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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.

In recent years, an increase in vehicle weight due to the electrification of automobiles, specifically EVs, has increased the input loads on anti-vibration rubber parts. Moreover, the characteristics of these loads have also changed due to the rotational drive of electric motors, regenerative braking, and other factors. When designing a vehicle, in advance it is necessary to set specifications that take into account the spring characteristics and durability of the anti-vibration rubber parts in order to meet functional requirements. In this study, the hyperelastic and fatigue characteristics (S-N diagram and Haigh diagram) of Rubbers which is widely used for anti-vibration rubber parts, were experimentally obtained, and structural and fatigue analyses using FEM (Finite Element Method) were conducted in conjunction with spring and fatigue tests of anti-vibration rubber parts to determine the correlation between their spring and fatigue characteristics.

In recent years, swift changes in market demands toward achieving carbon neutrality have driven significant developments within the automotive industry. Consequently, employing computer simulations in the early stages of vehicle development has become imperative for a comprehensive understanding of performance characteristics. Of particular importance is the cooling performance of vehicles, which plays a vital role in ensuring safety and overall performance. It is crucial to predict optimal cooling performance, particularly about the heat generated by the powertrain during the initial phases of vehicle development. However, the utilization of thermal analysis models for assessing vehicle cooling performance demands substantial computational resources, rendering them less practical for evaluating performance associated with design changes in the planning phase.

Toyota has developed a new 2.4L L4 turbo (2.4L-T) engine with 8AT and 1-motor hybrid electric powertrains for midsize pickup trucks. The aim of these powertrains is to fulfill both strict fuel economy and emission regulations toward “Carbon Neutrality”, while exceeding customer expectations. The new 2.4L L4 turbocharged gasoline engine complies with severe Tier3 Bin30/LEVIII SULEV30 emission regulations for body-on-frame midsize pickup trucks improving both thermal efficiency and maximum torque. This engine is matched with a newly developed 8-speed automatic transmission with wide range and close step gear ratios and extended lock-up range to fulfill three trade-off performances: powerful driving, NVH and fuel economy. In addition, a 1-motor hybrid electric version is developed with a motor generator and disconnect clutch between the engine and transmission.

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.

Powertrain development requires an efficient development process with no rework and model-based development (MBD). In addition, to performance design that achieves low CO2 emissions is also required. Furthermore, it also demands fuel economy performance considering real-world usage conditions, and in North America, the EPA (U.S. Environmental Protection Agency) 5-cycle, which evaluates performance in a combination of various environments, is applied. This evaluation mode necessitates predicting performance while considering engine heat flow. Particularly, simulation technology that considers behavior based on engine temperature for Hybrid Electric Vehicle (HEV) is necessary. Additionally, in the development trend of vehicle aerodynamic improvement, variable devices like Active Grille Shutter (AGS) are utilized to contribute to reducing CO2 emissions.

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.

Ethanol blending is one method that can be used to reduce knock in spark ignition engines by decreasing the autoignition reactivity of the fuel and modifying its laminar flame speed. In this paper, the effects of ethanol blending on knock propensity and flame speed of petroleum and low-carbon gasoline fuels is analyzed. To do so, surrogate fuels were formulated for methanol-to-gasoline (MTG) and ethanol-to-gasoline (ETG) based on the fuels’ composition, octane number, and select physical properties; and 0-D and 1-D chemical kinetics simulations were performed to investigate reactivity and laminar flame speed, respectively. Results of MTG and ETG were compared against those of PACE-20, a well-characterized surrogate for regular E10 gasoline. Similarly to PACE-20, blending MTG and ETG with ethanol increases the fuel’s research octane number (RON) and sensitivity.

In the 1st generation Toyota "MIRAI" fuel cell stack, carbon protective surface coating is deposited after individual Ti bipolar plate being press-formed into the desired shape. Such a process has relatively low production speed, not ideal for large scale manufacturing. A new coating concept, consisting of a nanostructured composite layer of titanium oxide and carbon particles, was devised to enable the incorporation of both the surface treatment and the press processes into the roll-to-roll production line. The initial coating showed higher than expected contact resistance, of which the root cause was identified as nitrogen contamination during the annealing step that inhibited the formation of the composite film structure. Upon the implementation of a vacuum furnace chamber as the countermeasure, the issue was resolved, and the improved coating could meet all the requirements of productivity, conductivity, and durability for use in the newer generation of fuel cell stacks.

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.

Internal combustion engines will play an important role in the coming decades, even considering targets of carbon neutrality for a sustainable future. This will be especially true in regions where pure electrified vehicle implementation is not yet practical, or for long-range heavy load transportation purposes, even in regions where BEV infrastructure is well established. HEV/PHEV’s importance and contribution to CO2 emission reduction together with carbon neutral fuels such as hydrogen, e-fuel and biomass fuel etc. will remain crucial regardless of region/transport sectors. In this respect, brake thermal efficiency improvements by friction reduction needs further investigation. This is especially so with the crankshaft bearings’ lubrication system, which can provide as much as 40% of the total mechanical losses in some cases. It is a well-established fact, that plain bearings require a minimum oil flow volume to maintain their real function rather than oil pressure.

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.

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.

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.

In response to the steadily worsening impact of global warming, greater efforts are being made to achieve carbon neutrality. Toyota Motor Corporation developed an in-vehicle solar charging system that utilizes generated solar energy to drive the vehicle. While the ignition is off, energy generated from a solar panel is used to charge the main battery. Then, while the ignition is on, this energy is supplied to the 12 V system to reduce consumption of the main battery energy, thereby helping to improve the electric driving range. This 1st-generation solar charging system adopted in the Prius PHV in 2017 was the first mass-produced in-vehicle solar charging system in the world. In 2022, the 2nd-generation solar charging system was developed and adopted in the bZ4X, including performance improvements such as a newly designed solar roof and lightweight charging system.

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].

Contribution to carbon neutrality is one of the most important challenges for the automotive industry. Though CO2 emission has been reduced through electrification, internal combustion engines equipped in vehicles such as Hybrid Electric Vehicle (HEV) and Plug-in Hybrid Electric Vehicle (PHEV) are still necessary for the foreseeable future, and continuous efforts to improve fuel economy are demanded. To improve powertrain thermal efficiency, direct-injection turbocharged gasoline engines have been widely utilized in recent years. Super lean-burn combustion engine has been being researched as the next generation of turbocharged gasoline engines. It is known that an increase of the boost pressure causes deposit formation, which decrease the turbocharger efficiency, in the turbocharger compressor housing. To avoid the efficiency loss due to deposit, air temperature at compressor outlet has to be limited low.

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.

To prevent global warming, many countries are making efforts to reduce CO2 emissions toward achieving 2050 carbon neutrality. In order to reduce CO2 concentration quickly, in addition to spread of renewable energy and expansion of BEV, it is also important to reduce CO2 emissions by improving thermal efficiency of ICE (internal combustion engine) and utilizing carbon neutral fuels such as synthetic fuels and biofuels. It is well known that lean burn is an effective technology to increase thermal efficiency of engine highly. However, since NOx emission from lean burn engine cannot be reduced with three-way catalyst, there have been issues such as complicated system configuration due to the addition of NOx reduction catalyst or limiting lean operation to narrow engine speed and load in order to meet emission regulation of each country.