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Abstract Improving the energy performance of batteries can increase the reliability of electric aircraft. To achieve this goal, battery management systems (BMS) are required to keep the temperature within the battery pack and cells below the safety limits and make the temperature distribution as even as possible. Batteries have a limited service life as a result of unwanted chemical reactions, physical changes that cause the loss of active materials in the structure, and internal resistance increase during the charging and discharging cycle of the battery. These changes usually affect the electrical performance of batteries. Battery life can be increased only by reducing or preventing unwanted chemical reactions. Lithium-ion (Li-ion) batteries are a suitable option due to their high specific energy and energy density advantages. In this study, the necessity of heat management is emphasized. The discharge tests of the Li-ion battery provided 94.6 Wh under 10C and 90.9 Wh under 1C.

Abstract The prediction of mechanical elastic response of laminated hybrid polymer composites with basic carbon nanostructure, that is carbon nanotubes and graphene, inclusions has gained importance in many advanced industries like aerospace and automotive. For this purpose, in the current work, a hierarchical, four-stage, multilevel framework is established, starting from the nanoscale, up to the laminated hybrid composites. The proposed methodology starts with the evaluation of the mechanical properties of carbon nanostructure inclusions, at the nanoscale, using advanced 3D spring-based finite element models. The nanoinclusions are considered to be embedded randomly in the matrix material, and the Halpin-Tsai model is used in order to compute the average properties of the hybrid matrix at the lamina micromechanics level.

Abstract Inline piston pumps are extensively used in aircraft hydraulic systems. They can be found in engine-driven large-sized hydraulic pumps and zonal electric motor-driven mid-small sized pumps. Inline piston pumps are positive displacement pumps with variable volumetric flow controls. Positive displacement pumps can provide a variable flow rate over a wide range of suction pressures. Aircraft fly at high altitudes, and therefore these pumps have to work in extreme conditions such as low atmospheric pressure, low temperature. At low inlet pressures, the pump is highly susceptible to cavitation, i.e., insufficient filling capacity. The pressure below which pump flow rate drops drastically is known as critical inlet pressure. Extensive research has been carried out to study cavitation in inline piston pumps.

Abstract Dynamic stresses exist in parts of a catalyst muffler caused by the vibration of a moving vehicle, and it is important to clarify and predict the vibration response properties for preventing fatigue failures. Assuming a vibration isolating installation in the vehicle frame, the vibration transmissibility and local dynamic stress of the catalyst muffler were examined through a vibration machine. Based on the measured data and by systematically taking vibration theories into consideration, a new prediction method of the vibration modes and parameters was proposed that takes account of vibration isolating and damping. A lumped vibration model with the six-element and one mass point was set up, and the vibration response parameters were analyzed accurately from equations of motion. In the vibration test, resonance peaks from the hanging bracket, rubber bush, and muffler parts were confirmed in three excitation drives, and local stress peaks were coordinate with them as well.

Abstract In this article, a unique design for Hydro-Pneumatic Energy Harvesting Suspension HPEHS system is introduced. The design includes a hydraulic rectifier to maintain one-way flow direction in order to obtain maximum power generation from the vertical oscillation of the suspension system and achieve handling and comfort car drive. A mathematical model is presented to study the system dynamics and non-linear effects for HPEHS system. A simulation model is created by using Advanced Modeling Environment Simulations software (AMEsim) to analyze system performance. Furthermore, a co-simulation platform model is developed using Matlab-Simulink and AMEsim to optimize the PID controller parameters of the external variable load resistor applied on the generator by using Particle Swarm Optimization (PSO).

Abstract A new concept of instantaneous wheel turn center (IWTC) is proposed to evaluate and improve multi-axle vehicle steering coordination performance. The concept of IWTC and its calculation method are studied. The index named dispersion of IWTC is developed to evaluate the vehicle steering coordination performance quantitatively. The simulation tests based on a three-axle off-road vehicle model are conducted under different vehicle velocities and lateral accelerations. The simulation results show that the turn centers of different wheels are disperse, and the dispersion becomes larger with the increase of vehicle velocities and lateral acceleration. Since suspension has important influences on vehicle steering performance, the genetic algorithm is used to optimize the suspension hard points and bushing stiffness, aiming at minimizing the dispersion of wheel turn centers (DWTC) to improve the vehicle steering coordination performance.

Abstract This research developed methods for a virtual operator model (VOM) to learn the optimal control inputs for operation of a virtual excavator. Virtual design, used to model, simulate, and test new features, has often been limited by the fidelity of the virtual model of human operators. Human operator learns, over time, the capability, limits, and control characteristics of new vehicles to develop the best strategy to maximize the efficiency of operation. However, VOMs are developed with fixed strategies and for specific vehicle models (VMs) and require time-consuming re-tuning of the VOM for each new vehicle design. Thus, there typically is no capability to optimize strategies, taking account of variation in vehicle capabilities and limitations. A VOM learning capability was developed to optimize control inputs for the swing-to-pile task of a trenching operation. Different control strategies consisted of varied combinations of speed control, position control, and coast.

