shift feel which will continue to maintain its’ competitiveness in the future.

Future Automotive Systems Technology Simulator (FASTSim) is a free and open-source tool developed by National Renewable Energy Lab (NREL). Among the attractive capabilities of the FASTSim is that it can perform computationally efficient fuel economy simulations of automotive vehicles with reasonable accuracy for standard or arbitrary drive cycles. The modeling capability includes vehicles with various types of powertrains such as: conventional vehicles (CVs), hybrid-electric vehicles (HEVs), plugin hybrid electric vehicles (PHEVs) and battery-only electric vehicles (BEVs). The public version of FASTSim available from NREL is implemented in Excel, which achieves the goal of good accessibility to a broad audience, but has some limitations, including: i) bottleneck in computations when importing arbitrary drive cycles, ii) slower computations in general than other scripting or programming languages, and iii) less portable to integration with other applications and/or other platforms.

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.

Over the past decades, the automotive industry has made significant efforts to improve engine fuel economy by reducing mechanical friction. Reducing friction under cold conditions is becoming more important in hybrid vehicle (HV) and plug-in hybrid vehicle (PHV) systems due to the lower oil temperatures of these systems, which results in higher friction loss. To help resolve this issue, a new internal gear fully variable discharge oil pump (F-VDOP) was developed. This new oil pump can control the oil pressure freely over a temperature range from -10°C to hot conditions. At 20°C, this pump lowers the minimum main gallery pressure to 100 kPa, thereby achieving a friction reduction effect of 1.4 Nm. The developed oil pump achieves a pressure response time constant of 0.17 seconds when changing the oil pressure from 120 kPa to 200 kPa at a temperature of 20°C and an engine speed of 1,600 rpm.

In an effort to reduce mass, future automotive bodies will feature lower gage steel or lighter weight materials such as aluminum. An unfortunate side effect of lighter weight bodies is a reduction in sound transmission loss (TL). For barrier based systems, as the total system mass (including the sheet metal, decoupler, and barrier) goes down the transmission loss is reduced. If the reduced surface density from the sheet metal is added to the barrier, however, performance can be restored (though, of course, this eliminates the mass savings). In fact, if all of the saved mass from the sheet metal is added to the barrier, the TL performance may be improved over the original system. This is because the optimum performance for a barrier based system is achieved when the sheet metal and the barrier have equal surface densities. That is not the case for standard steel constructions where the surface density of the sheet metal is higher than the barrier.

One way to improve the fuel efficiency of HVs is to reduce the losses and size of the Power Control Unit (PCU). To achieve this, it is important to reduce the losses of power devices (such as IGBTs and FWDs) used in the PCU since their losses account for about 20% of the total loss of an HV. Furthermore, another issue when reducing the size of power devices is ensuring the thermal feasibility of the downsized devices. To achieve the objectives of the 4th generation PCU, the following development targets were set for the IGBTs: reduce power losses by 19.8% and size by 30% compared to the 3rd generation. Power losses were reduced by the development of a new Super Body Layer (SBL) structure, which improved the trade-off relationship between switching and steady-state loss. This trade-off relationship was improved by optimizing the key SBL concentration parameter.

The new eight-speed automatic transmission direct shift-8AT (UA80) is the first automatic transmission to be developed based on the Toyota New Global Architecture (TNGA) design philosophy. Commonizing or optimizing the main components of the UA80 enables compatibility with a wide torque range, including both inline 4-cylinder and V6 engines, while shortening development terms and minimizing investment. Additionally, it has superior packaging performance by optimizing the transmission size and arrangement achieving a low gravity center. It contributes to Vehicle’s attractiveness by improving driving performance and NVH. At the same time, it drastically improves fuel economy and quietness.

Since drowsy driving is a major cause of serious traffic accidents, there is a growing requirement for drowsiness prevention technologies. This study proposes a drowsy driving prediction method based on eye opening time. One issue of using eye opening time is predicting strong drowsiness before the driver actually feels sleepy. Because overlooking potential hazards is one of the causes of traffic accidents and is closely related to driver cognition and drowsiness, this study focuses on eye opening movements during driving. First, this report describes hypotheses concerning drowsiness and eye opening time based on the results of previous studies. It is assumed that the standard deviation of eye opening time (SDEOP) indicates driver drowsiness and the following two transitions are considered: increasing and decreasing SDEOP. To confirm the hypotheses, the relationship between drowsiness and SDEOP was investigated.