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Increasing urbanisation and the growing environmental awareness in society require new and innovative vehicle concepts. In the present work, the design freedoms of additive manufacturing (AM) are used to develop a front axle wheel suspension for a novel modular vehicle concept. The development of the suspension components is based on a new method using industry standard load cases for the strength design of the components. To design the chassis components, first the available installation space is determined and a suitable configuration of the chassis components is defined. Furthermore, numerical methods are used to identify component geometries that are suitable for the force flow. The optimisation setup is selected in a way that allows to integrate information, energy and material-carrying conductors into the suspension arms. The conductors even serve as load-bearing structures because of the matching design of the components.

Despite being ubiquitous elements in aerospace structures, thin cylindrical shells’ catastrophic buckling response under axial compression has still remained an enigma. The recent advancements in theoretical and numerical studies aided in realising the role of localisation in shell buckling. However, the buckling being instantaneous made it unfeasible for the experimental observations to corroborate the numerical results. This necessitates high-fidelity shell buckling experiments using full-filed measurement techniques. Cut-outs are deliberate and inevitable geometrical imperfections in actual structures that could dictate the buckling response. Additive manufacturing makes it feasible to fabricate shells with tailored imperfections and study various conceivable designs.

The Selective Laser Melting (SLM) process is employed in high-precision layer-by-layer Additive Manufacturing (AM) on powder bed and aims to fabricate high-quality structural components. To gain a comprehensive understanding of the process and its optimization, both modeling and simulation in conjunction with extensive experimental studies along with laser calibration studies have been attempted. Multiscale and multi-physics-based simulations have the potential to bring out a new level of insight into the complex interaction of laser melting, solidification, and defect formation in the SLM parts. SLM process encompasses various physical phenomena during the formation of metal parts, starting with laser beam incidence and heat generation, heat transfer, melt/fluid flow, phase transition, and microstructure solidification. To effectively model this Multiphysics problem, it is imperative to consider different scales and compatible boundary conditions in the simulations.

Bio-composites have gained significant attention within the aerospace industry due to their potential as a sustainable solution that addresses the demand for lightweight materials with reduced environmental impact. These materials blend natural fibers sourced from renewable origins, such as plant-based fibers, with polymer matrices to fabricate composite materials that exhibit desirable mechanical properties and environmental friendliness. The aerospace sector's growing interest in bio-composites originates from those composites’ capacity to mitigate the industry's carbon footprint and decrease dependence on finite resources. This study aims to investigate the suitability of utilizing plant derived flax fabric/PLA (polylactic acid) matrix-based bio-composites in aerospace applications, as well as the recyclability potential of these composites in the circular manufacturing economy.

Thermo-mechanical fatigue and natural aging due to environmental conditions are difficult to simulate in an actual test with the advanced fiber-reinforced composites, where their fatigue and aging behavior is little understood. Predictive modeling of these processes is challenging. Thermal cyclic tests take a prohibitively long time, although the strain rate effect can be scaled well for accelerating the mechanical stress cycles. Glass fabric composites have important applications in aircraft and spacecraft structures including microwave transparent structures, impact-resistant parts of wing, fuselage deck and many other load bearing structures. Often additional additively manufactured features and coating on glass fabric composites are employed for thermal and anti-corrosion insulations. In this paper we employ a thermo-mechanical fatigue model based accelerated fatigue test and life prediction under hot to cold cycles.

Selective Laser Melting (SLM) has gained widespread usage in aviation, aerospace, and die manufacturing due to its exceptional capacity for producing intricate metal components of highly complex geometries. Nevertheless, the instability inherent in the SLM process frequently results in irregularities in the quality of the fabricated components. As a result, this hinders the continuous progress and wider acceptance of SLM technology. Addressing these challenges, in-process quality control strategies during SLM operations have emerged as effective remedies for mitigating the quality inconsistencies found in the final components. This study focuses on utilizing optical emission spectroscopy and IR thermography to continuously monitor and analyze the SLM process within the powder bed, with the aim of strengthening process control and minimizing defects.

Industries have been increasingly adopting AI based computer vision models for automated asset defect inspection. A challenging aspect within this domain is the inspection of composite assets consisting of multiple components, each of which is an object of interest for inspection, with its own structural variations, defect types and signatures. Training vision models for such an inspection process involves numerous challenges around data acquisition such as insufficient volume, inconsistent positioning, poor quality and imbalance owing to inadequate image samples of infrequently occurring defects. Approaches to augmenting the dataset through Standard Data Augmentation (SDA) methods (image transformations such as flipping, rotation, contrast adjustment, etc.) have had limited success. When dealing with images of such composite assets, it is challenging to correct the data imbalance at the component level using image transformations as they apply to all the components within an image.

