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The benefits introduced by the replacement of conventional centrifugal pumps with volumetric machines for Internal Combustion Engines (ICEs) cooling were experimentally and theoretically proven in literature. In particular, Sliding Rotary Vane Pumps (SVRPs) ensure to achieve an interesting reduction of ICEs fuel consumption and CO2 emissions. Despite volumetric pumps are a reference technology for ICE lubrication oil circuits, the application in ICE cooling systems still not represent a ready-to-market solution. Particularly challenging is the case of Heavy-Duty ICE due to the wide operating range the pump covers in terms of flow rate delivered. Generally, SVRPs are designed to operate at high speeds to reduce machine dimensions and, consequently, the weight. Nevertheless, speed increase could lead to a severe penalization of pump performance since the growth of the friction losses.

With the modernization of agriculture, the application of unmanned agricultural special vehicles is becoming increasingly widespread, which helps to improve agricultural production efficiency and reduce labor. Vehicle path-tracking control is an important link in achieving intelligent driving of vehicles. This paper designs a controller that combines path tracking with vehicle lateral stability for four-wheel steer/drive agricultural special electric vehicles. First, based on a simplified three-degrees-of-freedom vehicle dynamics model, a model predictive control (MPC) controller is used to calculate the front and rear axle angles. Then, according to the Ackermann steering principle, the four-wheel independent angles are calculated using the front and rear axle angles to achieve tracking of the target trajectory.

The current focus in the ongoing development of autonomous driving systems (ADS) for heavy duty vehicles is that of vehicle operational safety. To this end, developers and researchers alike are working towards a complete understanding of the operating environments and conditions that autonomous vehicles are subject to during their mission. This understanding is critical to the testing and validation phases of the development of autonomous vehicles and allows for the identification of both the nominal and edge case scenarios encountered by these systems. Previous work by the authors saw the development of a comprehensive scenario generation framework to identify an operating domain specification (ODS), or external and internal conditions an autonomous driving system can expect to encounter on its mission to form critical scenario groups for autonomous vehicle testing and validating using statistical patterns, clustering, and correlation.

Considering the current trend towards the electrification of commercial vehicles, the development of Beam eAxle solutions has become necessary. The utilization of an electric drive unit in heavy-duty solid axle-based commercial vehicles presents unique and demanding challenges. These include the necessity for elevated peak and continuous torque while meeting packaging constraints, structural integrity requirements, and extended service life. One such solution was developed by BorgWarner to address these challenges. This paper offers a comprehensive overview of the design and development process undertaken for this Dual Motor Beam eAxle system. This includes the initial comparison of various eAxle solutions, the specifications of components selected for this design, and the initial results from dyno and vehicle development.

In electric vehicle applications, the majority of the traction motors can be categorized as Permanent Magnet (PM) motors due to their outstanding performance. As indicated in the name, there are strong permanent magnets used inside the rotor of the motor, which interacts with the stator and causes strong magnetic pulling force during the assembly process. How to estimate this magnetic pulling force can be critical for manufacturing safety and efficiency. In this paper, a full 3D magnetostatic model has been proposed to calculate the baseline force using a dummy non-slotted cylinder stator and a simplified rotor for less meshing elements. Then, the full 360 deg model is simplified to a half-pole model based on motor symmetry to save the simulation time from 2 days to 2 hours. A rotor position sweep was conducted to find the maximum pulling force position. The result shows that the max pulling force happens when the rotor is 1% overlapping with the stator core.

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.

As the automotive industry focuses on fuel-efficient and eco-friendly vehicles along with reducing the carbon footprint, weight reduction becomes essential. Composite materials offer several advantages over metals, including lighter weight, corrosion resistance, low maintenance, longer lifespan, and the ability to customize their strength and stiffness according to specific loading requirements. This paper describes the design and development of the Rear Under Run Protection Device (RUPD) using composite materials. RUPD is designed to prevent rear under-running of passenger vehicles by heavy-duty trucks in the event of a crash. The structural strength and integrity of RUPD assembly are evaluated by applying loads and constraints in accordance with IS 14812:2005. The design objective was to reduce weight while maintaining a balance between strength, stiffness, weight, manufacturability, and cost.

