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Abstract This article describes the development of a low-cost rotary screw compressor technology to meet the requirements of a mini air compressor application for electric vehicle (EV) air brake and suspension systems. An existing rotor profile and size was initially used to build an “Alpha” compressor prototype. This was tested to provide data for analysis and numerical simulation to determine a smaller rotor size, rotor profile, and more efficient overall package for hybrid/EV air brake and suspension applications. From the “Alpha” prototype testing and analysis, the author identified the root causes of lower energy efficiency. To address these deficiencies and develop a foundation for an optimized solution for the intended application, the author developed a clean sheet design. A smaller diameter rotor set with high tip speed was developed using parameter calculations, working process simulation, and prototype test data analysis.

Abstract The efficiency of the traditional machining process becomes limited because of the mechanical properties and complexity of the geometric shape of the processed materials. This difficulty is resolved through the nonconventional machining process. Electric Discharge Machining (EDM) process is one of the popular nonconventional machining processes among all nonconventional machining processes for processing such materials. The main objective of the present research work is to evaluate the effect of percentage weight fraction of reinforcement and process parameters on machining responses during EDM of aluminum (Al) 7075-reinforced boron carbide (B4C) and graphite metal matrix composite (MMC) and optimization of the result.

Abstract Under high-speed working conditions of an engine, the lubrication and tribological performance (LTP) of the crankpin bearing (CB) are strongly influenced by the oil film pressure (p) and asperity contact in the mixed lubrication regime (MLR) of CB, while these parameters mainly depend on the CB’s geometrical dimensions including the bearing radius (r b), bearing width (B), surface roughness (σ), gap between crankpin and bearing (c), and crankpin speed (ω). To analyze the sensitivity of the dynamic parameters of the r b, B, σ, c, and ω on the CB’s LTP, a hybrid model of the piston-rod-crank dynamic and CB lubrication is proposed to establish the dynamic equations of the CB. An algorithm program written in MATLAB software is then applied to solve the dynamic equations. The effect of the dynamic parameters of the r b, B, σ, c, and ω on the CB’s LTP is simulated and evaluated via the indexes of the p, asperity contact force, friction force, and friction coefficient.

Abstract The elastic hydrodynamic lubrication (EHL) region of the crankpin bearing (CB) not only creates the high friction force due to the solid asperity contact but also reduces the CB’s lubrication effectiveness. To improve the CB’s tribological properties, the partial textures (PT) designed on the EHL region are proposed. Based on a new hydrodynamic approach combined between the CB’s lubrication model and the slider-crank-mechanism (SCM) dynamics model, the distribution density of spherical dimples (SDs) and different structures of the SDs, circular-cylindrical dimples (CCDs), square-cylindrical dimples (SCDs), and wedge-shaped dimples (WSDs) are then simulated and assessed for their effectiveness on improving CB’s tribological properties, respectively. The oil film pressure (p), friction force (F f), and friction coefficient (μ) of the CB are selected as the evaluation indexes.

Abstract Passengers would always like to reach their destinations with minimum commute time. Generating a higher thrust is a necessity. This implies that the turbomachinery associated with the power plant has to rotate faster and with higher efficiencies. However, high rotational speeds, mainly in the transonic regime, often lead to boundary layer separation, shocks, compressor stall, and surge. The current investigation is an attempt to reduce the abovementioned phenomena. It involves the performance study of a smoothened controlled diffusion airfoil (CDA) blade that has been optimized by “Multi-Objective Genetic Algorithm” (MOGA) by altering maximum camber location and stagger angle. Inlet pressure is varied from 15 kPa to 30 kPa and the angle of attack ranging from 40.4° to 56.4°. C48-S16-BS1 is validated and considered as the baseline profile, and all other blades are collated to this.

Abstract This article compares elastohydrodynamic lubrication (EHL) and mobility-based solution methods for the determination of cyclic minimum film thickness hmin * encountered in four-stroke, big-end connecting rod bearings. Mobility-based solution methods are substantially faster than the EHL method for such bearings, so quantifying the accuracy of mobility-based methods is an obvious benefit to the engine designer. Production-level connecting rods are modeled and analyzed using an established mass-conserving mode-based EHL formulation, accounting for realistic oil feed arrangements and realistic housing deformation associated with structural inertia and surface pressures. From a large set of dimensional studies, it is observed that hmin * calculated using mass-conserving EHL can be bounded by results obtained from finite-bearing mobility formulations, provided that a non-dimensional bearing number Λ falls below a critical value Λ crit ≈ 4.

