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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.

Knock in spark-ignition (SI) engines has been a subject of many research efforts and its relationship with high efficiency operating conditions keeps it a contemporary issue as engine technologies push classical limits. Despite this long history of research, literature is lacking coherent and generalized descriptions of how knock is affected by changes in the full cylinder temperature field, residence time (engine speed), and air/fuel ratio. In this work, two dimensionless numbers are applied to fully 3D SI conditions. First, the characteristic time of autoignition (ignition delay) is compared against the characteristic time of end-gas deflagration, which was used to predict knocking propensity. Second, the temperature gradient of the end-gas is compared against a critical detonation-based temperature gradient, which predicts the knock intensity.

Combustion in a lean atmosphere diluted with a large amount of air can greatly improve fuel efficiency by reducing cooling loss [1, 2]. On the other hand, when air-fuel mixture in cylinder becomes lean, the turbulent combustion speed will decrease, resulting in problems such as the generation of unburned hydrocarbon (HC) and combustion instability [3, 4]. In order to solve these problems, it is important to increase the turbulence intensity and combustion speed [5, 6, 7, 8, 9, 10]. When designing combustion in cylinder by using Computational Fluid Dynamics (CFD), K-epsilon model is widely used for a turbulence model, and the calculated turbulence energy k or turbulence intensity u’ have been used as important indices of combustion velocity [11, 12].

This paper describes a new control technology that coordinates the operation of multiple actuators in a new hybrid electric vehicle (HEV) system consisting of a turbocharged engine, front and rear electric motors, two clutches, and a 6-speed automatic transmission. The development concept for this control technology is to achieve the driver’s desired acceleration G with a natural feeling engine speed. First, to realize linear acceleration G even while the engine is starting from EV mode, clutch hydraulic pressure reduction control is implemented. Furthermore, the engine start timing is optimized to prevent delayed drive force response by predicting the required maximum power during cranking. Second, to realize linear acceleration, this control selects the proper gear position based on the available battery power, considering noise and vibration (NV) restrictions and turbocharging response delays.

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.

In Toyota’s 2nd generation FCV, an electric turbo-type air compressor has been adopted for downsizing and cost reduction. Automotive Fuel Cell applications present several challenges for implementing a turbo-type air compressor. When operating a fuel cell in high-temperature or high-altitude locations, the FC stack must be pressurized to prevent dry-up. The flow rate vs pressure conditions that the FC must pass through or in some cases operate at are typically within the surge region of a turbo-type air compressor. Additionally, Toyota requires quick air transient response (< 1 sec) for power generation, energy management, and FC dry-up prevention. If the turbo-type air compressor is not precisely controlled during quick transients, it can easily enter the surge region.

Combustion of a lean air-fuel mixture diluted with a large amount of air or Exhaust Gas Recirculation (EGR) gas is one of the important technologies that can reduce thermal NOx and improve gasoline engine fuel economy by reducing cooling loss. On the other hand, lean combustion increases unburned Hydro Carbon (HC) and unburned loss compared to stoichiometric combustion. This is because lean combustion reduces the burning rate of the air-fuel mixture and forms a thick quenching layer near the wall surface. In this study, the relationship between the thickness of the unburned HC and the excess air ratio is analyzed using Laser Induced Fluorescence (LIF) method and Computational Fluid Dynamic (CFD) of combustion. The HC distribution near the engine liner when the excess air ratio is increased is investigated by LIF. As a result, it is found that the quenching distance of the flame in the cylinder is larger for lean conditions than the general single-wall quenching relationship.

This paper describes an exhaust system using a new air-fuel ratio (hereinafter, A/F) sensor that contributes to low emissions and low fuel consumption of gasoline engines. As the first technical feature, the water splash resistance of the A/F sensor has been substantially improved which allows A/F control to be enabled without delay during engine cold start. To realize this capability, it is important that the sensor characteristics are not affected by the condensed water generated in the exhaust pipe. Therefore, a technique that has the effectiveness of a water splash resistance layer with water repellent function is demonstrated. As the second technical feature, the power consumption of the sensor has been substantially reduced. This is achieved by improving thermal efficiency of the sensor that the element can be activated at a low temperature.