Leaf Springs are commonly used as a suspension in heavy commercial vehicles for higher load carrying capacity. The leaf springs connect the vehicle body with road profile through the axle & tire assembly. It provides the relative motion between the vehicle body and road profile to improve the ride & handling performance. The leaf springs are designed to provide linear stiffness and uniform strength characteristics throughout its travel. Leaf springs are generally subjected to dynamic loads which are induced due to different road profiles & driving patterns. Leaf spring design should be robust as any failure in leaf springs will put vehicle safety at risk and cost the vehicle manufacturer their reputation. The design of a leaf spring based on conventional methods predicts the higher stress levels at the leaf spring center clamp location and stress levels gradually reduce from the center to free ends of the leaf spring.

Recent advancements towards autonomous heavy-duty vehicles are directly associated with increased interconnectivity and software driven features. Consequently, rise of this technological trend is bringing forth safety and cybersecurity challenges in form of new threats, hazards and vulnerabilities. As per the recent UN vehicle regulation 155, several risk-based security models and assessment frameworks have been proposed to counter the growing cybersecurity issues, however, the high budgetary cost to develop the tool and train personnel along with high risk of leakage of trade secrets, hinders the automotive manufacturers from adapting these third party solutions. This paper proposes an automated Threat Assessment & Risk Analysis (TARA) framework aligned with the standard requirements, offering an easy to use and fully customizable framework. The proposed framework is tailored specifically for heavy-duty vehicular networks and it demonstrates its effectiveness on a case study.

Threaded joints are considered the most basic of components. Although in use for over a century, significant problems still exist with their usage. Wheel bolt loosening in overloaded segments such as HD tippers and high-speed intercity buses poses a safety challenge for drivers, passengers, and pedestrians. Wheel nut loosening is a notable cause of service, fretting, and cracks in the mating components; contributing a significant chunk of warranty cost to the company. The need of the hour is to reinforce these joints while keeping resources at bay. This paper establishes a methodology for the evaluation and design of a safe wheel bolt joint interface including key parameters such as embedding, axial forces, and shear forces. It is necessary to obtain the minimum preload requirement for a wheel bolt joint to hold the clamped surfaces intact, which if not maintained otherwise would cause relative movement, play, shear load onto the bolt, and eventually failure.

The basic needs of people are met by the building, fabric, and farming sectors. In addition, the automobile industry significantly contributes to human mobility and is essential to India’s economic expansion. There are numerous research strategies available to improve the bus body building industries. Several investigative approaches for enhancing bus body building industries are available. However, several of these studies merely look at it from the perspective of shop floor activity. Accordingly, when it comes to the execution of process design approaches, there is little practical evidence for accepting Gemba kaizen’s attitude. Hence, the purpose of this article is to present a continuous improvement redesign framework tailored to a specific bus body building industrial sector. The proposed model is structured after a critical examination of Gemba and Kaizen.

Efficient transportation for carrying heavy loads is a common challenge across various applications, from supermarkets to industrial purposes. Conventional trolleys often fall short when loaded with heavy cargo, resulting in increased exertion and diminished productivity. Moreover, these challenges can adversely affect posture and lumbar spine health, especially for elder people and persons with cervical problems. There is a need for more user-friendly, ergonomic, and space-efficient solutions. This project addresses these challenges through an innovative design that encompasses various aspects of trolley functionality, including the study of comfort, wheel selection, and material considerations, drawing from ergonomic research. Multiple methods are employed to optimize the trolley’s dimensions to improve its overall performance. The trolley’s design features a collapsible basket for the transport of smaller-sized items and a base frame for larger goods and luggage.

Intelligent construction has become an important way to accelerate the transformation and upgrading of the construction industry and promote the high-quality development of the construction industry. As a national pilot city of intelligent construction, Shenyang needs effective policy system support for the development of intelligent construction. Quantitative research of policy text can provide a decision-making basis and path optimization suggestions for formulating and improving intelligent construction incentive policies (ICIP) in Shenyang. This study uses text mining and the Policy Modeling Consistency index (PMC index) model to construct an intelligent construction policy index system. Then it combines the PMC index and PMC surface to evaluate and analyze the text of ICIP in Shenyang quantitatively. The results show that there is still room for improvement in the ICIP in Shenyang.

