High-end Models Research Articles

Research on Product Positioning of New Energy Vehicles - Taking Tesla and Build Your Dream as Examples

This study focuses on the product positioning strategy of new energy vehicles, taking Tesla and Build Your Dream as examples. As a global leading electric vehicle manufacturer, Build Your Dream is committed to technological innovation and has launched a variety of new energy vehicle models, including pure electric vehicles, hybrid vehicles, and plug-in hybrid vehicles. Its product line covers multiple market segments, ranging from small city electric vehicles to large luxury electric vehicles, as well as special-purpose vehicles and commercial vehicles. In contrast, Tesla adopts a development model of first launching high-end models and then gradually expanding into the low-end market. From now on, Tesla's export volume is greater than Build Your Dream's, and it occupies a larger share of the global market. In terms of price, sales volume, sales channels, sales positioning, marketing strategies, imports, and exports, the two companies differ. Generally speaking, Tesla focuses on brand building and technological innovation, while Build Your Dream pays more attention to product cost-effectiveness and market share.

Estimating the Sustainability of AI Models Based on Theoretical Models and Experimental Data

As AI models become more and more common in process industry applications, it is important to understand their carbon footprint. Recent papers have shown that it can be quite big, i.e., the training of a single high-end model can result in emissions of more than 500t of CO2eq. In this paper we discuss the factors that influence the carbon footprint of AI models, explore what impact different decisions have, and show how the footprint can be reduced. We also evaluate different models to validate orchallenge theoretical assumptions from the literature. Two experimental examples using process industry data show the impact on providers of industrial analytics in particular.

Huawei Smartphone Marketing Case Analysis

Smart phones have become a part of people's lives, and Huawei mobile phones are the mainstream brand in China. This article will introduce Huawei's sales strategies in the context of the epidemic, Huawei's response strategies when its products are subject to U.S. sanctions, and Huawei's marketing and profit making skills in sandbox countries. In recent years, the price of conversation voice resources of major telecom companies in China has continued to decline, making the use of conversation voice resources by customers more and more. There are three reasons: the purchase of low-price models is price-driven and does not require on-site confirmation. The on-site display of medium and high-end models can strengthen the brand's positioning in the high-end field. The cost of offline channels is high, and the premium of first-line models is needed to ensure profits. Under the influence of COVID-19 and US policies, Huawei's smart phone marketing abroad must be reduced and also needs to increase its online marketing efforts. The relationship between the profitability of high-end mobile phones and retail outlets is a particularly important sales strategy of Huawei. Huawei should focus on facing different consumer groups at different times.

Direct Determination of Optimal Real-Space Orbitals for Correlated Electronic Structure of Molecules.

We demonstrate how to determine numerically nearly exact orthonormal orbitals that are optimal for the evaluation of the energy of arbitrary (correlated) states of atoms and molecules by minimization of the energy Lagrangian. Orbitals are expressed in real space using a multiresolution spectral element basis that is refined adaptively to achieve the user-specified target precision while avoiding the ill-conditioning issues that plague AO basis set expansions traditionally used for correlated models of molecular electronic structure. For light atoms, the orbital solver, in conjunction with a variational electronic structure model [selected Configuration Interaction (CI)] provides energies of comparable precision to a state-of-the-art atomic CI solver. The computed electronic energies of atoms and molecules are significantly more accurate than the counterparts obtained with the orbital sets of the same rank expanded in Gaussian AO bases, and can be determined even when linear dependence issues preclude the use of the AO bases. It is feasible to optimize more than 100 fully correlated numerical orbitals on a single computer node, and significant room exists for additional improvement. These findings suggest that real-space orbital representations might be the preferred alternative to AO representations for high-end models of correlated electronic states of molecules and materials.

A Study on Electromagnetic Riveting Behavior of High-Strength Rivets Depending on Hardness

Recently, the application of aluminum based on ultra-high strength steel is expanding around high-end models of electric vehicles, so it is necessary to develop strategic welding/joining technologies for these materials. In the case of overseas advanced automobile companies, such development is being carried out at the level of introducing mass production facilities through the development of joining technology, but in Korea, the localization rate of original core technology and related equipment in the field of welding and joining is still very insufficient. Therefore, in this study, in order to develop a high-strength rivet suitable for the rivet process during the multi-material bonding process, cold forging steel was used to attain an appropriate level of hardness through changes in the microstructure through heat treatment. Rivets with different hardness were fabricated through heat treatment, and flaring and tensile test were conducted. As a result of flaring test of rivets, buckling occurred with hardness values of Hv 447 and 486, while cracks occurred without buckling in rivets with hardness values of Hv 506. But as a result of tensile shear test using GA980 and Al5052 materials, there was no significant difference in tensile shear load values according to hardness values of the rivets.

