International Journal of Vehicle Structures and Systems
International Journal of Vehicle Structures and Systems (IJVSS) is a bi-monthly journal and is published by MechAero Foundation for Technical Research & Education Excellence (MAFTREE), Chennai, India from 2009 to 2022. Since January 2023, the publication has been fulfilled by Carbon Magics Ltd, UK. IJVSS will endeavour to publish high quality original research and review papers, case studies, technical notes and book reviews. All published papers in this journal will have undergone rigorous peer review.
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Impact of Graphene Nanoparticles Fillers Addition on Flexural Behavior of Single Lap Bonded Joints
The aim of this work was to evaluate the flexural strength of Single Lap Joints (SLJs) produced by using carbon and glass fibres as adherend, while reinforcing the adhesive with Graphene. The adhesive was reinforced with Graphene nanoparticles (GNP) filler at different concentrations by wt. as 0%, 0.25% and 0.5%. SLJs were prepared using 12.5mm and 25mm bond lengths. Then, SLJs were subjected to a series of three-point bending tests. The incorporation of GNP into the adhesive employed for the fabrication of SLJs has yielded a significant improvement in the flexural strength of said joints, irrespective of the exact weight proportion of GNP. The greatest flexural strength was observed at a concentration of 0.5% wt. of GNP for both carbon and glass adherend composites.
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Preliminary Design and Numerical Simulation of 2D Ramjet Engine
This study examines the design and flow modelling of the ramjet Engine at efficient Mach values, focusing on its theoretical and mathematical foundations. This work presents a comprehensive investigation of ramjet engines, aiming to clarify their fundamental operating principles, examine design standards and performance optimisation methods, delve into Computational Fluid Dynamics (CFD) methods for internal process modelling, and identify current design obstacles. The outcome presents an optimal ramjet engine design, exhibiting efficiency at supersonic speeds between Mach 2.8 and 3.3. The subsonic speed at the combustion chamber is created by generating shock waves with the use of an inlet cone, with a cone angle of 35. The Mach number at the nozzle was increased by using dual bell nozzles.
Design and Analysis of Telescopic Morphing Wing for Loitering Munition Drones
Loitering munition drones (LMDs), with their ability to perform surveillance, reconnaissance and targeted strikes, have garnered significant attention in modern military operations. One key challenge in their design is achieving versatility in flight performance while maintaining a compact form factor. This paper presents a novel approach to address this challenge through the integration of a telescopic morphing mechanism into the design of LMDs. The proposed telescopic morphing mechanism enables the drone to dynamically adjust its wing span and shape during the flight. We discuss the design principles, kinematics and control strategies of the telescopic morphing mechanism, emphasising its ability to enhance the drone's agility, endurance and stealth capabilities. Furthermore, we present experimental results and simulations demonstrating the effectiveness of the proposed mechanism in improving the overall performance and mission success rates of loitering munition drones.
Biocomposite: A Promising Sustainable Alternative for Aerospace Structural Applications
The growing commitment to environmentally friendly practices, commonly referred to as "Go Green," is increasingly shaping contemporary society. This movement towards sustainability is evident in diverse sectors, including aviation, which showcases a remarkable opportunity for research and innovation. A significant focal point within this field is the use of biocomposite materials derived from renewable natural sources, which offer a promising alternative to conventional composite materials that typically include a mix of metallic and non-metallic elements such as carbon and glass fibers. Biocomposites possess biodegradable fibers from hemp and wool, often combined with eco-friendly epoxy. This paper critically examines the potential integration of biocomposites into aircraft manufacturing, identifying specific components that may be replaced or enhanced with these sustainable materials. Furthermore, it evaluates various biomaterial combinations explored by researchers to pinpoint the most viable options for advancing sustainability in the aviation industry.
Advancing Battery Pack Technology through Enhanced Battery Management System Design and Analysis
Fast advancements in battery technology require sophisticated Battery Management Systems (BMS) in order to ensure security, extend lifespan and optimise efficiency. The development and implementation of a BMS intended especially for new battery spacers is the main topic of this study. These spacers, which are essential for improving battery system structural stability, temperature control and electrolyte distribution, are made of materials that implicitly optimise thermal management. By stabilising the interior temperature of battery packs in Electric Vehicles (EVs), these advances seek to preserve performance and safety in a variety of operating environments. The suggested BMS precisely monitors and maintains vital parameters like voltage, temperature and charge level by utilising cutting-edge sensing technologies, sophisticated control algorithms and dependable communication protocols. Through comprehensive design optimisation, simulation and problem-solving in temperature regulation and fault detection. This work aims to significantly boost the efficiency and security of batteries fitted with these novel spacers. The findings have the potential to drastically change preconceived notions about battery management, hastening the transition to sustainable energy practices by allowing a greater adoption of safer, more efficient energy storage technologies in critical sectors such as renewable energy and EVs.