Abstract An accurate and rapid thermal model of an axle-brake system is crucial to the design process of reliable braking systems. Proper thermal management is necessary to avoid damaging effects, such as brake fade, thermal cracking, and lubricating oil degradation. In order to understand the thermal effects inside of a lubricated braking system, it is common to use Computational Fluid Dynamics (CFD) to calculate the heat generation and rejection. However, this is a difficult and time-consuming process, especially when trying to optimize a braking system. This article uses the results from several CFD runs to train a Stacked Ensemble Model (SEM), which allows the use of machine learning (ML) to predict the systems’ temperature based on several input design parameters. The robustness of the SEM was evaluated using uncertainty quantification.

Abstract Off-highway equipment are subjected to diverse environmental conditions, severe duty cycles, and multiple simultaneous operations. Due to its continuous, high-power adverse operating conditions, equipment are exposed to high thermal loads, which result in the deterioration of its performance and efficiency. This article describes a model-based system simulation approach for thermal performance evaluation of a self-propelled off-highway vehicle. The objective of developing the simulation model including thermal fidelity is to quantify the impact of thermal loads on vehicular system/subsystems performance. This article also describes the use of simulation models for driving architectural design decisions and virtual test replication in all stages of product development.

Abstract Cavitation erosion caused by high-frequency vibrating walls can appear in the cooling circuit of internal combustion engines along the liners. The vibrations caused by the mechanical forces acting on the crank drive can lead to temporary regions of low pressure in the coolant with local vapor formation, and vapor collapse close to the liner walls leads to erosion damage, which can strongly reduce the lifetime of the entire engine. The experimental investigation of this phenomenon is so time consuming and expensive, which it is usually not feasible during the design phase. Therefore, numerical tools for erosion damage prediction should be preferred. This study presents a numerical workflow for the prediction of cavitation erosion damages by coupling a three-dimensional (3D) Multi-Body-Dynamic (MBD) simulation tool with a 3D Computational Fluid Dynamics (CFD) solver.

Abstract Uncertainties in design represent a considerable industrial stake. Controlling the reliability and robustness of a mechanical system at the level of design has become necessary in order to control these uncertainties. Using the theory of probabilistic design optimization, the present work reports on the application of the concept of reliability-based robustness on minimizing the weight of a planetary gear train (PGT). The optimum combination of reliability and robustness for the minimum weight of the PGT was found using an optimization algorithm based on Particle Swarm Optimization (PSO) and Monte Carlo Simulation (MCS). The algorithm was developed by combining the propagation of uncertainties with the optimization of the function objective within a single probabilistic model. The results show that a reliability-based robust design offers a better alternative to the traditional deterministic design models.

Abstract Internal combustion (IC) engines incorporating the conventional slider-crank mechanism are subjected to high frictional power losses mainly due to the piston-rod assembly. Due to its simplicity, IC engines have utilized this mechanism almost unchanged since its introduction. This study introduces the hypocycloid gear mechanism (HGM) as an alternative to the conventional slider-crank mechanism for IC engine systems. The HGM provides several advantages that allow for enhancing both the thermal and mechanical efficiencies of IC engines. In this study, the kinematic and dynamic performances of the HGM engine are analyzed in detail. The geometric relations of the HGM are used to derive the kinematic equations that describe the piston motion. These equations are then used to derive the dynamics equations considering gas and inertia forces acting on the HGM.

Abstract The mechanical efficiency of the current continuously variable transmission (CVT) suffers from high pump loss induced by a high-pressure system. A novel wedge mechanism is designed into the CVT clamp actuation system to generate the majority of clamp force mechanically. Therefore, the hydraulic system can operate at a low-pressure level most of the time, and the pump loss is greatly reduced to improve the CVT’s mechanical efficiency. Through dynamic analysis and design optimization, 90% of clamp force is contributed by the wedge mechanism and the rest of the 10% is generated by a conventional hydraulic system. The optimal design is validated through dynamic modeling using Siemens Virtual.Lab software by simulating the wedge clamp force generation, ratio change dynamics, and system response under tip-in conditions. After that, we built prototype components that target 70% of the clamp force contributed by the wedge mechanism and tested them on a transmission dynamometer.

Abstract In this article, we propose a method of combining neural networks (NN) with nonlinear state-space models (SSM). Such model parts that are well understood can be integrated into the state space, while the NN can estimate such parts that are uncertain or hard to model. We apply the method to vehicle state estimation on a race track. Therefore, we derive a nonlinear two-track model with a scaled magic formula and adaptively estimate the tire parameters—stiffnesses and maximum friction potential—with the NN. The results show that the NN is able to reach an excellent estimation performance and generalizes over different model parameters, such as tire type, tread depth, surfaces conditions, and maneuvers. The trained model is furthermore integrated into an Extended Kalman Filter (EKF) to estimate the longitudinal speed, lateral speed, and yaw rate of the vehicle.

