Electrical Manufacturers Research Articles

Developing electric vehicles in China and the United States: Revisiting debates on industrial strategy

AbstractMotivationStrategies to develop manufacturing industry are the subject of lively debate over whether to follow or defy national comparative advantage. Electric vehicles (EVs), a major change for automobile manufacturers, are no exception.Despite the US government's promotion of global integration to activate the semi‐invisible hand of market forces, neither traditional Detroit automakers nor new firms, even with government grants or loans, were able to launch EVs on the world market promptly, with the notable exception of Tesla. In China, the government helped dozens of domestic electric vehicle manufacturers enter the market through formidable government subsidies. However, none of China's manufacturers, other than Wuling, were able to surpass Tesla in sales in China.The rapid growth of Tesla and Wuling without relying heavily on government protection and subsidies raises the question of whether their success can be attributed to other forms of state intervention.PurposeWhat policies and strategies enable manufacturers to develop and market a new technology, such as EVs? What can we learn by comparing the experiences of US and Chinese vehicle manufacturers?We consider these questions and what the implications are for debates about industrial development strategy.Methods and approachWe compare four carmaking firms—GM, Tesla, BYD, and Wuling—their business strategies and their interactions with the US and Chinese states. We draw on company reports, government documents, and press reports.FindingsBoth China and the US employed semi‐developmentalist, semi‐neoliberal policies to promote the manufacture of EVs. The US subsidized research and development in its automobile industry and provided incentives to consumers. It has subsequently moved to lending to the most promising firms for EV production. China, in contrast, has selectively subsidized EV firms all the way from development to marketing.Subsidies from the US government have been steady: they are expected to stay this way in the near term. However, the fastest‐growing carmakers have used outward foreign direct investment to gain competitive advantage. China's subsidies, on the other hand, have been unstable: linked to the performance of the target firms. The higher the firm's profit, the lower the subsidies and vice versa. China has been careful with subsidies to prevent rent seeking and moral hazard.Neither following nor defying comparative advantage explains the strategies followed by the four firms: comparative advantage considerations have been tempered by the possibilities of foreign investment.Policy implicationsThe results imply that traditional developmental strategies have resorted to inward foreign direct investment in high‐income countries as a means to learn technologies and outward foreign direct investment in low‐ and medium‐income countries as a way to reduce production costs, but have missed the comparative advantage of outward and inward foreign direct investment, and strategic mixes of these, when developing and diffusing radical innovation like EVs.

Perbaikan Nilai Overall Equipment Effectiveness dengan Metode Total Productive Maintenance pada PT. Electric Vehicle Trimotorindo

This research was conducted to increase the Overall Equipment Effectiveness (OEE) value at PT Electric Vehicle Trimotorindo, which is an electric vehicle manufacturing company. The main problem faced by the company is the decline in OEE value every month due to lack of machine maintenance and deterioration in production quality. The method used in this study is Total Productive Maintenance (TPM), which involves identifying the factors that cause production losses through the analysis of Six Big Losses. The results show that the OEE value has increased from 78.61% to 80.36% after improvements through TPM, especially in increasing the quality rate from 88.48% to 92.23%. The conclusion of this study is that the application of TPM can improve the effectiveness of machine use and production quality, which ultimately contributes to the improvement of the company's productivity.

An Introduction to Lagrange Multipliers: Theory and Applications in Economics

The purpose of this paper is to explore the basic applications of the Lagrange multiplier method in economics and to help beginners build their understanding of this mathematical tool. Tesla Inc. is used as a case study to examine how it maximizes profits by optimizing pricing and marketing expenses under given market conditions and constraints. The context of the study includes the importance of maintaining Tesla’s leadership position as the world’s leading electric car manufacturer in a competitive market. In this paper, the Lagrange multiplier method is used to incorporate specific market share and marketing expense constraints into the profit function and to find the extreme values by constructing the Lagrange function and solving for the derivatives. However, the results of the study show that the solutions obtained are extreme minima rather than the expected maxima. This result highlights the possible limitations of the Lagrange multiplier method in economic optimization problems. Nonetheless, this paper provides valuable lessons for understanding and applying the Lagrange multiplier method and points the way for further research on the application of optimization methods in economic decision making.