Analysis and Optimization of Automotive Self-Priming Door Lock Closing Sound

<div>With higher customer expectations and advances in vehicular technology, automotive functions and operations are becoming more intelligent. Electric self-priming door locks fulfil the automatic closing and locking of side doors, hatchback doors, sliding doors, liftgates, decklids, etc. They are widely implemented into high-end models for the elegance of soft closing. In the list of perceived vehicle qualities, door-closing sound quality has been one of the important customer concerns in the market. In comparison to conventional door locks, electric self-priming door locks add another dimension to the development of sound quality for noise, vibration, and harshness (NVH) efforts. In this article, the characteristics of door-closing sound involving self-priming door lock mechanisms are analyzed and illustrated. Human perception of different sounds from the self-priming door lock working process is ranked by subjective evaluations. For typical door closing sounds associated with the self-priming lock mechanisms, i.e., the motor sound and rebound sound, real-case examples are discussed. A case of the buzzing noise issue due to the self-priming lock on a hatchback door is also presented. In these cases, the correlation between the sounds and the structure of the self-priming door locks is investigated and the root causes of the encountered issues are identified. The door closing sound quality associated with the self-priming door locks is improved in each case to meet the program requirements. In the particular cases presented in this work, the analysis involves psychoacoustic metrics for sound quality study originally. It is found later that sound pressure level can address the encountered issues, and thus only sound pressure level results are included.</div>

An Industrial Perspective on Magnesium Alloy Wheels: A Process and Material Design

Light weights wheels improve vehicle performance with respect to road handling, cornering as well providing fuel economy and reduced greenhouse gas emissions. Aluminum wheels are currently used in many models and are produced usually by low pressure assisted gravity casting. Important property requirements are fatigue strength, pressure tightness, tensile strength, impact resistance, and corrosion resistance. Many attempts have been made to convert aluminum road wheels to magnesium. Race cars and some of the high end models (Porsche, Ferrari, etc.) have used magnesium wheels. These wheels have been gravity cast or forged. Viable corrosion protection systems have been developed and magnesium wheels have been used with success on these models. To use magnesium on more modest models is a challenge due to cost issues. Higher productivity casting processes or more cost effective coating systems need to be utilized. The project consists of selecting magnesium alloys for road wheels, examining the possible cost effective casting processes and corrosion protection systems, evaluating the cost per one wheel and comparing it to aluminum wheel costs. The wheels will also be compared with respect to fatigue and impact properties, pressure tightness, and corrosion.

Development of IoT Smart Greenhouse System for Hydroponic Gardens

This study focused on the development of a smart greenhouse system for hydroponic gardens with the adaptation of the Internet of Things and monitored through mobile as one of the solutions towards the negative effects of the worlds booming population, never ending - shrinking of arable lands, and the effect of climate change drastically in our environments. To achieve the goal of the study, the researchers created an actual hydroponic greenhouse system with completely developing plants, and automation in examining and monitoring the water pH level, light, water, and greenhouse temperature, as well as humidity which is linked to ThingSpeak. The developed SMART Greenhouse monitoring system was tested and evaluated to confirm its reliability, functions, and usability under ISO 9126 evaluation criteria. The respondents who include casual plant owners and experts in hydroponic gardening able to test and evaluate the prototype, and the mobile application to monitor the parameters with the results of 7.77 for pH level, 83 for light, 27.94 deg C for water temperature, 27 deg C for greenhouse temperature, and 75% for humidity with a descriptive result in both software and hardware as Very Good with a mean average of 4.06 which means that the developed technology is useful and recommended. The SMART Greenhouse System for Hydroponic Garden is used as an alternative tool, solution, and innovation technique towards food shortages due to climate change, land shortages, and low farming environments. The proponents highly suggest the use of solar energy for the pump power, prototype wiring should be improved, the usage of a high-end model of Arduino to address more sensors and devices for a larger arsenal of data collected, enclosures of the device to ensure safety, and mobile application updates such as bug fixes and have an e-manual of the whole systems.