Aluminum alloys are employed in agricultural equipment, aerospace sectors, medical instruments, machinery, automobiles, etc. due to their physical and mechanical characteristics. The geometrical shape and size of the parts are modified in turning operation by using a single-point cutting tool. A356 aluminum alloy is widely used in various engineering sectors, hence there is a necessity to produce A-356 components with quality. The inappropriate cutting parameters used in turning operation entail high production costs and reduce tool life. Box–Behnken design (BBD) based on response surface methodology (RSM) was used to design the experiments such that the experiment trials were conducted by varying cutting parameters like N-spindle speed (rpm), f-feed rate (mm/rev), and d-depth of cut (mm). The multi-objective responses, such as surface roughness (SR) and metal removal rate (MRR) were analyzed with the desirability method.

Tractor is primarily used for Haulage and agricultural applications due to this high tractive effort. A tractor usage has been increased in recent times for its wide range of implement applications. Considering environmental factors and sustainability, restrictions are set on the Tractor emissions. This brings new challenge in the Tractor industry to reduce the carbon footprint. Conventional casting process involves preparation of die & mold, material removal and machining in the final stage to get the desired final product. Alternatively Additive Manufacturing Process (AMP) helps in creation of lighter and stronger parts by adding material layer by layer. By saving the material, weight of the overall Tractor is reduced which helps in reducing carbon footprint. But the disadvantage of this process is the limited availability and high cost of AMP material and lack of infrastructure/skill set for operation handling.

With the rise of worldwide trends towards light weighting and the move towards electric vehicles, it is now more important than ever for the automotive industry to develop and implement lightweight materials that will result in significant weight reduction and product improvements. A great deal of research has been done on how to best combine and configure honeycomb cores with the right face sheets for Truck-Mounted Container Applications. Honeycomb structures possess the ability to bring about superior structural rigidity when the core parameters are selected and optimized based on the automotive application requirements.

India striving for carbon neutrality influences futures powertrain architecture of commercial vehicles. The use of CO2-free drives as battery electric have been demonstrated for various applications. The productivity still is a challenge due to missing high power charging infrastructure or limited range. This draws the attention to the use of sustainable fuels due to lower refueling times. The hydrogen engine got highest attention in the last couple of years. For markets as the EU the driver for hydrogen is the CO2 emission reduction, whereas for markets as India hydrogen offers the additional opportunity for more independence from fossil imports. Different OEMs all over the world have converted diesel engines to hydrogen operation with strong focus on performance and emission demonstration, so far with limited technology readiness of different key components.

Toe misalignment detection and its correction are important periodic tasks recommended by Original Equipment Manufacturers (OEMs) for Heavy Commercial Road Vehicles (HCRVs) to prevent premature tyre wear and improve fuel economy. Existing misalignment detection methods need skilled professionals to operate sophisticated equipment, while automated methods require additional sensors, which are not readily available in most trucks, making their implementation challenging. This study explores the effectiveness of a data-driven method to detect toe misalignment in single-unit twin-axle trucks with symmetric and asymmetric toe configurations. This method involves continuous monitoring of lateral dynamics variables measurable using sensors present in most trucks making it practically tractable.

Brazil has a robust agricultural sector; however, the mechanization of crops causes several problems in the physical soil structure, including surface compaction. Compaction reduces crop productivity and producer profits. The intensity of compaction varies depending on the wheelset model used, tire type, water content, and soil load applied. Recent studies have shown that soil compaction in sugarcane can be attenuated by maintaining the vegetation cover (straw biomass) on the surface after harvesting. The present study used different tire models to evaluate the interaction between wheelset-soil as a function of different amounts of biomass left over from the sugarcane harvest. A physical simulation system (fixed tire testing unit) was used for the tests. The wheelsets were subjected to controlled loads on tanks with confined and standardized soil samples.

The mechanization of crops causes problems in soil structure as it causes compaction. Compaction can be severe depending on the type of tire adopted in the field. Producers are concerned with selecting wheelsets that harm the soil less and remembering to save resources when buying agricultural tires. Agricultural tires are more expensive than road tires, and truck tires can be an alternative for producers to save money. The present study evaluated the interaction between wheelset and ground in a fixed tire testing unit, comparing the impact of different tire models on bare ground. The 6 treatments performed consisted of 3 tire models (p1: road radial, composed of double wheelset - 2×275/80r22.5; p2: agricultural radial - 600/50r22.5; and p3: agricultural diagonal - 600/50-22.5) versus two contact surfaces, one rigid and the other with bare agricultural soil. Seven response variables were used to apply Regression analysis and descriptive statistics.