Abstract The Friction stir welding (FSW) is recently presented so to join different materials without the melting process as a solid-state joining technique. A widely application for the FSW process is recently developed in automotive industries. To create the welded components by using the FSW, the plunged probe and shoulder as welding tools are used. The Finite Element Method (FEM) can be used so to simulate and analyze material flow during the FSW process. As a result, thermal and mechanical stresses on the workpiece and welding tool can be analyzed and decreased. Effects of the welding process parameters such as tool rotational speed, welding speed, tool tilt angle, depth of the welding tool, and tool shoulder diameter can be analyzed and optimized so to increase the efficiency of the production process. Material characteristics of welded parts such as hardness or grain size can be analyzed so to increase the quality of part production.

Abstract In this work, the complex relationship between deformation history and residual stresses in a magnesium-to-aluminum self-pierce riveted (SPR) joint is elucidated using numerical and experimental approaches. Non-linear finite element (FE) simulations incorporating strain rate and temperature effects were performed to model the deformation in the SPR process. In order to accurately capture the deformation, a stress triaxiality-based damage material model was employed to capture the sheet piercing from the rivet. Strong visual comparison between the physical cross-section of the SPR joint and the simulation was achieved. To aid in understanding of the role of deformation in the riveting process and to validate the modeling approach, several experimental measurements were conducted. To quantify the plastic deformation from the piercing of the rivet, micro hardness mapping was performed on a cross-section of the SPR joint.

Abstract Surface roughness is one of the important aspects in producing quality die. Wire Electrical Discharge Machine (WEDM) is commonly used in tool and die fabrication, since the die material is usually difficult to cut using traditional metal removal processes. Selection of optimal WEDM cutting parameters is crucial to obtain quality die finish. In this study, 2379 steel which equivalent to SKD 11 is selected as the die material. Four main WEDM cutting parameters, namely, pulse duration (A), pulse interval (B), servo voltage (C), ignition pulse current (D), were experimentally evaluated for both main cut and multiple trim cuts using Taguchi Method. Taguchi’s L9 orthogonal array is employed for experimental design and analysis of variance (ANOVA) was used in recognizing levels of significance of WEDM cutting parameters.

Abstract New analytical structural stress solutions for a rigid inclusion in a finite square thin plate with clamping edges under opening loading conditions are developed. The new solutions are used to derive new analytical structural stress and stress intensity factor solutions for similar and dissimilar spot welds in cross-tension specimens. Three-dimensional finite element analyses are conducted to obtain the stress intensity factor solutions for similar spot welds and dissimilar magnesium/steel spot welds in cross-tension specimens of equal thickness with different ratios of half-specimen width-to-weld radius. A comparison of the analytical and computational solutions indicates that the analytical stress intensity factor solutions for similar spot welds in cross-tension specimens of equal thickness are accurate for large ratios of half-specimen width-to-weld radius.

Abstract In this study, an attempt is made to deduce the number of teeth in the driven sprocket of a Formula SAE (FSAE) car using Optimum Lap software based on track run simulation of the car, which comes out to be 51 teeth. The sprocket material was selected as Aluminum Alloy AL-7075 T6 because of its strength-to-weight ratio. In addition to it, the generative design strategy by Fusion-360 was utilized to automatically engender the slotted sprocket design on the ground of stress induced on it during operation. Furthermore, the design was verified virtually carrying out static structural and fatigue analysis under the worst-case scenario in CAE software. The overall weight reduction achieved was around 45%. Furthermore, the center-to-center distance between the sprockets and the number of chain links required were also calculated on the basis of space constraints and the wrap angle of the sprocket.

Abstract This article presents a finite element (FE)-based model to simulate the temperature swing phenomenon of Silica-Reinforced Porous Anodized Aluminum (SiRPA) thermal barrier coatings (TBCs). A realistic three-dimensional (3D) SiRPA coating microstructure is constructed based on the morphology of an experimentally grown coating structure, and the known relationship of geometry and anodization parameters. The coatings’ thermophysical properties are first computed using the FE model. The predicted thermal conductivity, thermal diffusivity, and bulk density are compared well with the experimental values. Also transient thermal analysis is conducted to model the temperature swing effect of the coating by comparing the temperature fluctuation of SiRPA coating with conventional Yttria-Stabilized Zirconia (YSZ)-based TBCs. With the predicted thermophysical properties, the model is capable to predict the “temperature swing” effect of SiRPA by transient thermal analysis.

