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Heavy vehicles such as construction machinery generally require a large traction force. For this reason, axle components are equipped with a final reduction gear to provide a structure that can generate a large traction force. Basic analysis of vertical load, horizontal load (traction force), centrifugal force, and torsional torque applied to the wheels of heavy vehicles such as construction machinery and industrial vehicles, as well as actual working load analysis during actual operations, were conducted and compiled into a load analysis diagram. The loosening tendency of wheel bolts and nuts that fasten the wheel under actual working load was measured, and the loosening analysis method was presented. The causes of wheel fall-off accidents in heavy trucks, which have recently become a problem, were examined. Wheel bolts are generally tightened by the calibrated wrench method using a torque wrench.

A special spot weld element (SWE) is presented for simplified representation of spot joints in complex structures for structural durability evaluation using the mesh-insensitive structural stress method. The SWE is formulated using rigorous linear four-node Mindlin shell elements with consideration of weld region kinematic constraints and force/moments equilibrium conditions. The SWEs are capable of capturing all major deformation modes around weld region such that rather coarse finite element mesh can be used in durability modeling of complex vehicle structures without losing any accuracy. With the SWEs, all relevant traction structural stress components around a spot weld nugget can be fully captured in a mesh-insensitive manner for evaluation of multiaxial fatigue failure.

Optimizing the specifications of the parts that make up the vehicle is essential to develop a high performance and quality vehicle with price competitiveness. Optimizing parts specifications for quality and affordability means optimizing various factors such as engineering design specifications and manufacturing processes of parts. This optimization process must be carried out in the early stages of development to maximize its effectiveness. Therefore, in this paper, we studied the methodology of building a database for parts of already developed vehicles and optimizing them on a data basis. A methodology for collecting, standardizing, and analyzing data was studied to define information necessary for specification optimization. In addition, AI technology was used to derive optimization specifications based on the 3D shape of the parts. Through this study, body parts specification optimization system using AI technology was developed.

The design of lightweight vehicle structures has become a common method for automotive manufacturers to increase fuel efficiency and decrease carbon emission of their products. By using aluminum instead of steel, manufacturers can reduce the weight of a vehicle while still maintaining the required strength and stiffness. Currently, Resistance Spot Welding (RSW) is used extensively to join steel body panels but presents challenges when applied to aluminum. When compared to steel, RSW of aluminum requires frequent electrode cleaning, higher energy usage, and more controlled welding parameters, which has driven up the cost of manufacturing. Due to the increased cost associated with RSW of aluminum, Refill Friction Stir Spot Welding (RFSSW) is being considered as an alternative to RSW for joining aluminum body panels. RFSSW consumes less energy, requires less maintenance, and produces more consistent welding in aluminum as compared to RSW.

Self-piercing riveting (SPR) are one of most important joining approaches in lightweight vehicle design for Body-in-white (BIW) manufacturing. Numerical simulation of the riveting process could significantly boost design efficiency by reducing trial-and-error experiments. The traditional Finite Element Method (FEM) with element erosion is hard to capture the large plastic deformation and complex failure behaviors in the SPR process. The smoothed Particle Galerkin Method (SPG) is a genuine meshless method based on Galerkin's weak form, which uses a novel bond-based failure mechanism to keep the conservation of mass and momentum during the material failure process. This study utilizes a combined FEM and SPG approach to join Aluminum sheet 5754 using a full three-dimensional (3D) model in LS-DYNA/explicit.

The wear of the piston ring-cylinder liner system in gasoline engines is inevitable and significantly impacts fuel economy. Utilizing a custom-built linear reciprocating tribometer, this study assesses the wear resistance of newly developed engine cylinder coatings. The custom device offers a cost-effective means for tribological evaluation, optimizing coating process parameters with precise control over critical operational factors such as normal load and sliding frequency. Unlike conventional commercial tribometers, it ensures a more accurate simulation of the engine cylinder system. However, existing research lacks a comprehensive comparative analysis and procedure to establish precision limits for such modified devices. This study evaluates the custom tribometer's repeatability compared to a commercial wear-testing instrument, confirming its potential as a valuable tool for advanced wear testing on engine cylinder samples.

As part of Nissan’s strategy of electrification and the shift to smart technologies, our powertrain department has two main pillars: zero emissions and ICE Evolution. As a core unit of ICE Evolution, we have developed a brand new 3.5L V6 Twin turbocharged gasoline engine for Nissan’s next generation full-size flagship SUV to deliver luxury and toughness at the highest level. This brand-new engine will be applied to vehicles in all corners of the world and must have strong performance in every corner. More specifically, it has to meet the latest emissions and fuel efficiency regulations, have strong power performance beyond expectation, and provide reliable drivability on rough roads and deserts. To achieve these requirements, the new engine is incorporating many cutting-edge technologies.

