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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.

When developing an off-road vehicle, it is essential to create excellent drivability that enables the vehicle to be driven on all surfaces while ensuring passenger comfort. Since durability is another indispensable performance aspect for these vehicles, the development method must be capable of considering a high-level combination of a wide range of performance targets. This paper proposes a method to identify the region in which each performance aspect is realized through a complex domain combination problem. The proposed method is helpful in the initial design stage when the detailed specifications of the target vehicle are not determined because it is capable of considering both the specifications and usage method of the target vehicle, such as the selection of road profiles and driving speeds as design variables. The proposed method has the advantage of enabling efficient concurrent studies to search for feasible regions.

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.

Since the regulations of CO2 emissions have been tightened in each country recently, each automotive manufacturer has responded by bringing competitive technologies that maximize efficiency while promoting vehicle electrification such as xEV. Not only the efficiency, we need to meet or exceed occupant performance and comfort expectations. The climate control system expends a large amount of energy to keep a comfortable environment, having a significant impact on fuel consumption and EV driving range. Therefore, many manufacturers try to save energy and improve occupant comfort quickly by using not only the conventional convective heating by HVAC but also the conductive heating to heat the human body directly such as seat and steering wheel heater. In this study, a radiative heater, which is more efficient than a convective heating to warm anterior thigh and shin where a conductive heating cannot warm, was applied to vehicle.

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 the development of a simplified fracture finite element (FE) model for resistance spot welds (RSW) of ultra-high-strength steel (UHSS) that can be incorporated into large-scale vehicle FE model. It is known that the RSW of UHSS generates two types of fracture modes: heat-affected zone (HAZ) and nugget zone fractures. Lap shear and peeling coupon tests using UHSS sheets found that the different RSW fracture modes occurred at different nugget diameters. To analyze this phenomenon, detailed simulated coupon tests were carried out using solid hexahedral elements. The analytical results revealed that RSW fractures are defined by both the application of plastic strain on the elements and the stress triaxiality state of the elements. A detailed model incorporating a new fracture criteria model recreated the different UHSS RSW fracture modes and achieved a close correlation with the coupon test results.

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.

The renewed platform of the upcoming flagship front-engine, rear-wheel drive (FR) vehicles demands high levels of driving performance, fuel efficiency and noise-vibration performance. The newly developed driveline system must balance these conflicting performance attributes by adopting new technologies. This article focuses on several technologies that were needed in order to meet the demand for noise-vibration performance and fuel efficiency. For noise-vibration performance, this article will focus on propeller shaft low frequency noise (booming noise). This noise level is determined by the propeller shaft’s excitation force and the sensitivity of differential mounting system. In regards to the propeller shaft’s excitation force, the contribution of the axial excitation force was clarified. This excitation force was decreased by adopting a double offset joint (DOJ) as the propeller shaft’s second joint and low stiffness rubber couplings as the first and third joints.

Torque loss reduction at differential gear unit is important to improve the fuel economy of automobiles. One effective way is to decrease the viscosity of lubricants as it results in less churning loss. However, this option creates a higher potential for thin oil films, which could damage the mechanical parts. At tapered roller bearings, in particular, wear at the large end face of rollers and its counterpart, known as bearing bottom wear is one of major failure modes. To understand the wear mechanism, wear at the rolling contact surface of rollers and its counterpart, known as bearing side wear, was also observed to confirm the wear impact on the tapered roller bearings. Because gear oils are also required to avoid seizure under extreme pressure, the combination of a phosphorus anti-wear agent and a sulfurous extreme pressure agent are formulated.

A new concept of an electromagnetic torque converter for hybrid electric vehicles is proposed. The electromagnetic torque converter, which is an electric system comprised of a set of double rotors and a stator, works as a high-efficiency transmission in the driving conditions of low gear ratio including a vehicle moving-off and as a starting device for an internal combustion engine. Moreover, it can be used for an electric vehicle driving as well as for a regenerative braking. In this concept, a high-efficiency drivetrain system for hybrid electric vehicles is constructed by replacing a fluid-type torque converter with the electromagnetic torque converter in the automatic transmission of a conventional vehicle. In this paper, we present the newly developed electromagnetic torque converter with a compact structure that enables mounting on a vehicle, and we evaluate its transmission efficiency by experiment.

With the goal of improving drivability, this research aimed to clarify the mechanism of vehicle longitudinal acceleration, focusing on tip-in acceleration. Conventional typical analysis methods include experimental modal and model-based analysis. However, since the former requires the measurement of impulses and other input forces while the vehicle is stopped, measurement under actual driving conditions is difficult. The latter requires characteristic values such as the stiffness and damping coefficients to be identified in advance, which cannot be achieved either easily or precisely. Therefore, this paper proposes a new experiment-based analysis method. This method enables the acquisition of engine torque and transmission torque/force by measuring only the acceleration values of some components under driving conditions.