A self-organizing map clustering adaptive artificial neural network model for analysis critical success factors in different phases of MTO projects case study: electrical equipment manufacturer and supplier in Iran

PurposeThe purpose of this paper is to investigate the benefit of critical success factors (CSFs) clustering in different phases of make-to-order (MTO) projects and develop standards for management.Design/methodology/approachThis study is based on a questionnaire survey. First of all, collecting data by structured interviews, relying on a questionnaire and second from leader contractors who are active in the engineering and steel industry (in Iran). So, the requirements and objective of the research are presented to the top management of MTO projects to gain their support in data collection. Then 20 CSFs were identified by the literature review so a questionnaire survey was prepared for the CSFs assessment and interview with the experts. Finally analyzing the importance and performance of CSFs in project phases and cluster them in different project phases with self-organizing map as one of the artificial neural network (ANN) approaches due to high predictive accuracy. Review the research result with the top management of MTO project and examine the results obtained from neural networks and validation indices.FindingsCluster analysis shows that the implementation phase is the most important stage in MTO organizations and the other phases like feasibility and start-up, design and planning, delivery and end-phase should be also considered as effective phases in determining the level of organization performance. Different industries with additional data at different periodic times will verify the result. Furthermore, testing the other ANN model will improve risk analysis and could shift this classification approach to a regression type.Research limitations/implicationsThe main limitation of the research is related to the sample. Research findings are limited to the time of data collection so validity is limited to the mentioned time. Different industries with additional data will verify the result. Furthermore, testing different ANN models such as K-MEANS, non-negative matrix factorization (NMF) analyses will improve risk analysis and could meet different classification results to find gaps.Practical implicationsIn this paper, CSF and project phase dimensions are viewed together which is necessary to meet better results for simplifying social and economic benefits. Merge the new findings and latest technologies could prepare the best results and enable managers to create a better framework or implement key factors for minimizing waste.Originality/valueThis paper moves the definition of MTO organizations beyond measuring cost, complexity and financial variables by clustering CSFs in different phases of projects. So, the results enable managers to use this concept in their daily production to minimize waste and could be implemented to efficiently choose factors.

Performance evaluation of a small-animal PET scanner with 213 mm axis using NEMA NU 4-2008.

Long-axis positron emission tomography (PET) has emerged as one of the recent research directions in PET due to its ability to significantly enhance sensitivity and counting performance for low-dose imaging, rapid imaging, and whole-body dynamicimaging. The PET system presented in this study is a long-axis animal PET based on lutetium-yttrium orthosilicate and silicon photomultiplier, designed for whole-body imaging in rats. It features a diameter of 143 mm and an axial length of 213.3 mm. This study evaluated the performance of this PET system in accordance with the National Electrical Manufacturers Association (NEMA) NU 4-2008standards. The performance evaluation was conducted according to the NEMA NU 4-2008 standards in terms of spatial resolution, sensitivity, counting rate performance, scatter fraction (SF) and image quality. In addition, a rat imaging study was conducted to assess the imaging capability of this PETsystem. The average energy resolution of the PET system was 12.87%, the average coincidence timing resolution was 751 ps. The FWHM of spatial resolution reconstructed by filtered back projection and 3D-OSEM-PSF algorithm at 5 mm radial offset from the axial center were 1.65 and 0.88 mm. The peak absolute sensitivity measured by a point source at the center of the field of view was evaluated as 6.71% (361-661keV) and 10.31% (250-750 keV). For the mouse-like phantom, the SF was 11.0% and the peak noise equivalent counting rate (NECR) was 1193 kcps at 94.2 MBq (2.54 mCi). For the rat-like phantom, the SF was 26.8% and the NECR was 682.5 kcps at 78.6 MBq (2.12 mCi). The performance measurement results demonstrate that this PET system exhibits high sensitivity and count rate performance, making it potential for high-quality whole-body dynamic imaging ofrats.

