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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.

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.

Traditional methods for monitoring corrosion processes and mechanisms in real time can be both time consuming and challenging to interpret, especially when evaluations at multiple temperatures are required. Reported at SAE world congress 2017 by this author, a new method for measuring the change in resistance of a thin copper wire was applied to provide a way to monitor the corrosion of copper in situ. In this work, a copper alloy in thin wire form has been used to compare the corrosion rates to pure copper. New insights on the kinetics and mechanisms of corrosion in the presence of lubricant additives over a range of operating temperatures using the wire resistance test will be discussed. The corrosion processes observed here are highly dependent upon temperature. Making assessments of corrosion performance through elevated temperature differentiation testing can provide less optimal corrosion protection at the actual operating temperature condition.

With globalization, vehicles are sold across the world throughout different markets and their automotive brake systems must function across a range of environmental conditions. Currently, there is no current standardized test that analyzes brake pads’ robustness against severe cold and humid environmental conditions. The purpose of this proposed test method is to validate brake system performance under severe cold conditions, comparing the results with ambient conditions to evaluate varying lining materials’ functional robustness. The goal of this paper is to aid in setting a standardized process and procedure for the testing of automotive brakes’ environmental robustness. Seven candidate friction materials were selected for analysis. The friction materials are kept confidential. Design of experiment (DOE) techniques were used to create a full-factorial test plan that covered all combinations of parameters.

The energy demand of the world is keep increasing, major share of the demand is compensated by non-renewable fossil fuels. Automotive sector consumes a huge amount of fossil fuels, as majority of the segment use internal combustion as a prime mover. In the present era researches are carried to figure out the suitable replacements for fossil fuels to attain sustainable environment. One of the major challenge and keen interest of everyone is on waste management, several researches are aimed to bridge the gap between energy demand and waste management. In such way biofuels came into limelight a decade ago, still numerous works are carried in the area for creating socio economic friendly environment. Enormous studies have been carried out to assess their performance in the internal combustion engines, here in the present study performance of the working material against the biodiesel is studied.

In this study, the copper corrosion rates of commercially available lubricants used in electrified and conventional transmissions are measured in both vapor and solution phases simultaneously using an updated version of our previously reported wire resistance test [1]. Unlike the commonly used copper strip tests (versions of the ASTM D130) that generally require high temperatures and long times to differentiate the corrosivity of fluids, the wire resistance test is sufficiently sensitive as to allow real time assessment, thus enabling an efficient and cost-effective way to screen lubricant chemistries over a range of potential operating temperatures. The results of even our small study underscores the importance of understanding both the vapor and solution corrosion across a wide range of temperatures.

Wound rotor synchronous machines (WRSM) without rare-earth magnets are becoming more popular for traction applications, but their potential in drive performance has not yet been fully explored. This paper presents a Pulse Width Modulation (PWM) scheme optimization procedure to minimize motor and inverter losses. It leverages different PWM schemes with different PWM switching strategies and switching frequencies. First, a generic PWM-induced motor loss calculation tool developed by BorgWarner is introduced. This tool iteratively calculates motor losses with PWM inputs across the entire operating map, significantly improving motor loss prediction accuracy. The inverter losses are then calculated analytically using motor and wide-bandgap (WBG) switching device characteristics. By quantifying these various scenarios, the optimal PWM scheme for achieving the best system efficiency across the entire operating map is obtained.

FMVSS No. 205, “Glazing Materials,” uses impact test methods specified in ANSI/SAE Z26.1-1996. NHTSA’s Vehicle Research and Test Center initiated research to evaluate a subset of test methods from ANSI Z26.1-1996 including the 227 gram ball and shot bag impact tests, and the fracture test. Additional research was completed to learn about potential changes to tempered glass strength due to the ceramic paint area (CPA), and to compare the performance of twelve by twelve inch flat samples and full-size production parts. Glass evaluated included tempered rear quarter, sunroof, and backlight glazing. Samples with a paint edge were compared to samples without paint, and to production parts with and without paint in equivalent impact tests. A modified shot bag with stiffened sidewalls was compared to the ANSI standard shot bag. The fracture test comparison included evaluating the ANSI Z26.1 impact location and ECE R43 impact location.

The modern luxurious electric vehicle (EV) demands high torque and high-speed requirements with increased range. Fulfilling these requirements gives rise to the need for increased efficiency and power density of the motors in the Electric Drive Unit (EDU). Internal Permanent Magnet (IPM) motor is one of the best suited options in such scenarios because of its primary advantages of higher efficiency and precise control over torque and speed. In the IPM motor, permanent magnets are mounted within the rotor body to produce a resultant rotating magnetic field with the 3-phase AC current supply in the stator. IPM configuration provides structural integrity and high dynamic performance as the magnets are inserted within the rotor body. Adhesive glue is used to install the magnets within the laminated stack of rotor.

As data science technologies are being widely applied on various industries, the importance of data itself increased. A typical manufacturer company has a vast data set of products as 2D&3D drawing formats, but a common problem was that building a database from the 2D&3D drawings costs much, and it is hard to update the database after it once built. Also, it is high-cost job when the new factor researched and necessary to investigate the new factors on previously fixed or uploaded drawings. As new products are developed with time, these problems are getting more difficult. In this paper, an automated database building method using CATIA introduced and future probabilities are suggested. An aluminum wheel part was used as an example. An automated logic used CATIA V5’s VBA functions and was handled by python programming language.