Observation-based trajectory of future sea level for the coastal United States tracks near high-end model projections

With its increasing record length and subsequent reduction in influence of shorter-term variability on measured trends, satellite altimeter measurements of sea level provide an opportunity to assess near-term sea level rise. Here, we use gridded measurements of sea level created from the network of satellite altimeters in tandem with tide gauge observations to produce observation-based trajectories of sea level rise along the coastlines of the United States from now until 2050. These trajectories are produced by extrapolating the altimeter-measured rate and acceleration from 1993 to 2020, with two separate approaches used to account for the potential impact of internal variability on the future estimates and associated ranges. The trajectories are used to generate estimates of sea level rise in 2050 and subsequent comparisons are made to model-based projections. It is found that observation-based trajectories of sea level from satellite altimetry are near or above the higher-end model projections contained in recent assessment reports, although ranges are still wide.

Implementation of Deep Learning Algorithm on a Custom Dataset for Advanced Driver Assistance Systems Applications

Road hazards such as jaywalking pedestrians, stray animals, unmarked speed bumps, vehicles, and road damage can pose a significant threat in poor visibility conditions. Vehicles are fitted with safety technologies like advanced driver assistance systems (ADAS) and AW (automatic warning) systems to tackle these issues. However, these safety systems are complex and expensive, and these proprietary systems are exclusive to high-end models. The majority of the existing vehicles on the road lacks these systems. The YOLO model (You Only Look Once Architecture) was chosen owing to its lightweight architecture and low inference latency. Since YOLO is an open-source architecture, it can enhance interoperability and feasibility of aftermarket/retrofit ADAS devices, which helps in reducing road fatalities. An ADAS which implements a YOLO-based object detection algorithm to detect and mark obstacles (pedestrians, vehicles, animals, speed breakers, and road damage) using a visual bounding box was proposed. The performance of YOLOv3 and YOLOv5 has been evaluated on the Traffic in the Tamil Nadu Roads dataset. The YOLOv3 model has performed exceptionally well with an F1-Score of 76.3% and an mAP (mean average precision) of 0.755, whereas the YOLOv5 has achieved an F1-Score of 73.7% and an mAP of 0.7263.

LBIST for Automotive ICs With Enhanced Test Generation

Contemporary and emergent automotive systems are heavily populated by complex integrated electronics. The number of safety-critical devices used in advanced driver-assistance systems or autonomous vehicles is growing with high-end models containing hundreds of embedded microcontrollers. Achieving functionally safe automotive electronics requires test solutions that might be costly to engineer. Therefore, to address challenges posed by high-quality and long-term reliability requirements, this article presents low-cost test pattern generation schemes for a scan-based hybrid logic BIST of automotive ICs. It may allow one to optimize test coverage and test time during in-system test applications. The first presented technique deploys a seed-flipping PRPG to periodically complement PRPG stages in a methodical tree-traversal manner. The second scheme is based on a seed-sorting approach that allows additional tradeoffs between test data volume and test coverage. As shown in this article, the proposed schemes can be easily integrated with a test compression environment and deployed in different modes of in-system testing, such as key-off, key-on, and periodic (incremental) online tests. Experimental results obtained for automotive designs and reported herein show improvements in test quality over conventional logic BIST schemes.

Performance Analysis of Thermographic Cameras Applied to Wood Damage Detection

Wood is a crucial component of the green economy of the 21st Century. From house construction to innovative daily applications and products, wood is one of the most sustainable resources. However, as a natural material, it suffers deterioration with time. Infrared thermography may provide an excellent potential for detecting internal damage. Although the prices of infrared cameras have dropped recently, getting the best value for money and choosing the right camera for wood inspection is a significant challenge. Before choosing an infrared camera, the operator needs to consider several parameters, such as the temperature range, spectral range, thermal sensitivity, resolution, spatial resolution, accuracy, optics and focus, to make an informed decision. This study aims to evaluate the performance of two infrared cameras, a high-end model and a mid-range model, in visual wood damage detection. For this purpose, samples of different wood species with induced damage were observed using active thermography. Our results suggest that, for technical purposes such as qualitative studies, resolution and thermal sensitivity may be more important parameters than accuracy. The results achieved are an important contribution when deciding which infrared camera to purchase