Response Surface Methodology based Optimisation of Performance, Exhaust Emissions and Vibrations of a PFI SI Engine Operated in Dual Fuel Mode with E20 and GEM Blends
The current study was carried out on dual-fuel diesel engines for optimising the performance, emission and vibration parameters with the help of response surface methodology. The engine was operated at 1800, 2200, 2600, 3000 and 3400 rpm by keeping the load 5 kg, with a combination of pure petrol, E20 and hydrogen at 3, 9, and 15 Lpm. Engine speed, various hydrogen flow rates and fuel blends are considered as input responses and brake thermal efficiency (BTE), brake-specific fuel consumption (BSFC), Nitrogen Oxides (NOx) emissions and vibrations are used as output responses. Optimisation of the engine was done by considering that BTE has to be in maximum condition and BSFC, NOx and vibrations to be in minimum condition. BTE and BSFC are high at 1832rpm speed with 15 Lpm hydrogen flow at blend 3, i.e., Gasoline-Ethanol-Methanol (GEM) blend. At 1832 rpm and a hydrogen flow of 15 Lpm with the GEM blend, the levels of NOx and vibrations were measured. E20 showed a rise of 12.35%, 8.69%, 22.22%, 12.76% and GEM blend showed a rise of 14.96%, 13.04%, 27.40% and 17.41% in BTE, BSFC, NOx and vibrations when compared to petrol at 15 Lpm hydrogen.
Design and Optimisation of Battery Thermal Management Systems in Electric Vehicles using Advanced Simulation Techniques
Efficient thermal management is essential for improving the safety, durability and performance of Electric Vehicle (EV) batteries. Even small temperature deviations can drastically affect battery life; for instance, a rise of just 1-2°C has been shown to accelerate cell degradation, making optimised cooling systems indispensable. This study investigates four fin configurations - no fins, rectangular, elliptical and irregular fins to identify the most effective solution for heat dissipation in EV battery chambers. Using CATIA for design and ANSYS coupled with CFD for simulation, each configuration was evaluated for temperature control, heat flux, airflow behaviour and turbulence characteristics. The results reveal meaningful differences in performance. The irregular fin design, for example, achieved the lowest battery temperature of 46.77°C, a noticeable improvement compared to 46.889°C without fins, illustrating how even fractional changes can significantly stabilise battery operation during continuous vehicle use. It also produced the highest total heat flux (0.82196 W/m²), indicating stronger overall heat removal capacity. Conversely, the elliptical fins delivered the highest directional heat flux (0.095758 W/m²) and the lowest eddy viscosity (7.185), resulting in smoother airflow and reduced energy losses - an advantage in systems where airflow efficiency is a priority. By combining thermal and flow metrics, this study highlights that while irregular fins maximise raw cooling performance, elliptical fins offer a balanced and energy-efficient alternative. These insights provide a practical pathway for designing next-generation battery thermal management systems that are both thermally robust and aerodynamically optimised.
Mechanical and Thermal Cycling Behaviour of NiTi and Cu Wire Reinforced E-Glass Epoxy Composites
The four different categories of composites have been fabricated namely pure e-glass reinforced epoxy composite (PEC), nickel-titanium wire reinforced composite (NTEC), copper wire reinforced composite (CEC) and hybrid NiTi-Cu wire reinforced composite (NTCEC) using hand lay-up method in this work. The NiTi and Cu wires were aligned longitudinally in NTEC and CEC, while in NTCEC they were interlaced in a grid pattern to improve stress transfer and crack resistance. Mechanical characterization was carried out through tensile, flexural and impact testing, along with thermal cycling to evaluate strength, stiffness and toughness under varying temperature conditions. The results from all composites were systematically compared to assess the influence of metallic reinforcement. Scanning electron microscopy (SEM) was employed to examine fracture surfaces and identify microstructural defects. Overall, the study highlights the enhanced mechanical reliability and thermal endurance of NTCEC, indicating its potential for aerospace and automotive applications that demand smart structural systems with resistance to repetitive thermal loading.