Abstract The lack of traceability in today’s supply-chain system for auto components makes counterfeiting a significant problem leading to millions of dollars of lost revenue every year and putting the lives of customers at risk. Traditional solutions are usually built upon hardware such as radio-frequency identification (RFID) tags and barcodes, and these solutions cannot stop attacks from supply-chain (insider) parties themselves as they can simply duplicate products in their local database. This industry-academia collaborative work studies the benefits and challenges associated with the use of distributed ledger (or blockchain) technology toward preventing counterfeiting in the presence of malicious supply-chain parties. We illustrate that the provision of a distributed and append-only ledger jointly governed by supply-chain parties themselves makes permissioned blockchains such as Hyperledger Fabric a promising approach toward mitigating counterfeiting.

Abstract Many disciplines of the current vehicle development process are still based on subjective scoring of prototypes, especially in the field of vehicle dynamics. To further reduce the need for hardware and to discover possible weaknesses early in the development process and therefore reduce costs, suitable simulative methods are required. The influence of body and chassis stiffness on vehicle dynamics is not fully understood and requires further research to implement reliable simulative methods. The development of methods requires an understanding and objective depiction of the physical chain. The influences of stiffening beams at the front of a vehicle on the static and dynamic response of wheels and body are observed by using static and dynamic suspension kinematics and a compliance test rig setup. This response is assessed by acceleration sensors, strain gauges, and optical measurement of wheel positions.

Abstract Combining ball milling with stir casting in the synthesis of nanocomposites is found effective in increasing the strength and ductility of the nanocomposites. In the first step, the nanoparticles used as reinforcement are generated by milling a mixture of aluminum (Al) and manganese dioxide (MnO2) powders. A mixture of Al and MnO2 powders are mixed in the ratio of 1:2.4 by weight and milled at 300 rpm in a high-energy planetary ball mill for different durations of 120 min, 240 min, and 360 min to generate nano-sized alumina (Al2O3) particles. It is supposed that the powders have two different roles during milling, firstly, to generate nano-sized Al2O3 by oxidation at the high-energy impact points due to collision between Al and MnO2 particles, and secondly, to keep nano-sized Al2O3 particles physically separate by the presence of coarser particles.

Abstract To improve the lubrication and friction of the crankpin bearing (CB) in the engine, the design of surface textures on the bearing surface is proposed and researched based on the CB hydrodynamic dynamic model. To enhance the reliability of the research results and its closeness to reality, the optimal CB parameters, the experimental data of the external dynamic load W0 acting on the crankpin, and the CB surface roughness in the well-known existing researches are referred to as input data for the simulation process. The effect of the distribution density {n, m}, diameter D, and depth of the microcircular textures hd on improving the lubrication and friction are then analyzed based on the indexes of the increase in the oil film pressure, decrease in the solid asperity contacts in the mixed lubrication region (MLR), friction force, and coefficient of friction (COF) between the crankpin and bearing surfaces, respectively.

Abstract The lubricating properties of diesel are an imperative aspect for the optimal functioning of fuel injection components. Regulatory standards followed by refineries utilize accelerated wear testing methodologies. These tests provide indicative results for judging the lubricity but are not conclusive for determining wear in functional applications attributed to higher loads and other environmental factors. In the course of this article, a tribological evaluation was carried out on Low-Sulfur Diesel (LSD) and Ultralow Sulfur Diesel (ULSD) by utilizing modified test parameters incorporating higher loads and a more extensive gradient of temperature on High-Frequency Reciprocating Rig (HFRR) tribotester. The variance in the resultant coefficient of friction (COF) and wear scar concerning the change in parameters was observed as well as a comparative analysis was drawn between both test fuels.

Abstract The most important and most easily damaged part of a revolving vane (RV) compressor is the vane. The friction loss of the vane determines the service life and maintenance cost of the RV compressor to a certain extent. To improve the efficiency and prolong the service life of the RV compressor, it is of great significance to analyze the dynamics of the vane and reduce the friction loss of the vane. In this article, a scheme is proposed to reduce the friction at the vane’s sides for the RV compressor. In the proposed scheme, the force acting on the vane tip due to the cylinder inertia is eliminated by driving the rotor and cylinder externally and separately; thus the friction loss at the vane’s sides is reduced. Calculations show that eliminating the effect of cylinder inertia can reduce the friction loss at the vane’s sides from 44.9 W to 24.7 W.

Abstract This article discusses a multi-item planning and scheduling problem in a job-shop system with consideration of energy consumption. Planning is considered by a set of periods, each one is characterized by a demand, energy, and length. Scheduling is determined by the sequences of jobs on available resources. A Mixed-Integer Linear Programming (MILP) problem is formulated to integrate planning and scheduling, it is considered as an NP-difficult problem. A Genetic Algorithm (GA) is then developed to solve the MILP, and then a hybridized approach of simulated annealing with genetic algorithm (HGASA) is presented to optimize the results. Finally, numerical results are presented and analyzed to evaluate the effectiveness of the proposed algorithms.