Performance Evaluation Tests and Technical Relevant Parameters of Infrared Cameras for Contactless Wood Inspection

The spread of infrared thermography technology is partly due to the development and commercialisation of increasingly cheap and user-friendly infrared cameras and the minimal instrumentation required to use them. Even though infrared camera prices have dropped dramatically in recent years, getting the best value for money and choosing the right camera is a major challenge. Several parameters need to be considered before choosing an infrared camera, such as the temperature range, spectral range, thermal sensitivity, resolution, spatial resolution, accuracy, optics, and focus.The aim of this study is to evaluate the performance of two infrared cameras, a high-end model and a mid-range model, in visual wood damage detection. The results show that, for qualitative purposes, thermal sensitivity and resolution are more crucial than accuracy. The results obtained are an important contribution to the decision-making process on which IR camera to buy.

Grey relation analysis of 4S service pilot in high-end equipment manufacturing industry

Servitization has a significant impact on the upgrading and reform of the equipment manufacturing industry. From the perspective of application of high-end servitization theory in business practice of equipment manufacturing industry, based on the review of relevant literature, this paper analyzes the concept of integration delay strategy mechanism of cooperative production between enterprises and customers, and thus constructs the theoretical model framework of 4S service pilot high-end equipment manufacturing product-customer interaction experience. With the Liaoning equipment manufacturing industry as a case for quantitative analysis, the feasibility of using delay strategy in the 4S service pilot program is demonstrated, and the three-stage development plan of Liaoning 4S service pilot is outlined. The results show that: At present, in the trend of servitization of China’s equipment manufacturing enterprises, 4S service pilot high-end manufacturing product model enables equipment manufacturing enterprises to delay production time and produce according to customer orders, improve service efficiency and optimize resource allocation, and help enterprises to obtain new exclusive competitive advantages.

Vehicle Semi-active Suspension Control with Cloud-based Road Information

Adaptive suspension control considering passenger comfort and stability of the vehicle has been researched intensively, thus several automotive companies already apply these technologies in their high-end models. Most of these systems react to the instantaneous effects of road irregularities, however, some expensive camera-based systems adapting the suspension in coherence with upcoming road conditions have already been introduced. Thereby, using oncoming road information the performance of adaptive suspension systems can be enhanced significantly. The emerging technology of cloud computing enables several promising features for road vehicles, one of which may be the implementation of an adaptive semi-active suspension system using historic road information gathered in the cloud database. The main novelty of the paper is the developed semi-active suspension control method in which Vehicle-to-Cloud-to-Vehicle technology serves as the basis for the road adaptation capabilities of the suspension system. The semi-active suspension control is founded on the Linear Parameter-Varying framework. The operation of the presented system is validated by a real data simulation in TruckSim simulation environment.

Global oscillatory modes in high-end climate modeling and reanalyses

Interannual oscillatory modes, atmospheric and oceanic, are present in several large regions of the globe. We examine here low-frequency variability (LFV) over the entire globe in the Community Earth System Model (CESM) and in the NCEP-NCAR and ECMWF ERA5 reanalyses. Multichannel singular spectrum analysis (MSSA) is applied to these three datasets. In the fully coupled CESM1.1 model, with its resolution of 0.1 times 0.1 degrees in the ocean and 0.25 times 0.25 degrees in the atmosphere, the fields analyzed are surface temperatures, sea level pressures and the 200-hPa geopotential. The simulation is 100-year long and the last 66 yr are used in the analysis. The two statistically significant periodicities in this IPCC-class model are 11 and 3.4 year. In the NCEP-NCAR reanalysis, the fields of sea level pressure and of 200-hPa geopotential are analyzed at the available resolution of 2.5 times 2.5 degrees over the 68-years interval 1949–2016. Oscillations with periods of 12 and 3.6 years are found to be statistically significant in this dataset. In the ECMWF ERA5 reanalysis, the 200-hPa geopotential field was analyzed at its resolution of 0.25 times 0.25 degrees over the 71-years interval 1950–2020. Oscillations with periods of 10 and 3.6 years are found to be statistically significant in this third dataset. The spatio-temporal patterns of the oscillations in the three datasets are quite similar. The spatial pattern of these global oscillations over the North Pacific and North Atlantic resemble the Pacific Decadal Oscillation and the LFV found in the Gulf Stream region and Labrador Sea, respectively. We speculate that such regional oscillations are synchronized over the globe, thus yielding the global oscillatory modes found herein, and discuss the potential role of the 11-year solar-irradiance cycle in this synchronization. The robustness of the two global modes, with their 10–12 and 3.4–3.6 years periodicities, also suggests potential contributions to predictability at 1–3 years horizons.