Strength Calculation and Durability Assessment of the Cardan Shaft Assembly in the Transmission System of Light Trucks
This paper focuses on the computational analysis and durability assessment of the drive shaft assembly in the power transmission system of a light-duty truck. A realistic 3D model is employed to determine critical geometric parameters, including the Shaft Length (L) and Shaft Wall Thickness (b), which significantly influence the durability. Six specific cases are analysed with the following parameters: (1) L1=1450 mm, b1=6 mm; (2) L1=1450 mm, b2=4 mm; (3) L2=1300 mm, b1=6 mm; (4) L2=1300 mm, b2=4 mm, (5) L3=1150 mm, b1=6 mm and (6) L3=1150 mm, b2 = 4 mm. Finite Element Method (FEM) is applied, in combination with Ansys Workbench software, to simulate and evaluate the strength and natural vibration modes, including bending and torsional vibrations of the shaft assembly. The results reveal that the durability of the drive shaft is strongly dependent on both length and wall thickness. These parameters significantly affect stress and deformation, providing a scientific basis for design optimisation. Simulation outcomes indicate that adjusting shaft length and wall thickness can effectively reduce the stress and deformation, enhance durability and simultaneously optimise the material usage and production costs.
Air-Breathing Hypersonic Vehicles: Review, Developments & Future Challenges
The hypersonic Flight has drawn international attention in the past few decades resulting in worldwide developments in hypersonic technology for civil and military applications and providing cost-effective and reliable hypersonic flight. This paper presents the recent advancement of different models of air-breathing hypersonic vehicles (AHV) during the last six decades to the present date used for the modelling, simulation and flight test. It highlights their challenges, research progress and their future developments. It also pronounces the theoretical and experimental nonlinear flight dynamic models used for the hypersonic technology development over the years and discusses the aspects of flight control design. The future and the ongoing developments of the hypersonic vehicle models by different nations worldwide are also presented. The bifurcation method with the continuation approach is presented here, which outlines the topological behaviour of the nonlinear dynamic model of AHVs and provides a fruitful analysis of the equilibrium states for the entire wide flight regimes of AHV flight. Bifurcation method shows a promising application to the effective analysis of nonlinear phenomena occurring in flight dynamics, global stability and improvements in control design parameters and flight controls.
Practical Exploration of Empowering Intelligent Pressure Regulation and Explosion-Proof Systems for Vehicle Tires based on Piezoelectric Technology
This paper presents an in-depth exploration of the intelligent pressure regulation and explosion-proof system for vehicle tires based on piezoelectric technology. It thoroughly analyses the system's structural composition, operational mechanism and technical characteristics and evaluates its effectiveness through experimental verification. The research shows that, relying on the unique advantages of piezoelectric technology, the system achieves accurate and intelligent control of tire pressure, possesses excellent explosion-proof performance and significantly enhances the safety of vehicle operation. This not only injects impetus into the innovation of the automotive safety technology field but also lays a solid foundation and provides direction for subsequent similar studies.
Valorisation of Municipal Waste Plastics into Fuel-Grade Oil: A Characterisation Study with Environmental Implications
Globally, waste management is being extensively studied and developed to achieve long-term environmental sustainability. The waste plastic for this research study was collected from the municipal solid waste streams. In this research study a detailed characterisation is presented for waste plastic oil (WPO) using Fourier Transform Infrared Spectroscopy (FTIR), Thermogravimetric-Differential Scanning Calorimetry (TG-DSC) and Gas Chromatography-Mass Spectrometry (GC-MS) to evaluate its chemical and thermal properties. FTIR analysis confirmed the presence of aliphatic hydrocarbons, carbonyl compounds and minor hydroxyl or amine groups, indicating that the oil primarily consists of long-chain hydrocarbons formed through polymer degradation with traces of oxidation. The distinct C-H stretching and bending vibrations verify its similarity to paraffinic and olefinic hydrocarbon structures typical of fuel-like materials. TG-DSC analysis revealed a major endothermic transition at approximately 294.1°C with an enthalpy of 17.9 J/g, signifying the decomposition or melting of higher molecular weight components and the progressive volatilisation of heavier fractions. GC-MS results further demonstrated the presence of a broad range of hydrocarbon compounds, from short-chain volatiles to heavier fractions, with a dominant mid-range peak around 22 minutes corresponding to diesel-range constituents. The analytical results indicate that WPO has potential as an alternative liquid fuel.
Process Optimisation and Characterisation of Karanja - Neem Biodiesel derived using Egg Shell-CuO-Nano-Bio Catalyst through Base Catalysed Transesterification Technique
The present investigation aims at deriving bio oil from the seeds of Karanja / Neem through the mechanical expulsion method. The extracted bio-oil was subjected to two stage transesterification process with methanol and Egg Shell/CuO-NaOH Nano biocatalyst. The Egg Shell/CuO-NaOH Nano biocatalyst was prepared by deposition precipitation method with aqueous solution of copper nitrate through ultrasonication and calcination technique at 375°C. The transesterification process was optimised considering the influential operating parameters like Molar ratio, Egg Shell/CuO-NaOH catalyst, Agitation speed and reaction temperature. The CCRD design in RSM technique developed a 30 Run model to predict the optimal yield of Karanja and Neem biodiesel. 1:9, 450 rpm, 1.5 w/w Egg Shell/CuO-NaOH Nano catalyst and 90°C of molar ratio, agitation speed, catalyst concentration and reaction temperature respectively predicted 97.21% and 95.11% of Karanja / Neem biodiesel respectively. The derived biodiesel was subjected to FTIR and GCMS spectral studies to standardise its characteristics and to identify the compounds and various functional groups. The physicochemical properties were also determined using ASTM methods and were within limits. The findings of the present investigation also support the usage of preparing hybrid blends with Karanja and Neem biodiesel with diesel as fuel in a diesel engine.