Sharing channel choices for electric vehicle battery manufacturers when considering range anxiety among heterogeneous consumers

PurposeThis study aims to investigate the optimal pricing decisions and shared channel strategy selection of battery manufacturers considering heterogeneous consumers' range anxiety.Design/methodology/approachAmidst the rapid growth of the electric vehicle sector, countries are promoting upgrades in the automotive industry. However, insufficient driving range causes consumer range anxiety. The study utilizes the Stackelberg game model to assess how range anxiety influences battery manufacturers' pricing and channel strategy decisions across three strategies.FindingsWe find that electric vehicle battery manufacturers' decisions to cooperate with third-party sharing platforms (TPSPs) are primarily influenced by fixed costs and consumer range anxiety levels. As range anxiety increases, the cost threshold for joining shared channels rises, reducing cooperation likelihood. However, considering diverse consumer needs, especially a higher proportion of leisure-oriented consumers, increases the likelihood of cooperation. Furthermore, higher battery quality makes direct participation in shared channels more probable.Originality/valueIn the electric vehicle industry, range anxiety is a significant concern. While existing literature focuses on its impact on consumer behavior and charging infrastructure, this study delves into battery manufacturers' strategic responses, offering insights into channel options and pricing strategies amidst diverse consumer segments.

How Does Innovation-Collaboration Network Structure Influence Regional Economic Resilience?

This paper examines whether different structures of co-patenting networks affect regional economic adaptation and adaptability in divergent ways. Adaptation differentiates from adaptability by recovering in a pre-shock growth path, while adaptability entails forging a new growth path. Focusing on computer, electronic, and electrical equipment manufacturing industries in U.S. metropolitan and micropolitan areas from 1990 to 2012, the study reveals that complete networks, characterized by closely connected nodes, promote adaptation but weaken adaptability. In contrast, coalitional networks, featuring loosely connected subgroups, enhance adaptability but hurt adaptation. The study contributes to regional economic resilience literature by empirically demonstrating the trade-off relationship between adaptation and adaptability from network structures’ perspective. Practically, the study helps policy makers to effectively allocate stimuli, such as grants and tax incentives, to develop targeted co-patenting networks to improve adaptation or adaptability.

El auge del coche eléctrico en China y su impacto en la Unión Europea

Rationale China’s electric vehicle sector has recently aroused considerable interest thanks to its rapid growth and current dominance of the global market. Given the importance of the automotive sector in Spain and the European Union (EU), and the recent introduction of tariffs, it is worth exploring the factors behind this rise. Takeaways •Battery electric vehicle (BEV) market penetration in the EU has grown notably in recent years: in 2023 BEVs accounted for 15% of all vehicles sold (5.4% in Spain), a figure well above the 1.9% recorded in 2019 (0.7% in Spain). •China has secured its status as the world’s leading electric vehicle manufacturer and exporter, its output proving particularly popular in the European market. As a consequence, the market share of BEVs made in China rose from 0.4% of new BEV registrations in 2019 to 20% in 2023. •The success of Chinese BEV exports rests on lower manufacturing costs, thanks largely to China’s control over the supply chain, government support policies at various stages of production and the country’s early embrace of electric vehicles.

Effect of metallic materials on magnetic resonance image uniformity: a quantitative experimental study.

To assess quantitatively the effect of metallic materials on MR image uniformity using a standardized method. Six types of 1cm cubic metallic materials (i.e., Au, Ag, Al, Au-Ag-Pd alloy, Ti, and Co-Cr alloy) embedded in a glass phantom filled were examined and compared with no metal condition inserted as a reference. The phantom was scanned five times under each condition using a 1.5-T MR superconducting magnet scanner with an 8-channel phased-array brain coil and head and neck coil. For each examination, the phantom was scanned in three planes: axial, coronal, and sagittal using T1-weighted spin echo (SE) and gradient echo (GRE) sequences in accordance with the American Society for Testing and Materials (ASTM) F2119-07 standard. Image uniformity was assessed using the non-uniformity index (NUI), which was developed by the National Electrical Manufacturers Association (NEMA), as an appropriate standardized measure for investigating magnetic field uniformity. T1-GRE images with Co-Cr typically elicited the lowest uniformity, followed by T1-GRE images with Ti, while all other metallic materials did not affect image uniformity. In particular, T1-GRE images with Co-Cr showed significantly higher NUI values as far as 6.6cm at maximum equivalent to 11 slices centering around it in comparison with the measurement uncertainty from images without metallic materials. We found that MR image uniformity was influenced by the scanning sequence and coil type when Co-Cr and Ti were present. It is assumed that the image non-uniformity in Co-Cr and Ti is caused by their high magnetic susceptibility.