The Convolution Addressing the Conundrum of Liability and Privacy in the Age of Autonomous Vehicles

The Automotive Industry has registered an impeccable growth rate since the adoption of autonomous vehicles by vehicle manufacturers in their high-end models. These fully autonomous vehicles are poised to replace the traditional human driver. Hence, the whole set of laws defining liability in the event of an accident involving a vehicle have to be reformed. An autonomous vehicle being sued in lieu of a human driver, would be impractical. With the accidents involving autonomous vehicles increasing, newly minted laws like that of Michigan Harbor Lacunas are forming to address the question of liability and as a consequence of which the innocent (the manufacturer in so many cases) is held absolutely liable, despite his pleading defense. Such a harsh stance is unhealthy for the development of technology. Apart from the conundrum surrounding liability there are other dimensions which are equally unaddressed when it comes to automation. These autonomous vehicles rely on data, thereby adding to the vulnerability of protection of an individual’s privacy. These brimming chaos are likely to hamper the aggrandizement of technology and subsequent protection of commercial interests.This Article is an attempt to comprehensively analyze the uncertainty surrounding the questions of liability and privacy protection for autonomous vehicles. It takes into account the technology friendly interpretation of law, which will balance the diametrically opposite variables. It draws the laws from the existing set of principles available. Further, it proposes a new framework eliminate obscurity and concludes on a positive note with recommendations which are likely to accentuate the effectiveness of the current laws and lay down a steppingstone for the future development of laws.

Are limitations of advanced vehicle technologies described consistently for different vehicle models: An examination for Adaptive Cruise Control

Vehicle manufacturers are increasingly offering increasingly sophisticated types of Advanced Driver Assistance Systems (ADS) in late model year vehicles, not just in higher end models but even in e...

Time and Area Optimized Testing of Automotive ICs

As cars become increasingly computerized and their safety functions evolve rapidly, the number of complex safety-critical components deployed in advanced driver assistance systems or autonomous vehicles is rising dramatically with high-end models containing hundreds of embedded microcontrollers. These integrated circuits must adhere to stringent requirements for high quality and long-term reliability driven by functional safety standards. This requires test solutions that address challenges posed by automotive systems. This article presents a scan-based test scheme optimizing test time and area overhead during manufacturing and in-system test of automotive electronics. The proposed scheme deploys observation test points that capture the faulty effects in every shift cycle into separate observation scan chains. To reduce area overhead, the scheme enables the sharing of flip-flops among control points. It is also shown how test points enhance test coverage (TC) in the presence of cascaded clock gaters. Finally, processing challenges when fault simulating every scan shift cycle to determine TC are addressed. Experimental results obtained for contemporary automotive designs and reported herein show significant improvements in test quality over traditional solutions.

Simplification of the Model of Piezoelectric Actuator Control Based on Preliminary Measurements

This article describes a mathematical model simplification, designed to automate the iterative process of non-circular drilling with a precise shape. This model has been optimized for systems that already have experimental data for processing and analysis. Additionally, using optimization steps, the model can be used for systems with insufficient experimental data with a self-learning opportunity. The high-end model can be used for drilling systems represented as a “black box” without knowing of any parameters of the system. The simplification and assumptions algorithm is based on controlling the input signal for non-circular drilling in the cylinders of internal combustion engines using a drilling machine controlled by 8 piezoelectric actuators. The total dynamics of this system is unknown and consists of the dynamics of electrical converters, piezo-kinematics, and mechanics. Simplification is carried out starting from the methods of diacoptics for a complex system with different process-flow rates, and ending with one or the sum of linear models valid for a given system of assumptions.