Fabrication and Performance Evaluation of Quartz-Reinforced AA6063 Aluminium Composites via Friction Stir Processing
Friction Stir Processing (FSP) has evolved as a promising solid-state approach for producing Aluminium Matrix Composites (AMCs), offering a distinct advantage over liquid metallurgy by preventing casting-related defects. In this study, Quartz (SiO₂) particulates were incorporated into AA6063 alloy through a controlled single-pass FSP route to develop particle-reinforced composites. Before processing, longitudinal grooves were machined on the alloy substrate and filled with quartz powder. The reinforcement content was systematically varied from 0 to 18 vol. % in increments of 6 vol. % to assess its influence on the resulting properties. Microstructural characterisation of optical microscopy, SEM and TEM confirmed an excellent dispersion of quartz particles throughout the processed zone. Significant grain refinement was observed in the matrix, attributed to the combined effects of severe plastic deformation and particle-induced boundary pinning. The refined microstructure, coupled with effective particle-matrix interaction, led to notable improvement in micro hardness and wear performance. Moreover, the study offers knowledge regarding the role of quartz content on worn surface features and wear debris formation, demonstrating that increasing particulate addition enhances the overall mechanical and tribological response of the AA6063 alloy.
Numerical Simulation of 2D Wedge to Determine Pitching Moment Derivative and Shock Behaviour at Hypersonic Mach Numbers
Creating a numerical model for the 2D wedge flow field is the aim of this study. Wedge shapes are frequently used in defensive applications as stabilising surfaces for hypersonic projectiles like rockets, missiles and aircraft. Delta or wedge-shaped wings are frequently employed as the main wing on hypersonic aircraft and weapons to maintain stability. Examining the static pressure, derivative of the pitching moment at different wedge pivot points and shock behaviour for the nose of a wedge-shaped plane or missile at various Mach numbers and incidence angles in the hypersonic zone is the primary objective of the current study. A detailed investigation was conducted on the numerical simulation findings. The fluctuation of the pitching moment derivative is influenced by the Mach number, angle of attack (α) and wedge angle (θ), as demonstrated by the application of computational fluid dynamics (CFD) analysis to estimate the pitching moment derivative (Cmq). Similarly, CFD analysis is used to quantify static pressure, showing that the Mach number influences the (Cmq) variation (α) and (θ). Static pressure increases with increasing Mach number (α) and (θ). Moreover, at hypersonic Mach numbers, the shock angle decreases as the Mach number increases. The vehicle accelerates at a Mach number of 15.5, reaching hypersonic Mach because the shock is at the surface and moves away from the nose as the Mach number rises.
Effect of MWCNTs on Fatigue Life of Woven Glass Fiber Reinforced Polymers
Tension-tension fatigue performance of GFRP woven laminates of orientation (0/90)12 has been examined with inclusion of MWCNTs at 0.5 wt. %. Fatigue tests were executed for neat and MWCNTs modified GFRP at three stress levels for 75%, 65% and 55% of ultimate tensile strength under stress ratio, R=0.1 and R=0.3. Fatigue behaviour was evaluated based on S-N curves, FSC and FSE. Under constant amplitude cyclic loading, fatigue life of nanotubes modified GFRP specimens remained higher when compared to neat GFRP specimens at all stress levels. Furthermore, it is found that the fatigue life of neat and modified GFRP were reliant on stress level and stress ratio. In addition, analytical models have been employed to predict fatigue life, demonstrating consistency with experimental fatigue life. Moreover, design life has been evaluated at several dependability levels by the application of the Weibull distribution.