Lunar tubes, natural underground structures on the Moon formed by ancient volcanic activity, offer natural protection from extreme temperatures, radiation, and micro-meteorite impacts, making them prime candidates for future lunar bases. However, the exploration of lunar tubes requires a high degree of mobility. Given the Moon's gravity, which is approximately six times weaker than Earth's, efficient navigation across rugged terrains within these lava tubes is achievable through jumping. In this work, we present the design of subsystems for a miniature hexapod rover weighing 1 kg, which can walk, jump, and stow. The walking system consists of two subsystems: one for in-plane walking, employing four single-degree-of-freedom (DOF) legs utilizing the KLANN walking mechanism, and another for directional adjustments before jumping. The latter employs a novel three-DOF mechanism employing a cable pulley mechanism to optimize space utilization.

In this paper, experimental studies were conducted to examine the mechanical behavior of a polymer composite material called polyamide with glass fiber (PA6-GF), which was fabricated using the three-dimensional (3D) fusion deposition modeling (FDM) technique. FDM is one of the most well-liked low-cost 3D printing techniques for facilitating the adhesion and hot melting of thermoplastic materials. PA6 exhibits an exceptionally significant overall performance in the families of engineering thermoplastic polymer materials. By using twin-screw extrusion, a PA6-GF mixed particles made of PA6 and 20% glass fiber was produced as filament. Based on literature review, the samples have been fabricated for tensile, hardness, and flexural with different layer thickness of 0.08 mm, 0.16 mm, and 0.24 mm, respectively. The composite PA6-GF behavior is characterized through an experimental test employing a variety of test samples made in the x and z axes.

The rotor and stator of electric motors consist of multiple materials, of which steel forms the majority of mass and volume. Steel in electric motors is commonly in the form of thin sheets (laminations), stacked along the axis of the rotor. The structural integrity of such a stack can be ensured using bolting, welding or bonding of the laminations. Predictive mechanical finite element simulations of these laminated stacks can become computationally intense because the steel sheets are thin, and the motor often contains hundreds of them. If the laminations are modelled individually, the size of the elements is very small compared to the overall dimensions and the interface between the laminations need to be modelled as well. In this paper, we present an alternate method of modelling this laminated stack as a single solid body using homogeneous and orthotropic material property, instead of representing each lamination.

Lithium-ion batteries are ubiquitous in modern energy storage applications, necessitating efficient methods for assessing their state and performance. This study explores a non-destructive approach to extract vital battery parameters using machine learning techniques applied to simulated Electrochemical Impedance Spectroscopy (EIS) data. EIS is a powerful diagnostic tool for batteries and provides a safe and repeatable alternative to the physical intrusion of battery dismantling, which could alter the batteries properties. The research focuses on the design and training of machine learning models for accurate prediction of battery parameters within the widely used P2D model. By leveraging the power of machine learning, this approach aims to accurately characterize the battery parameters using an electrochemical model as opposed to the less accurate equivalent circuit models, contributing to the reliability and longevity of lithium-ion batteries in diverse applications.

The design and testing of innovative components and control logics for future vehicular platform represents a challenging task in the automotive field. The use of scale model vehicles constitutes an interesting alternative for testing assessment by decreasing time and cost efforts with a potential benefit in terms of safety. The target of this research work is the development of a customized scale vehicle platform for verifying and validating innovative control strategies in safe conditions and with cost reduction. Consequently, the electrification of a radio-controlled 1:5 scale vehicle is carried out and a customized remote real-time controller is installed onboard. One of the main features of this commercial product is its modular characteristics that allows the modification of some component properties, such as the viscous coefficient of the shock absorbers, the stiffness of the springs and the suspension geometry.

The requirement for lightweight, high-performance materials with higher wear resistance, which is critical in industries such as aerospace, automotive, and consumer-related sectors, has fueled the development of particle reinforced metal matrix composites (PRMCs). These materials are an appealing alternative for a broad variety of scientific and technological applications due to their remarkable mechanical qualities and low cost. The primary goal of developing metal matrix composite materials is to combine the favorable properties of metals and ceramics. This study included several experimental experiments to explore the behavior of stir-cast composites made of aluminum grade 6063 with varying amounts of SiC, Al2O3, and TiO2 reinforcements.