Abstract Maximum lifetime and minimum manufacturing cost for new products are the primary goals of companies for competitiveness. These two objectives are contradictory and the geometric dimensions of the products directly control them. In addition, the earlier design errors of new products are predicted, the easier and more inexpensive their rectification becomes. To achieve these objectives, we propose in this article a novel model that makes it possible to solve the problem of optimizing the lifespan and the manufacturing cost of new products during the phase of their design. The prediction of the life of the products is carried out by an energy damage method implemented on the finite element (FE) calculation by using the ABAQUS software. The manufacturing cost prediction is carried out by applying the ABC cost estimation analytical method. In addition, the optimization problem is solved by the method of genetic algorithms.

Abstract The high quality of the machined parts in a short time is a research challenge for enhancing these parts’ operating performance. Optimizing the machining operations and adequately selecting the cutting parameters can solve this challenge. Thus, this work proposes an optimization approach of the machining process parameters of epoxy hybrid nanocomposites reinforced by multiwall carbon nanotubes (MWCNTs) and aluminum oxide (Al2O3). Cutting speed (V), feed rate (F), insert nose radius, and depth of cut (D) were the machining parameters. The roundness error and surface roughness (Ra) were selected as process response control parameters. The optimization techniques such as response surface method (RSM) and grey relation analysis (GRA) with the variance of analysis (ANOVA) were involved. Forty experimental runs were performed. The RSM optimization and ANOVA results showed that the insert nose radius and F are the most significant factors that affect the Ra.

Abstract A two-dimensional model of three elements, high-lift airfoil, was designed at a Reynolds number of ?????? using computational fluid dynamics (CFD) to generate downforce with good lift-to-drag efficiency for a formula student open-wheel race car basing on the nominal track speeds. The numerical solver uses the Reynolds-averaged Navier-Stokes (RANS) equation model coupled with the Langtry-Menter four-equation transition shear stress transport (SST) turbulence model. Such model adds two further equations to the ?? − ?? SST model resulting in an accurate prediction for the amount of flow separation due to adverse pressure gradient in low Reynolds number flow. The ?? − ?? SST model includes the transport effects into the eddy-viscosity formulation, whereas the two equations of transition momentum thickness Reynolds number and intermittency should further consider transition effects at low Reynolds number.

Abstract In this work, optimal modeling parameters for self-pierce riveting (SPR) were determined using a factorial design of experiments (DOE). In particular, we show statistically how each of the calibrating parameters used in modeling the SPR process through nonlinear finite element modeling can drastically change the geometry of the joint. The results of this study indicate that the degree of interlock, which is a key feature of a sound joint, is largely influenced by the friction between the die and bottom sheet as well as the friction between the rivet and top sheet. Furthermore, this numerical study also helped elucidate the role of friction in SPR and sheds light on how coatings with diverse friction coefficients can affect material deformation and ultimately structural integrity of the joint.

Abstract Finite Element Analysis (FEA) of metal cutting is largely the domain of research organizations. Despite significant advances towards accurately modelling metal machining processes, industrial adoption of these advances has been limited. Academic studies, which mainly focused on orthogonal cutting, fail to address this discrepancy. This paper bridges the gap between simplistic orthogonal cutting models and the complex components typical in the manufacturing sector. This paper outlines how to utilize results from orthogonal cutting simulations to predict industrially relevant performance measures efficiently. In this approach, using 2D FEA cutting models a range of feed, speed and rake angles are simulated. Cutting force coefficients are then fit to the predicted cutting forces. Using these coefficients, forces for 3D cutting geometries are calculated.

Abstract In order to improve robustness of vehicle dynamic performance, a steering mechanism model is proposed with alignment parameters of front wheel based on preference function method. In the steering mechanism model controllable variables include the trapezoid connection length, the base angle of steering trapezoid, the kingpin inclination angle, caster, camber and uncontrollable variables include load and initial braking velocity. Optimization objective is some vehicle dynamic performance. In the preference function method the individual performance preference and preference aggregation in designing variable space and performance variable space are analyzed. The individual performance preference includes the controllable variable preference, noise factor preference and optimization objective preference. The aggregation function is developed by aggregating all the individual performance preferences.

Abstract The pursuit of improved fuel economy through weight reduction, reduced manufacturing costs, and improved crash safety can result in increased compliance in automobile structures. However, with compliance comes an increased susceptibility to aerodynamic and vibratory loads. The hood in particular withstands considerable aerodynamic force at highway speeds, creating the potential for significant aeroelastic response that may adversely impact customer satisfaction and perception of vehicle quality. This work seeks an improved understanding in computational and experimental study of fluid-structure interactions between automobile hoods and the surrounding internal and external flow. Computational analysis was carried out using coupled CFD-FEM solvers with detailed models of the automobile topology and structural components. The experimental work consisted of wind tunnel tests using a full-scale production vehicle.