Enhancing EDM Performance: Optimisation of SS316L Electrodes Via Direct Metal Laser Sintering
EDM, employed as one of the methods in processing, involves the utilisation of a series of sparks to erode material from the workpiece, thus achieving the desired form. This method is particularly useful for processing hard metals. The manufacture of EDM electrodes, concluded SLS, as a distinct method from conservative dispensation techniques, has been facilitated by the work done by several researchers. Investigational investigation is conducted by SLS hap-penning electrodes finished from materials such as nickel alloy, brass, copper alloy (including bronze and nickel) and alloy steel, for the fragmentation of compact substances. In the assessment of EDM presentation, metrics such as substantial deposition rate (Vw) and wear rate (θ) are considered. Vw, indicating the volume of material extracted from the section per unit of time, is typically measured in cubic meters per second. θ, demonstrating the affiliation between the amount of electrode wear and the proportion of substantial withdrawal, is also evaluated. Comparative studies are undertaken between electrodes produced via SLS and those manufactured using conventional methods, particularly concerning materials such as SS316L. Through these studies, the efficacy and efficiency of SLS-produced electrodes in EDM processes are assessed in comparison to traditional electrode manufacturing methods. The ad-ancients in EDM technology and the optimisation of manufacturing processes for various applications are thus facilitated by such investigations.
Artificial Intelligence Algorithms for Prediction of Tensile Strength for Process Parameter Variations in Friction Stir Welded Al7075 and Al 6063 Joints
The most important breakthroughs in contemporary computer science can be traced to the interaction between machine learning and the optimisation process. Mechanical automobile industries rely heavily on optimisation because of the savings it brings in terms of manpower, time, and production. In recent studies, researchers have sought to maximise the Ultimate Tensile Strength (UTS) of the aluminium dissimilar welded joints, which are mostly used in vehicles, by optimising the friction stir welding process. The XGBoost method and the Decision Trees regression model are two of the machine learning techniques used for this task. The UTS is the output variable, whereas the input variables are the Rotational Speed (rpm), Weld Speed (mm/min), and Tool Profile (Cylindrical, Hexagonal and Taper). Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) are found to be 6.77, 2.281 and 2.934 respectively for testing sets when using the XGBoost method. The MSE, RMSE, and MAE for Testing Sets with Decision Trees regression model, are 10.767, 3.281, and 3.255 respectively. We can therefore conclude that XGBoost is more effective and yields more reliable results than the Decision Tree approach
Microstructural and Corrosion Analysis of SS304L and ER308L Bimetallic Structure Prepared by Hybrid Manufacturing Process
Surfaces created with bimetallic additives take the place of conventional surfaces. In this work, a Bimetallic Additively-Manufactured Structures (BAMS) is created by fusing wire arc additive manufacturing (WAAM) with metal forming technology. SS304L hot forged piece was used as the hybrid manufactured technology base and ER308L was used for deposition using MIG based WAAM technology with pulse and spray modes. In order to achieve successful outcomes, this hybrid manufacturing technology was ultimately examined using SEM, EDS, XRD and corrosion analysis at various zones of the manufactured BAMS, and found they have acceptable level of microstructural characteristics..
Exploring Multi-Modal Trust based Security Mechanisms for Autonomous Vehicles
This research focuses on improving the security of autonomous vehicles (AVs) via trust-based approaches involving many operation modes. Given the swift progress of AV technology, it is crucial to implement strong security measures to protect passengers and infrastructure from possible threats. This work is unique because it introduces and investigates trust mechanisms that use many modes of information, including sensor data, communication signals and historical behavior patterns. These mechanisms evaluate the dependability of AV operations and identify any malicious behaviors. The proposed approach is proven effective through extensive experimentation, demonstrating improved capabilities in detecting threats and increased resilience against cyber-attacks. The experimental results highlight the effectiveness of trust-based security solutions that utilize several modes of operation to enhance the safety and reliability of autonomous driving systems. This, in turn, promotes the wider acceptance and use of AV technology.
Friction Stir Welding Process Parameter Optimization for AZ31 and AZ91 Magnesium Alloy Material using Design of Experiments and Taguchi Approach
As a welding process is key aspect for any fabrication work; which joint dissimilar or similar material with or without application of pressure as per necessity. In a welding process base metal turns to a plasticized form which lead to joining of metals. Friction Stir Welding (FSW) is a one type of welding process mostly employ by an industry with a application of weld tool and desired pressure. In this research article, two alloys of magnesium, AZ31 and AZ91 are used as base material and by adopting FSW method to obtain process parameter with the help of optimization tool. Different mechanical properties like ultimate tensile strength, percentage of elongation along with microstructure behavior of welded specimen are observed to comment on best possible process parameter for magnesium alloy. In this research work base material are prepared from the sheet of 5000 series magnesium alloy with 150 mm in length, 50 mm in width and 5 mm in thickness dimension prior to perform the welding process. Using the Design of Experiment (DOE) and Taguchi approach as an optimization tool along with the universal testing machine for the evaluation of different process parameter of welded structure.