Generation Y and the Shift to Electric Vehicles in Indonesia: Exploring Key Drivers and Barriers

Purpose: Compared With other Asian countries, the usage rate of electric vehicles in Indonesia remains slow owing to a lack of public interest. This paper explores some significant factors that affect the interest of electric vehicles for Gen Y EV products, including environmental concerns and individual consequences. Research Methodology: We extend the previous study by adding other variables, including individual and environmental consequences. Data from 446 respondents were collected through a judgmental sampling procedure and analyzed using partial least squares structural equation Modeling. Results: The results showed that attitudes towards the five dimensions of the UTAUT-2 model significantly influenced intention to purchase. However, attitude did not mediate the relationship between habit and purchase intention. On the other hand, attitude mediation vastly influences not only the association between individual consequences and purchase intention, but also that between environmental concerns and purchase intention. On the other hand, subjective norms also have a positive influence on purchase intention, while perceived risk is not considered to affect the purchasing decisions of Generation Y. Recommendation: This study recommends that both electric vehicle manufacturers and the Indonesian government improve infrastructure and raise public awareness to increase interest in electric vehicles.

A representation learning-based approach to enhancing manufacturing quality for low-voltage electrical products

In low-voltage electrical product manufacturing, resolving quality issues is heavily reliant on engineering experience, and can be time-consuming and error-prone. Through quality management systems, a large number of historical defect cases can be consolidated for analysis along with relevant causes. However, these defect descriptions are often casually described with a mix of Chinese and English language, containing domain-specific terms. Additionally, defect product features have varieties and complex relationships. Therefore, historical defect cases have not been effectively utilized to support manufacturing quality issues. To address this challenge, this study proposes a representation learning-based approach to enhance manufacturing quality. Key research contributions include: (1) A two-stage word embedding technique based on the pre-trained language model. First, TSDAE is utilized for unsupervised pre-training on a large amount of unlabeled data. Then, Sentence-BERT is utilized for fine-tuning on a small set of labeled similar sentence pairs. This process yields a pre-trained language model specific to low-voltage electrical product defects. (2) NSHPSAGE graph embedding model based on the constructed product feature knowledge graph. We select more valuable neighboring nodes during sampling and explore different aggregation functions to enhance graph embedding performance. This model effectively aggregates product feature information into “Defect_Case” nodes, yielding graph embedding vectors. The model exhibits good Weighted-Precision and Weighted-Recall with a short training duration, and it can handle new nodes, addressing the issue of heterogeneous graph embedding. (3) A defect case recommendation technique that fuses word embedding and graph embedding. We use Multi-Head Attention Fusion in the late-fusion to obtain defect case vectors. This approach comprehensively considers defect description semantic knowledge and complex product feature relationships, enabling accurate defect case recommendation with the prototype system.