The powertrain system plays a crucial role in electric vehicles, exerting significant impact on both the dynamic and economic performances. A breakthrough has been observed by using the dual-motor powertrain system, which outperformed its single-motor counterparts. This study reports a dual-motor powertrain with magnetorheological technology. The powertrain consists of two motors, two magnetorheological brakes and a planetary gear set. Via regulating the brakes, the power transmission flow can be controlled to realise different torque ratios and velocities. The synergetic control of motors and brakes is capable of achieving smooth gear shifting without interruption. This paper details the design of the powertrain system: the structural configuration of the magnetorheological brakes is highlighted, the magnetic field distribution of the brakes under different currents is simulated by COMSOL Multiphysics, and the torque capacities of the brake are also calculated.

Recent studies have shown that for a given RON, fuels with a higher sensitivity (RON-MON) tend to have better antiknock performance at most knock-limited conditions in modern engines. The underlying chemistry behind fuel sensitivity was therefore investigated to understand why this trend occurs. Chemical kinetic models were used to study fuels of varying sensitivities; in particular their autoignition delay times and chemical intermediates were compared. As is well known, non-sensitive fuels tend to be paraffins, while the higher sensitivity fuels tend to be olefins, aromatics, diolefins, napthenes, and alcohols. A more exact relationship between sensitivity and the fuel's chemical structure was not found to be apparent. High sensitivity fuels can have vastly different chemical structures. The results showed that the autoignition delay time (τ) behaved differently at different temperatures. At temperatures below 775 K and above 900 K, τ has a strong temperature dependence.

This paper reviews the history of the General Motor's Epsilon Platform from a Body Structure perspective. From the time that it was conceived in 1996 to the present, the platform has evolved to meet many changing requirements. The focus of this paper will cover basic body requirements such as crash performance, modal requirements, packaging issues, changes for wheelbase and powertrains, mass, different body styles, etc, including the differences between European and US requirements. It will demonstrate that this globally developed platform met all its initial requirements and continued to evolve over time to meet additional changing requirements.

ALONG with larger tires, independent wheel suspensions, higher speeds, and the dynamic and vibrational problems associated with these innovations, came the need for chassis frames having a high resistance to torsional movements. The X-member-type frame has been the most generally adopted means for obtaining increases in this direction. However, the past few years have seen the need for torsional rigidity in the chassis frame to be intensified. Although considerable gains have been made, in general, these gains have been accomplished not by major improvements in the design of the structure but by the addition of material. Consequently, the weight of the chassis frame has become a serious problem, so much so that in many cases special heavy frames are being used for the open-body types where the need for a stiff frame is acute.

In today's industrial sphere, machines are the key supporting various sectors and their operations. Over time, due to extensive usage, these machines undergo wear and tear, introducing subtle yet consequential faults that may go unnoticed. Given the pervasive dependence on machinery, the early and precise detection of these faults becomes a critical necessity. Detecting faults at an early stage not only prevents expensive downtimes but also significantly improves operational efficiency and safety standards. This research focuses on addressing this crucial need by proposing an effective system for condition monitoring and fault detection, leveraging the capabilities of advanced deep learning techniques. The study delves into the application of five diverse deep learning models—LSTM, Deep LSTM, Bi LSTM, GRU, and 1DCNN—in the context of fault detection in bearings using accelerometer data. Accelerometer data is instrumental in capturing vital vibrations within the machinery.

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.

RAMBHA-LP (Radio Anatomy of Moon Bound Hypersensitive Ionosphere and Atmosphere - Langmuir Probe) is one of the key scientific payloads onboard the Indian Space Research Organization’s (ISRO) Chandrayaan-3 mission. Its objectives were to estimate the plasma density and its variations on the near lunar surface. The probe was initially kept in a stowed condition attached to the lander. A mechanism was designed and realized to meet the functional requirement of deploying the probe at a distance of 1 meter, equivalent to the Debye length of the probe in the moon’s plasma environment. The probe deployment mechanism consists of the Titanium alloy spherical probe with a Titanium Nitride coating on its surface to achieve a constant work function, a long carbon-fiber-reinforced polymer boom, a double torsion spring, a dust-protection box, and a shape-memory alloy-based Frangibolt actuator for low-shock separation. The entire mechanism weighed less than 1.5 kilograms.

The Daimler Detroit AssuranceⓇ 4.0 collision mitigation system is able to assist a driver in various aspects of safely operating their vehicle. One capability is the Active Brake Assist (ABA), which uses the Video Radar Decision Unit (VRDU) to communicate with the front bumper-mounted radar to provide information about potential hazards to the driver. The VRDU may warn the driver of potential hazards and apply partial or full braking, depending on the data being gathered and analyzed. The VRDU also records event data when an ABA event occurs. This data may be extracted from the VRDU using Detroit DiagnosticLink software. This paper presents an overview of the VRDU functionality and examines aspects of VRDU data such as the range and resolution of data elements, the synchronicity or timing of the recorded data, and application of the data for use in the analysis of crashes.