It is important for vehicle concept planning to estimate fuel economy and the influence of vehicle vibration using virtual engine specifications and a virtual vehicle frame. In our former study, we showed the 1D physical power plant model with electrical starter, battery that can predict combustion transient torque, combustion heat energy and fuel efficiency. The simulation result agreed with measured data. For idling stop system, the noise and vibration during start up is important factor for salability of the vehicle. In this paper, as an application of the 1D physical power plant model (engine model), we will show the result of analysis that is starter shaft resonance and the effect on the engine mount vibration of restarting from idle stop. First, an engine model for 3.5L 6cyl NA engine was developed by energy-based model using VHDL-AMS. Here, VHDL-AMS is modeling language registered in IEC international standard (IEC61691-6) to realize multi physics on 1D simulation.

Current vehicle acoustic performance prediction methods, CAE (computer aided engineering) or physical testing, have some difficulty predicting interior sound in the mid-frequency range (300 to 1000 Hz). It is in this frequency range where the overall acoustic performance becomes sensitive to not only the contributions of structure-borne sources, which can be studied using traditional finite element analysis (FEA) methods, but also the contribution of airborne noise sources which increase proportional to frequency. It is in this higher frequency range (>1000 Hz) that physical testing and statistical CAE methods are traditionally used for performance studies. This paper will discuss a study that was undertaken to test the capability of a finite element modeling method that can accurately simulate air-borne noise phenomena in the mid-frequency range.

According to the U.S. National Highway Traffic Safety Administration, 743 pedal cyclists were killed and 48,000 were injured in motor vehicle crashes in 2013. As a novel active safety equipment to mitigate bicyclist crashes, bicyclist Pre-Collision Systems (PCSs) are being developed by many vehicle manufacturers. Therefore, developing equipment for evaluating bicyclist PCS is essential. This paper describes the development of a bicycle carrier for carrying the surrogate bicyclist in bicyclist PCS testing. An analysis on the United States national crash databases and videos from TASI 110 car naturalistic driving database was conducted to determine a set of most common crash scenarios, the motion speed and profile of bicycles. The bicycle carrier was designed to carry or pull the surrogate bicyclist for bicycle PCS evaluation. The carrier is a platform with a 4 wheel differential driving system.

The unsteady aerodynamic loads produced due to vehicle dynamic motions affect vehicle dynamic performance attributes such as straight-line stability or handling characteristics. To improve these dynamic performances, understanding the detailed mechanisms by which unsteady aerodynamic loads are caused during dynamic motions and the effects of unsteady aerodynamic loads on vehicle dynamic performance are needed. This paper describes the numerical study of unsteady aerodynamics of a 1/4 scale car model in dynamic pitching motion to clarify the detailed mechanisms by which unsteady aerodynamic loads are caused during the motion. Vortical structures around front wheelhouse and front under side of the body are analyzed by introducing schematic views to understand the mechanisms of unsteady flow fields. Furthermore, effects of aerodynamic devices devised based on the analyses on unsteady aerodynamics are discussed.

Replacing the metal car roof with conventional solar modules results in the increase of total car weight and change of center of mass, which is not preferable for car designing. Therefore, weight reduction is required for solar modules to be equipped on vehicles. Exchanging glass to plastic for the cover plate of solar module is one of the major approaches to reduce weight; however, load bearing property, impact resistance, thermal deformation, and weatherability become new challenges. In this paper a new solar module structure that weighs as light as conventional steel car roofs, resolving these challenges is proposed.

In recent years, improving the engine thermal efficiency is strongly required. To enhance the engine thermal efficiency, it is important to improve the engine anti-knock quality. Technologies for modifying engine cooling have been developed to improve anti-knocking quality of engines. However, excessive improvement of engine cooling leads to an increase in cooling heat loss. Therefore, it is necessary to clarify the effects of the temperature of each part of the engine such as engine head-cylinder, cylinder-liner, and piston on knocking and cooling heat loss. In this paper, computer aided engineering (CAE) is used to predict the effects of each part of the engine on engine knocking and cooling heat loss. Firstly, the amount of heat energy that air-fuel mixture receives from engine cylinder-head, cylinder-liner, and piston is calculated during the intake stroke. The result shows that the cylinder-liner contributes largest heat energy to air-fuel mixture, especially the exhaust side.

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.

To reduce interior noise effectively in the vehicle body structure development process, noise and vibration engineers have to first identify the portions of the body that have high sensitivity. Second, the necessary vibration characteristics of each portion must be determined, and third, the appropriate body structure for achieving the target performance of the vehicle must be realized within a short development timeframe. This paper proposes a new method based on the substructure synthesis method which is effective up to 200Hz. This method primarily utilizes equations expressing the relationship between driving point inertance change at arbitrary body portions and the corresponding sound pressure level (SPL) variation at the occupant's ear positions under external force. A modified system equation was derived from the body transfer functions and equation of motion by adding a virtual dynamic stiffness expression into the dynamic stiffness matrix of the vehicle.

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.