Comparative Analysis of Non-Cryogenated and Cryogenated Goat and Human Hair Fiber Reinforced Hybrid Composites
Composites, owing to their light weight, are considered favourable materials in the field of material engineering. Utilisation of natural fiber is very important for maintaining the sustainability of the ecosystem. Goat and human hair is available in plenty and are dumped as waste. The ultimate goal of the research is to fabricate a hybrid composite out of goat and human hair. In order to further improve the properties, the fabricated composites are cryogenically treated. Then the specimens were tested as per ASTM standards to find the mechanical and thermal properties. The morphology of the specimens was also analysed using Scanning Electron Microscopy (SEM). The influence of cryogenic treatment is studied by carrying out a comparative analysis for seven proportions of goat-human hair hybrid composites of cryogenically treated and non-treated, along with pure epoxy specimens. To find the variation in the standard deviation between the non-treated and cryogenic-treated composites, the t-test and p-test were performed using the Python programming language and the respective standard deviation graphs were plotted. This type of plot is useful for comparing the distribution of data between two categories and identifying the central tendency, spread and potential outliers in the datasets. The tensile strength results of the standard deviation revealed that the tensile strength value of C3 composite with 40% goat hair and human hair lies outside 1.5 times the mean of the remaining values obtained for other proportions. This specimen performed well in all properties in comparison to all other specimens.
PID and ANN-based Control of Passive and Semi-Active Suspension System using Different Training Algorithms
The study considers Proportional-Integral-Derivative (PID) and Artificial Neural Network (ANN) approaches to control quarter-car passive and semi-active suspensions. The mathematical models have been derived and simulated in MATLAB Simulink. The models were initially controlled using a PID controller, and the results were used to train the ANN model. The conclusions highlight a better response of ANN controller compared to the PID controller. ANN training was performed using the Levenberg-Marquardt (LM), Bayesian Regularisation (BR) and Scaled Conjugate Gradient (SCG) algorithms. The responses of the ANN controllers were compared in terms of settling time and overshoot. The fallouts confirmed better outcomes of ANN controller trained through the BR-algorithm compared to other training algorithms.
Percussion-based Health Monitoring of Bolted Lap Joints
Bolted joints are critical to guaranteeing structural safety and performance, yet traditional monitoring methods tend to be expensive and intrusive. In practice, pretensioned bolts inevitably suffer from preload loss, making the reliable detection of loosening essential. This study introduces a Structural Health Monitoring (SHM) approach based on vibration and percussion, utilising audio-emission signals generated under controlled impact. A single bolted lap joint was tested, with the resulting audio and vibration responses recorded and analysed in both the time and frequency domains to assess bolt tightness. The impact range is kept between 300-325 N for tightness levels of 2 Nm, 10 Nm and 20 Nm, considered as loose, semi-tight and tight, respectively. The features such as signal energy, peak to RMS ratio and kurtosis from loose to tight conditions vary by 60%, 34% and 67%, respectively for vibration signals and 62%, 62%, 38% and 52% for sound signals. Utilising the Fast Fourier Transform (FFT) for analysis, a correlation was identified between bolt tightening levels and frequency amplitudes. Both signal types exhibited a slight increase in frequency corresponding to an increase in bolt torque. Sensor fusion is found to be an effective method for validating results and can enhance SHM of bolted connections in automotive, aerospace and aircraft structures.
Optimisation of Cold Plate Design Technology for Blade Battery Management of New Energy Vehicles
Blade batteries are widely used in new energy vehicles and the long strip structure helps improve the energy density of the system. Under high-rate operation and fast charging conditions, the heat accumulation on the surface and inside of the battery cell is easier to concentrate and the temperature gradient is enlarged, which affects the cycle life and increases the trigger probability of thermal runaway. To improve the heat dissipation capacity and temperature uniformity, three types of cold plate models with different flow channel structures, namely single straight channel, double serpentine channel and microchannel structure, are constructed in this study and the comparative analysis is carried out by combining experimental data with 3D thermal fluid-solid coupling simulation. The experimental samples were discharged at the inlet liquid temperature of 30 ℃ and the flow rate of 3.0-4.5 L/min and the data of multi-point temperature change on the surface of the battery cell were collected. The temperature error of the simulation model is controlled within 1.2 ℃ and the pressure drop error is controlled within 8 %, which verifies the reliability of the model. The results show that the microchannel structure has outstanding heat dissipation performance and the maximum temperature can be maintained at about 43 ℃, the maximum temperature difference (ΔT) can be controlled below 5 ℃ and the Temperature Uniformity Index (TUI) is raised to 0.89, which slows down the attenuation difference between cells and improves the thermal safety margin. The double serpentine channel balances the heat transfer capacity and flow resistance and its comprehensive performance is suitable for the platform power system in the middle power range. The single straight channel cold plate has advantages in pressure drop (ΔP) and system energy consumption and the temperature accumulation are more obvious under high heat flow conditions, which is suitable for low load scenarios. Combined with the life mechanism and vehicle thermal management framework, the cold plate structure selection and parameter classification application strategy are put forward, which can provide structural design reference for different types of new energy vehicle platforms. It is said that the Optimisation of cold plate structure affects the transient temperature control effect and has a long-term impact on the battery cycle decay rate, safety margin and system energy consumption level, which has engineering popularisation value.