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.

When the air conditioning (A/C) is turned on, the intake air to the HVAC is cooled at the evaporator. This is not only used for cooling the air temperature but also to dehumidify. Therefore, for a typical automatic climate control system, A/C will automatically operate even in winter (cold ambient temperature conditions) in order to prevent the windows from fogging despite its effect on fuel economy. In some applications, a humidity sensor is installed on top of the windshield and when the probability of fogging is low the A/C operation is disabled automatically to prevent unnecessary compressor operation which can increase fuel consumption. However, humidity sensor is not widely adopted as it requires some space to be installed and the cost is relatively expensive compared with other HVAC equipped sensors. In this study, a system was invented that disables the compressor operation when the fogging probability is low without using the conventional humidity sensor.

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.

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.

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.

The quantity of heavy components in fuel is increasing as automotive fuels diversify, and engine oil formulations are becoming more complex. These trends result in the formation of larger amounts of carbon deposits as reaction byproducts during combustion, potentially worsening the susceptibility of the engine to knock [1]. The research described in this paper aimed to identify the mechanism that causes knocking to deteriorate due to carbon deposits in low to medium engine load ranges, which are mainly used when the vehicle drives off and accelerates. With this objective, the cylinder temperature and pressure with and without deposits were measured, and it was found that knocking deteriorates in a certain range of ignition timing.

Occurrence of knock in spark ignition (SI) engines is usually suppressed by inhibiting auto-ignition of the fuel-air mixture. A steep increase in pressure by auto-ignition of the local mixture is thought to initiate the pressure oscillation, which results in knock. Therefore, in order to prevent knock, the strength of the pressure oscillation would be decreased by reducing the local heat release of the end gas. In this study, the oxidation reaction rate of the auto-ignition was attempted to be reduced by dilution of the mixture. The effect of mixture dilution on the strength of pressure oscillation, that is knock intensity, was examined using a rapid compression machine (RCM) and a single cylinder SI engine. The test result of compression ignition of homogeneous mixture using RCM showed that increase in dilution ratio could decrease the knock intensity even if the input heat increased and the auto-ignition timing advanced.

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.

Toyota Motor Corporation has developed a new series of engines under the Toyota New Global Architecture (TNGA) design philosophy, which aims to satisfy customer requirements for both fun-to-drive dynamic performance and better fuel economy by adopting a high-speed combustion concept to improve thermal efficiency and specific power. This new engine series achieves a maximum engine thermal efficiency of 40%, a specific power ratio of 60 kW/l, and lower emissions by combining high-speed combustion and a high compression ratio with a high-tumble intake port, high-energy ignition coil, high-pressure multi-hole nozzle direct injector, and new electrical variable valve timing (VVT). The first engine in this series is a new 4-cylinder 2.5-liter gasoline naturally aspirated engine for use in passenger cars alongside a new TNGA 8-speed automatic transmission, which was introduced for minivans and SUVs in the U.S. market in 2016.

A new shift control system using a model-based control method for stepped automatic transmissions. Using a gear train numerical formula model, the model-based shift control system is constructed using minimum calibration parameters with feedforward and feedback controllers. It also adopts control target values for the input shaft revolution and output shaft torque, thus enabling precise control that provides the most suitable shift feeling in various driving situations and for various vehicle characteristics. Furthermore, the model-based shift control system improves robustness in terms of disturbance elements such as production tolerance, time degradation, and use environment. Toyota has adopted this model-based shift control system in its UA80/UB80 8-speed automatic transmissions for front-wheel-drive vehicles and its AGA0 10-speed automatic transmission for rear-wheel-drive vehicles. This paper describes the details of this model-based shift control system.