Laser powder bed fusion is one of the metal additive manufacturing technologies, so-called 3D printing. It has attracted great attentions due to high geometrical flexibility and remarkable metallurgical characteristics. An oil catch tank has been widely used in automotive industries for filtering oil vapors or carbon sludge from blow-by gas as a conventional usage. A pneumatic valve system mainly adopted to high-performance engines is also a potential application of it because undesirable oil infiltrates into air springs during engine operation, resulting in an excess spring pressure. This work focused on developing a lightweight oil catch tank which can be applied to a pneumatic valve system by taking advantage of additive manufacturing techniques. Al-Mg-Sc alloy powder with high tensile strength as well as high ductility were used under the consideration of specific strength, printability and availability.

The rapidly growing amount of software in cars reshapes the automotive industry. The software has a significant influence on the production lines, due to the time required to flash it onto the vehicle and its capabilities to test vehicle functions during production. In this paper we identify the main pain points regarding software in the manufacturing process by performing a structured analysis on the experiences made at a major car manufacturer over last two years. Consequently, the paper analyses the possible approaches to address the challenges.

Over the last decade, Climate change due to fossil fuel burning has taken centre stage in all discussions. Automotive sector has come under some flak for being one of the contributors to this Climate Change. Active steps have been taken by Vehicle Manufacturers and their Suppliers to address this issue. This sector has been facing below challenges to reduce pollutant in the air by A. Reducing Emissions, B. Increasing Energy Efficiency C. Use of Renewable Energy. One of the many alternatives by the Automotive Industry was to have a phased introduction to Electric Vehicles (EV), Hybrids, Fuel cells and other variants. As various emission norms and safety requirements takes Centre stage, it invariably, increases the weight of the vehicle. Now a days, Vehicles are having challenges to make it lightweight to achieve Range for an EV and improve fuel efficiency without sacrificing safety.

Historically manufacturing variability has been considered as a noise factor due to limited insights about manufacturing history and its influence on part performance. With improvement in computational power and enhancements in commercial simulation tools, it is now feasible to study the influence of manufacturing process on product life in addition to manufacturability. This study demonstrates the concept of as manufactured part performance prediction utilizing forming simulation software to capture deformed geometry along with residual stresses and its integration to performance simulation tool using sheet drawing operation. Simulation predictions are verified and validated with available experimental data. This approach helps to visualize the variation in part performance with respect to manufacturing process change including process sequence, process parameters and tooling design change.

The present work focusses on development of AlSi10Mg alloy component from the pre-alloyed powder by laser powder bed fusion (LPBF), one of the popular additive manufacturing technologies. The effect of heat treatment on microstructure and mechanical properties has also been studied. In accordance with T6 heat treatment process, the LPBF specimens were solution treated at 535°C for 2 h, then water quenched and subsequently, artificially aged at 160°C for 10 h. The role of printing direction on microstructure and mechanical properties has also been investigated. The printing parameters such as laser power, scan speed and hatch space were optimized for defect free automotive component. The as-printed and heat treated components were subsequently evaluated to assess their performance.

The usage of forging a preformed, near net shape, compacted and sintered metal powder has been widely accepted since the eighties and is now one of the mainstays for producing Connecting rods in North America. However, its use in Indian subcontinent is limited as its counterpart i.e. conventional steel forging is still the most dominant. Powder metallurgy route has many advantages like good dimensional accuracy; minimum scattering of weight etc. Despite these advantages, the Powder metallurgy process is still not preferred predominantly due to technical (endurance) and infrastructural limitations. This work envisages combining the benefits of powder metallurgy process with the required mechanical properties viz. tensile and fatigue strength alongside design modifications to meet the requirements of a connecting rod for a 2-cylinder diesel engine. The connecting rods met the fatigue life at the required FOS equaling the performance of a conventionally forged connecting rod.

Helmholtz resonator is a very common anechoic measure, and it is widely used in pipe acoustic fields. Based on the enlightenment of the classic Helmholtz resonator, this paper proposes a headrest resonator model and extends it to the acoustic field of the passenger cabin to improve the road noise in the car. Firstly, through the theoretical model of Helmholtz resonator, the relationship between its resonance frequency and the geometric size of the resonator is clarified. Secondly, the influence of the headrest resonator on the acoustic field characteristics of the car is studied through finite element simulation analysis. It is demonstrated that the headrest resonator is placed in the car, and the sound pressure distribution characteristics of the passenger's inner ear near the resonance frequency change significantly. At the same time, through 3D printing, a sample of the headrest resonator is made.