Optimization of Image Quality in Pelvis Lymphoscintigraphy SPECT/CT Using Discovery NM/CT 670

Abstract Aim A lymphoscintigraphy is a crucial diagnostic tool for visualizing lymph nodes. This scan plays a significant role in determining the treatment and recovery plan for the patients. Due to the small lymph node size, obtaining high-quality images is important to prevent inaccurate results. We aimed to identify the most effective method for enhancing image quality through postprocessing techniques and altering the image reconstruction process. Methods Two data sets were utilized in this study. First, National Electrical Manufacturers Association body phantom was filled with [99mTc]Tc-pertechnetate and prepared with and without any activity in the background of the body. Second, the images of 50 patients who underwent single-photon emission computed tomography/computed tomography imaging received [99mTc]Tc-phytate were collected. Discovery 670 GE gamma camera was used for imaging. Preprocessing of all images was performed by Xeleris and 3DSlicer 5.2.2 software was used for quantification. The effect of image reconstruction parameters such as resolution recovery (RR) algorithm, iteration, subsets, cutoff, and power in Butterworth filter, and full width at half maximum (FWHM) of Gaussian filter was assessed. The image quality index was determined based on contrast-to-noise ratio (CNR), contrast, and coefficient of variation. Results The utilization of the RR algorithm showed notable improvements equal to 74, 35, and 38% of CNR, contrast, and noise reduction, respectively. Significant differences were observed in subiteration of 40 to 112 (p-value < 0.05). The alteration of effective parameters in both smoothing filters yielded statistically significant results, leading to enhanced detectability, reduced noise, and improved contrast simultaneously. Optimum results in terms of noise reduction and CNR were achieved with subiteration (i × s) 4 × 12 using a Gaussian filter with FWHM of 4 or Butterworth filter with power of 10 and cutoff of 1. The highest contrast was observed at subiteration 40 using the Butterworth filter with cutoff of 0.5 and power of 5 or Gaussian filter with 2 mm FWHM. Qualitative analysis by two nuclear medicine specialists validated the quantified image quality. Conclusion The reconstruction setting involving subiteration 48 with the Butterworth filter using cutoff of 1 and power of 10 or 4 mm FWHM of Gaussian filter produced the highest quality images.

Impact of upgrading from a 25-cm to a 30-cm z-axis field of view digital PET/CT in a pediatric hospital

BackgroundIncreased positron emission tomography (PET) scanner z-axis coverage provides an opportunity in pediatrics to reduce dose, anesthesia, or repeat scans due to motion.ObjectiveRecently, our digital PET scanner was upgraded from a 25-cm to a 30-cm z-axis coverage. We compare the two systems through National Electrical Manufacturing Association (NEMA) testing and evaluation of paired images from patients scanned on both systems.Materials and methodsNEMA testing and a retrospective review of pediatric patients who underwent clinically indicated 18F-fluorodeoxyglucose (FDG) PET computed tomography (PET/CT) on both systems with unchanged acquisition parameters were performed. Image quality was assessed with liver signal to noise ratio (SNR-liver) and contrast to noise ratio (CNR) in the thigh muscle and liver with results compared with an unpaired t-test. Three readers independently reviewed paired (25 cm and 30 cm) images from the same patient, blinded to scanner configuration.ResultsExpansion to 30 cm increased system sensitivity to 29.8% (23.4 cps/kBq to 30.4 cps/kBq). Seventeen patients (6 male/11 female, median age 12.5 (IQR 8.3–15.0) years, median weight 53.7 (IQR 34.2–68.7) kg) were included. SNR-liver and CNR increased by 35.1% (IQR 19.0–48.4%) and 43.1% (IQR 6.2–50.2%) (P-value <0.001), respectively. All readers preferred images from the 30-cm configuration. A median of 1 (IQR 1–1) for fewer bed positions was required with the 30-cm configuration allowing a median of 91 (IQR 47–136) s for shorter scans.ConclusionIncreasing z-axis coverage from 25 to 30 cm on a current-generation digital PET scanner significantly improved PET system performance and patient image quality, and reduced scan duration.