It is widely recognized that internal combustion engines (ICE) are needed for transport worldwide for years to come, however, demands on ICE fuel efficiency, emissions, cost, and performance are extremely challenging. Gasoline compression ignition (GCI) is one approach to achieve demanding efficiency and emissions targets. At Aramco Research Center-Detroit, an advanced, multi-cylinder GCI engine was designed and built using the latest combustion system, engine controls, and lean aftertreatment. The combustion system uses Aramco’s PPCI-diffusion process for ultra-low NOx and smoke. A P2 48V mild hybrid system was integrated on the engine for braking energy recovery and improved cold starts. For robust low-load operation, a 2-step valvetrain system was used for exhaust rebreathing. Test data showed that part-load fuel consumption was reduced 7 to 10 percent relative to a competitive 2.0L European diesel engine.

A multi-material design strategy of steel and aluminium alloy is a key solution in response to stringent emission requirements and to offset the additional weight of batteries in electric vehicles. However, dissimilar Al/steel welding is mainly challenging due to the formation of brittle and hard intermetallic compounds (IMC). In order to resolve the issue of IMC formation, the present study proposed an alternative manufacturing method consisting of friction surfacing deposition and arc welding. The proposed method involves two steps for dissimilar welding: step 1, friction surfacing deposition of aluminium alloy on the steel surface and step 2, arc welding of friction surfacing deposited steel and aluminium alloy.

Mo-free 1.6-GPa bolt was developed for a Variable Compression Turbo (VC-Turbo) engine, which is environment friendly and improves fuel efficiency and output. Mo contributes to the improvement of delayed fracture resistance; therefore, the main objective is to achieve both high strength and delayed fracture resistance. Therefore, Si is added to the developed steel to achieve high strength and delayed fracture resistance. The delayed fracture tests were performed employing the Hc/He method. Hc is the limit of the diffusible hydrogen content without causing a delayed fracture under tightening, and He is the diffusible hydrogen content entering under a hydrogen-charging condition equivalent to the actual environment. The delayed fracture resistance is compared between the developed steel and the SCM440 utilized for 1.2-GPa class bolt as a representative of the current high-strength bolts.

Automotive body structures are being increasingly made in multi-material system consisting of steel, aluminum (Al) and fiber-reinforced plastics (FRP). Therefore, many joining techniques such as self-piercing riveting (SPR) and adhesive bonding have been developed. On the other hand, OEMs want to minimize the number of joining techniques to reduce the manufacturing complexity. Amount all joining methods, resistance spot welding (RSW) is the most advanced and cost-effective one for body-in-white. However, RSW cannot be applied for joining dissimilar materials. Therefore, a novel Rivet Resistance Spot Welding method (RRSW) was developed in which Al or FRP components can be directly welded to steel structures with existing welding systems. RRSW uses rivet-like double T-shaped steel elements as a welding adapter which are formed or integrated into Al or FRP components during their forming process. After that, they are welded to the steel components by RSW.

In the face of growing concerns about environmental sustainability and urban congestion, the integration of eco-driving strategies has emerged as a pivotal solution in the field of the urban transportation sector. This study explores the potential benefits of a CAV functioning as a virtual eco-driving controller in an urban traffic scenario with a group of following human-driven vehicles. A computationally inexpensive and realistic powertrain model and energy management system of the Chrysler Pacifica PHEV are developed with the field experiment data and integrated into a forward-looking vehicle simulator to implement and validate an eco-driving speed planning and energy management strategy assuming longitudinal automation. The eco-driving algorithm determines the optimal vehicle speed profile and energy management strategy.

The push for environmental protection and sustainability has led to strict emission regulations for automotive manufacturers as evident in EURO VII and 2026 EPA requirements. The challenge lies in maintaining fuel efficiency and simultaneously reducing the carbon footprint while meeting future emission regulations. Alcohol (primarily methanol, ethanol, and butanol) and ether (dimethyl ether) fuels, owing to their comparable energy density to existing fuels, the comparative ease of handling, renewable production, and suitable emission characteristics may present an attractive drop-in replacement, fully or in part as an additive, to the gasoline/diesel fuels, without extensive modifications to the engine geometry. Additionally, lean and diluted combustion are well-researched pathways for efficiency improvement and reduction of engine-out emissions of modern engines.