Real-Time Obstacle Detection Algorithm based on Visual Perception in Unmanned Vehicles
This study addresses the issue of identifying obstacles in real time for unmanned automobiles using visual perception, which is a crucial component for ensuring the safety of autonomous driving. Existing detection methods are often limited in accuracy and robustness under diverse lighting and weather conditions. The purpose of this project is to create a new model that enhances detection precision, adaptability and immediate efficiency over a wide range of traffic circumstances. By making use of the KITTI dataset, which is divided into the training, validation and test sets in a ratio of 7:2:1, the performance of the proposed model is evaluated on the basis of detection efficiency, recall rate and average precision. These results are then compared to the results of YOLOv4, Faster Region-based Convolutional Neural Network (R-CNN) and classic convolutional neural network models. The results of the experiments show that, in bright settings, the model attains a median detection accuracy of 0.9275. In addition, it obtains a pedestrian detection accuracy of 0.88 and a vehicle detection accuracy of 0.90 in rainy situations. Furthermore, the model has achieved remarkable accuracy in detecting obstacles at night. Additionally, it demonstrates improved memory rates and average precision in circumstances where traffic is congested. The exceptional performance of the model can be ascribed to its distinctive modular configuration and mechanisms for interaction that are highly efficient. This research offers a viable and effective approach for real-time obstacle detection in autonomous vehicles, despite the fact that restrictions exist owing to experimental settings and the dataset.
Design and Optimisation of Wireless Charging Systems for Public Transit Buses
To reduce the electric buses emission of particulate matter, as electric buses are being rapidly adopted in public transit, solutions for efficient charging systems are required. From this angle, this paper proposes a design and optimisation model for Wireless Charging Systems (WCS) of public transit buses, aimed at reducing system costs and improving operational efficiency. Five variables of the design, consisting of battery size, number of mobile WPT pads, stationary charging rate, service headways and stop densities, are utilised in the optimisation model. These design variables were data-normalised and scaled to standardise their effects on the optimisation process. Using the Finite Element Method (FEM) in ANSYS Maxwell, an electromagnetic field simulation was performed to find the optimised positions of WPT pads so that effective energy transfer can occur. Key performance metrics such as energy efficiency and system costs were used for classification using a Decision Tree Classifier and the most cost-effective designs based on these metrics were classified. Results reveal that optimised WCS are more advantageous than statically charged systems with respect to reduction of both costs to both transit agencies and passengers, as well as improvement of service quality.
Enhancing Path Tracking for Autonomous Vehicles using Adaptive PID Control and Particle Swarm Optimisation
A path tracking strategy that modifies the classical Proportional-Integral-Derivative (PID) controller with adaptive parameters optimised through a particle swarm optimisation algorithm and supplemented with a feed-forward controller is proposed for self-driving cars in this paper. Such a controller design aims to reduce errors in lateral displacement and heading while promoting smooth, optimal turns. As a part of this optimisation routine, parameters like a Proportionality Constant (Kp), Integration Constant (Ki), Derivative Constant (Kd) and heading error constant (Kh) and a look-ahead parameter would be taken into consideration. The mean absolute error of lateral error is minimised to 0.68993 m, with a root mean square error of 0.76227 m. Furthermore, the maximum lateral error is minimised to 2.0 m. The variance of the steering rate is minimised to 0.62233 (rad/s)2. It reveals that the steering response is pretty smooth. The mean steering angle is also 0.16967 rad. The presence of feedforward control terms leads to a remarkable decrease in oscillations in heading and lateral errors, with peak heading errors less than 5° and lateral errors tending towards zero. The results of the simulation show that the best-designed PID controller will enhance the accuracy of the path-tracking performance.