Study on the Selection of Recycling Strategies for the Echelon Utilization of Electric Vehicle Batteries under the Carbon Trading Policy

Global climate change has prompted all sectors of society to take urgent action to reduce carbon emissions. Electric vehicles are the key to low-carbon transportation transformation, but their popularity has led to difficulties in disposing of used batteries. Improper handling will pollute the environment and violate the original goal of promoting low-carbon practices. Therefore, it is crucial to establish a sustainable battery-recycling and disposal system. This study uniquely incorporates the concept of battery echelon utilization into its analytical framework using a Stackelberg game model, exploring the equilibrium strategies for stakeholders in a closed-loop supply chain under carbon emission constraints. We analyzed the impact of multiple factors in the recycling process, as well as the influence of digital technology, on enterprise pricing, recycling efficiency, and the choice of recycling channels. The study found that the market pricing of batteries and electric vehicles is not influenced by recycling participants, but is instead related to the application of digital technology. Numerical simulations further reveal that the battery’s echelon utilization rate and carbon emission limit policies jointly motivate enterprises to be more proactive in recycling. In the joint recycling model, battery suppliers can achieve more substantial profit growth compared to electric vehicle manufacturers, providing new insights and directions for innovation and the development of collaborative models within the supply chain.

Research regarding the simulation of the autonomy for the electric vehicles in the case of the WLTC test cycle

Abstract In current mainstream research, energy consumption and autonomy are just a few of the the major objectives anticipated for electric road vehicles. The production of electric vehicles is continuously expanding, offering to the market a large variety of constructive variants in order to satisfy the requirements for their exploitation. Also, in the current energy context, it is expected from the electric car manufacturers, to deliver high quality models which can be characterized as the actual alternatives to actual existing solutions equipped with an internal combustion engine. Under these circumstances, the continuous research it is a high priority for everyone electric vehicle producers, where simulation on the computer is basically not absent as a go-between step prior to the validation of the final draft proposals. According to these assumptions, in the first part of the article you will find the AMESim simulation platform points, where it describes the model made with it and the simulated test cycle. In the second part of the article, as a consequence of the simulation of the experimental electric vehicle, are highlighted some aspects of the autonomy behaviour in the case of simulation on the World-wide harmonized Light duty Test Cycle (WLTC), for all four speed zones specific to it.

Exploring Factors Influencing Electric Vehicle Purchase Intentions through an Extended Technology Acceptance Model

Recently, with climate deterioration and environmental pollution, consumers are becoming more and more aware of the use of sustainable energy. In particular, the demand for electric vehicles that use sustainable energy is also increasing. In addition, due to the simple driving principle of pure electric vehicles, many electric vehicles developed by electronics companies are continuously being launched. Electric vehicles not only use renewable energy to protect the environment but also save on various usage expenses, so they are expected to become the main products in the mobile travel equipment market in the future. This study aims to explore the impact of product design dimensions on electric vehicle (EV) purchase intentions, provide a theoretical basis for companies’ differentiation strategies, and reflect the impact of product design on purchase intention. This study uses Davis’s TAM combined with environmental awareness (EA) for analysis; an online survey was conducted on Chinese (n = 468) and Korean (n = 409) consumers, both male and female, aged 20–60 years and above. We found that, for Chinese consumers, the aesthetic and symbolic dimensions do not affect perceived usefulness and perceived ease of use, but they do affect environmental awareness, while the functional dimension affects not only perceived ease of use and usefulness but also environmental awareness. For Korean consumers, the aesthetic, functional, and symbolic dimensions all affect perceived ease of use and environmental awareness, but perceived usefulness is only affected by aesthetics and environmental awareness. Through simulation analysis, the results show that perceived ease of use, usefulness, and environmental awareness all directly affect purchase intentions. Perceived ease of use and environmental awareness are particularly important for Chinese consumers, while Korean consumers pay more attention to the test drive experience and environmental awareness. The results show that electric vehicle manufacturers should develop new technologies for the Chinese market to attract consumers, while in the Korean market, they should improve perceived usefulness through test drives and pay attention to environmental awareness. Specific statistical data show that both Chinese and Korean consumers assign importance to the impact of environmental awareness on purchase intention, proving the importance of environmental awareness. The results of this study will be of great reference value to electric vehicle manufacturers, policymakers, and consumer behavior researchers, helping them to better understand the role of product design in improving the market acceptance of electric vehicles.