Multi-motor powertrain topologies are playing an increasingly important role in the development of heavy duty battery electric trucks due to the changing driving requirements of these vehicles. The use of multiple motors and/or transmissions in a powertrain provides additional degrees of freedom for the energy management. The energy management system (EMS) consist of the gear selection strategy and torque split between the drive motors. The aim of the EMS is thereby to achieve high energy efficiency in motor and regenerative operation, while reducing the number of gear changes to ensure driving comfort. Ongoing research focuses on the energy management system of hybrid electric trucks, where the aim is to optimize the torque split between the combustion engine and the electric motor. In this paper, the EMS for an electric truck is described as a mixed-integer nonlinear control problem. This type of optimal control problem is notoriously difficult to solve.

This paper proposes an optimization-based transmission gear shifting strategy for electrified powertrains with a transmission. With the demand for reduced vehicle emissions, electrified propulsion systems have garnered significant attention due to their potential to improve vehicle efficiency and performance. An electrified propulsion system architecture of significance includes multiple electric motors and a transmission where some driveline actuators can transmit torque through changing gear ratios. If there is at least one electric motor arranged before the input of the transmission and at least one after the transmission output, a unique design opportunity arises to shift gears in the most energy efficient manner.

In this paper, a control strategy for state of charge (SOC) allocation using navigation data for Hybrid Electric Vehicle (HEV) propulsion systems is proposed. This algorithm dynamically defines and adjusts a SOC target as a function of distance travelled on-line, thereby enabling proactive management of the energy store in the battery. The proposed approach incorporates variances in road resistance and adheres to geolocation constraints, including ultra-low emission zones (uLEZ). The anticipated advantages are particularly pronounced during scenarios involving extensive medium-to-long journeys characterized by abrupt topological changes or the necessity for exclusive electric vehicle (EV) mode operation. This novel solution stands to significantly enhance both drivability and fuel economy outcomes.

By installing an automated mechanical transmission (AMT) on heavy-duty vehicles and developing a reasonable shift strategy, it can reduce driver fatigue and eliminate technical differences among drivers, improving vehicle performance. However, after detaching from the experience of good drivers, the current shifting strategy is limited to the vehicle state at the current moment, and cannot make predictive judgment of the road environment ahead, and problems such as cyclic shifting will occur due to insufficient power when driving on the ramp. To improve the adaptability of heavy-duty truck shift strategy to dynamic driving environments, this paper first analyzes the shortcomings of existing traditional heavy-duty truck shift strategies on slopes, and develops a comprehensive performance shift strategy incorporating slope factors. Based on this, forward-looking information is introduced to propose a predictive intelligent shift strategy that balances power and economy.

Amid rising demands for fuel efficiency and emissions reduction, enhancing the thermal efficiency of gasoline engines has become imperative, which requires higher efficiency combustion strategies and integrated optimized design to maximize the work output from fuel. In gasoline engine, both increasing the compression ratio and using lean burn mode improve the ratio of useful work output to the energy input effectively, which resulting in higher thermal efficiency. Although there is limited scope for increasing the compression ratio due to the higher sensitivity to knocking, especially under stoichiometric conditions, reduced sensitivity could be got with leaner mixture fill into cylinder, which can further increase the specific heat ratio and thermal efficiency.

Battery electric vehicles are quickly gaining momentum to improve vehicle fuel efficiency and emission reduction. However, they must be designed to provide adequate range on a single charge combined with good acceleration performance, top speed, gradeability, and fast charging times. The paper presents a model for sizing the power train of an electric vehicle, including the power electronic converter, electric motor, and battery pack. A major assumption is that an optimal wheel slip rate can be achieved by modern vehicles using slip control systems. MATLAB/Simulink was used to model the vehicle powertrain. Simulations were conducted based on different speed and acceleration profiles. The purpose of the study focused on the motor and power electronics sizing requirements to achieve optimal range and performance.

This paper presents a feedback control strategy to minimize noise during dog clutch engagement in a hybrid transmission. The hybrid transmission contains an internal combustion engine(ICE) and 2 electric motors in P1 and P3 configurations. For efficiency during driving, at high vehicle speeds ICE is connected to wheels, via the dog clutch, hence shifting the vehicle from series to parallel hybrid mode. It is shown by experimental results that if the speed difference between the two sides of the dog clutch is below a certain level the engagement will be without clonk noise. In this paper the designed state feedback Linear Quadratic Integral (LQI) control provides the synchronization torque request to the P1 motor, hence matching the speed of one side of dog clutch with the other under the disturbance from combustion torque of the engine.