Thermal Behaviour, Coating Performance and SEM Analysis of Surface Morphology Aspects of Fiber Reinforced Polymer Composites
The present study investigates the influence of thermal behaviour, coating performance, and surface morphology on fibre-, filler-, and nanofiller-reinforced polymer matrix composites. Key parameters such as fibre type (natural or synthetic), matrix material, fibre orientation, reinforcement volume fraction, and the presence of coatings are systematically analysed to understand their impact on thermal performance. Surface morphological analysis is conducted to identify the underlying wear mechanisms and modes of failure. The role of fibre reinforcement type and its proportion in achieving optimal wear resistance is also evaluated. Additionally, the effects of abrasive material characteristics including particle size, shape, and composition, on the wear behaviour of the composites are examined. Various coating materials and deposition techniques are assessed to determine their effectiveness in enhancing the thermal and wear performance of the composites. Furthermore, the study compares computational simulation results with experimental findings to evaluate the accuracy and reliability of predictive models in capturing wear behaviour and material deformation..
Performance and Emission Prediction of CI Engine Fuelled with ZOME20 Blends Enhanced by Nanoparticles using Advanced Machine Learning Models
Here, we investigate the joint effects of biodiesel-nanoparticle fuel composites and machine learning modelling on diesel engine performance and emissions. The experiment was conducted using a single-cylinder diesel engine with 20% Ziziphus Oenoplia Methyl Ester (ZOME20) and is paired with 80% diesel. Al₂O₃ and graphene oxide nanoparticles were added to the ZOME20 blend at the concentration levels of 50-200 ppm. As the results show, due to a high thermal conductivity and accompanying catalytic oxidation capacity, Al₂O₃ nanoparticles significantly improved combustion efficiency. Meanwhile, 20% Ziziphus Oenoplia Biodiesel Blend with 150 ppm Additive (ZO20A150) yielded the highest Brake Thermal Efficiency (BTE) and the lowest Brake Specific Fuel Consumption (BSFC); it also helped decrease CO, HC and smoke emissions, while the tendency of NOx also decreased, which was attributed to the in-cylinder temperature rise. Opposite results could be obtained in the models, with KNN, Hyper-SVR and linear models delivering the most credible results and undercutting the experimental data by 10% at maximum. The best prediction was made by the Random Forest model, with R² ≈ 1.0. Thus, the investigation is indicative of ZO20A150 being the best blend with which to improve efficiency at the expense of increased emissions and the Random Forest model is the most reliable ML tool for measuring engine performance when biodiesel is matched with specific types of nanoparticles.
Predictive Modelling of Cooled Gas Turbine Operating Parameters: RSM based Multi-Objective Optimisation
An analysis of gas turbine cycle has been carried out for predicting optimum operating parameters using Response Surface Methodology (RSM) is a multi-objective optimisation technique. In addition to energy and exergy, analysis of the cycle has also been carried out. The results obtained from present study shows that gas turbine specific is found to have its best values (>370 kJ/kg) at compressor pressure ratio ~19. Thermal and rational efficiency have been found to have its highest values (>37%) at lower value of ambient temperature and compressor pressure ratio ~22-24. A main effect plot has also been plotted to find the difference between different coded levels to carry out optimisation analysis and shows that optimum individual values of different input operating parameters for thermal and rational efficiencies be TIT=1500 K, rp=24, AT=288K and RH=50%. The results from optimisation analysis reveals that optimum values of different output parameters Mass of Coolant (MoC), Compressor Work (Wc), Mass of Fuel (MoF), Gas Turbine Work Output (Wgt), Thermal Efficiency (TE) and Rational Efficiency (RE) are 0.0496kg/kg of air, 409.11kJ/kg, 0.02136kg/kg of air, 346.83kJ/kg, 38.53% and 37.33% respectively for corresponding input values of turbine-inlet-temperature, compressor-pressure-ratio, ambient-temperature and relative-humidity to be 1424.2424K, 18.1010, 288 K and 50.0% respectively.
Performance, Combustion and Emission Characteristics of a Diesel Engine Fuelled with Neem Oil Blended with Sodium Hydroxide, Sulphuric Acid and Calcium Oxide Nanoparticles
The objective of this project is to analyse the performance of biodiesel derived from neem seeds. To enhance its properties, various types of catalysts-alkali, acid and metal oxide-were incorporated during production. The primary goal was to identify the catalyst that yields biodiesel with the lowest emissions while maintaining good engine performance. Three types of biodiesel were produced using sodium hydroxide, calcium oxide and sulphuric acid as catalysts. The results indicate that the biodiesel blend produced with calcium oxide exhibited superior performance compared to the other two blends. Key performance parameters such as brake thermal efficiency, specific fuel consumption and maximum torque were evaluated. Emission tests were also conducted to measure the pollutant levels of each biodiesel blend. The findings show that the calcium oxide-catalysed blend produced the lowest emissions among the tested fuels. Overall, the results are promising and suggest that neem seed-based biodiesel produced with calcium oxide is a viable alternative to conventional diesel fuel.