Research on Tesla's Pricing Strategy in Chinese Market

As a leading global electric vehicle manufacturer, Tesla's performance in the Chinese market has a significant impact on the entire industry and market. The paper aims to analyze and evaluate Tesla's market pricing strategy in the Chinese market through SWOT analysis. Based on the analysis of pricing strategies, the paper also explores the impact of Tesla on the Chinese automotive economy market. Finally, the paper proposes some suggestions to address the challenges of future development and market expansion in the Chinese automotive market.

Sustainable Performance of Industrialised Building Systems in the Construction Phase

The Industrialised Building System (IBS) is a construction method where components are manufactured in controlled environments, either on-site or offsite, before being assembled into construction works. Over the past several decades, it has garnered growing interest as a method to promote sustainable building. This study identified sustainable indicators through literature reviews, extracting sixteen indicators for a sustainability evaluation. A survey was conducted among developers, designers, civil and structure (C&amp;S) consultants, mechanical and electrical (M&amp;E) consultants, manufacturers, and contractors in North Malaysia, focusing on Kedah state, to identify their perceptions on the sustainable indicator performance of IBS construction. The participants had experience in both IBS and conventional construction. The data collected from the questionnaires were analysed for the mean and Relative Importance Index (RII). The results revealed significant changes in IBS construction compared with conventional construction across all indicators. The top three indicators were reducing the amount of formwork, labour availability, and reducing site disruption. Next, the analysis of the within-group comparison using Intra-class Correlation (ICC) of the indicators revealed that contractors, developers and manufacturers possessed moderate similarity within the same group of organisations. This research gives an overview of the present perspectives of performance of sustainable indicators across key stakeholders in the Kedah construction sector. This is especially beneficial because IBS has grown in popularity and popularity owing to its ability to enhance the building environment, quality, and productivity.

Comparison between a surface permanent magnet synchronous motor and a segmented stator switched reluctance motor with aluminum windings for light electric traction

Nowadays, light electric vehicles are usually powered by drives with motors that use rare-earth permanent magnets. Nevertheless, due to the problems these materials present, light electric vehicle manufacturers are open to considering other alternative drives free of permanent magnets. This paper raises a comprehensive comparison between a surface permanent magnet synchronous motor and a segmented stator switched reluctance motor with aluminum windings for light electric traction, specifically for a motorcycle similar to the Super Soco TCmax.

FAST (fast analytical simulator of tracer)-PET: an accurate and efficient PET analytical simulation tool

Objective. Simulation of positron emission tomography (PET) images is an essential tool in the development and validation of quantitative imaging workflows and advanced image processing pipelines. Existing Monte Carlo or analytical PET simulators often compromise on either efficiency or accuracy. We aim to develop and validate fast analytical simulator of tracer (FAST)-PET, a novel analytical framework, to simulate PET images accurately and efficiently. Approach. FAST-PET simulates PET images by performing precise forward projection, scatter, and random estimation that match the scanner geometry and statistics. Although the same process should be applicable to other scanner models, we focus on the Siemens Biograph Vision-600 in this work. Calibration and validation of FAST-PET were performed through comparison with an experimental scan of a National Electrical Manufacturers Association (NEMA) Image Quality (IQ) phantom. Further validation was conducted between FAST-PET and Geant4 Application for Tomographic Emission (GATE) quantitatively in clinical image simulations in terms of intensity-based and texture-based features and task-based tumor segmentation. Main results. According to the NEMA IQ phantom simulation, FAST-PET’s simulated images exhibited partial volume effects and noise levels comparable to experimental images, with a relative bias of the recovery coefficient RC within 10% for all spheres and a coefficient of variation for the background region within 6% across various acquisition times. FAST-PET generated clinical PET images exhibit high quantitative accuracy and texture comparable to GATE (correlation coefficients of all features over 0.95) but with ∼100-fold lower computation time. The tumor segmentation masks comparison between both methods exhibited significant overlap and shape similarity with high concordance CCC > 0.97 across measures. Significance. FAST-PET generated PET images with high quantitative accuracy comparable to GATE, making it ideal for applications requiring extensive PET image simulations such as virtual imaging trials, and the development and validation of image processing pipelines.