Vehicle Industry Research Articles

Comparative Analysis of Policy Effect Evaluation of New-energy Vehicle Industry in China and the U.S.

Against fluctuations in the global automotive market, the electric vehicle (EV) industry has demonstrated a positive development trend overall. China has become a leader in battery production and related infrastructure construction, while the United States, though ranking third, also holds an important position. This paper analyzes the effects of government-led policies and market-driven policies on the electric vehicle policies of China and the United States. It explains how the industries and policies of the two countries interact. By analyzing the current state of the industries in both countries and their different policy preferences in terms of fiscal policy, infrastructure allocation, and other dimensions, the following conclusions can be drawn. Firstly, compared to the incoherent central policies and decentralized local policies lacking central authority in the U.S. electric vehicle industry, China's top-down long-term policies lead to a more consistent and efficient development of its electric vehicle industry. This article concludes that China's strong authoritative and consistent policies in the electric vehicle industry play an important role in maintaining its leading position in the global electric vehicle industry.

Rapid diagnosis of power battery faults in new energy vehicles based on improved boosting algorithm and big data

In recent years, the new energy vehicle industry has developed rapidly. A fast diagnostic method based on Boosting and big data is proposed to address the low accuracy and efficiency of fault diagnosis in new energy vehicle power batteries. Boosting is a machine learning technique that combines multiple weak learners into a strong learner. Big data refers to large-scale, complex datasets that exceed traditional data processing capabilities. Firstly, analyze and preprocess the big data uploaded by the battery. Subsequently, the importance of indicators in the data was analyzed using the Random Forest algorithm (RF). Finally, three improved Boosting algorithms were proposed, namely Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting Tree (XGBoost), and Gradient Boosting Decision Tree (CatBoost). The experimental results indicate that the LightGBM model effectively detects anomalies in battery big data. The accuracy values of XGBoost, CatBoost, and LightGBM are 97.84%, 98.57%, and 99.16%, respectively. The recall rates of XGBoost, CatBoost, and LightGBM models are all 1. The F1 values of GBoost, CatBoost, and LightGBM are 0.873, 0.983, and 0.985, respectively. The power battery is the core component of new energy vehicles, and its safety performance directly affects the operational safety of the vehicle. Timely identification and diagnosis of battery faults can effectively reduce potential accidents such as battery overheating and short circuits. Research can achieve real-time monitoring and timely reminders of potential faults. By early detection of issues such as battery overheating and voltage imbalance, this method can effectively reduce the risk of serious safety accidents and improve the overall operational reliability of new energy vehicles during driving.

Analysis of the Transformation of the New Energy Vehicle Industry under the Background of the Digital Economy

Today, the digital economy has become the main theme. The digital economy includes digital industrialization, industrial digitization, digital governance, and data value. In this context, data has become the kinetic energy of factors for economic development. In recent years, China's new energy vehicle industry has risen rapidly. In the 2024 "Global Top 100 Auto Supply Chain", three Chinese enterprises have entered the top 20: CATL, Weichai Group, and Huayu Automotive. This represents the profound accumulation and innovation ability of Chinese component enterprises and shows the indispensable role and status of Chinese enterprises in the global auto supply chain to the world. The development of the new energy vehicle industry has promoted the reconstruction of the auto industry chain, including the production and manufacturing of core components such as batteries, motors, and electronic controls, as well as the development of fields such as intelligent driving and intelligent interconnection. This transformation has not only promoted technological innovation and business model innovation within the industry but also driven the construction and improvement of related infrastructure, such as the construction of charging piles and battery swapping stations, as well as the development of intelligent transportation systems, providing convenience for the popularization and use of new energy vehicles.

Cross-Field Road Markings Detection Based on Inverse Perspective Mapping

With the rapid development of the autonomous vehicles industry, there has been a dramatic proliferation of research concerned with related works, where road markings detection is an important issue. When there is no public open data in a field, we must collect road markings data and label them by ourselves manually, which is huge labor work and takes lots of time. Moreover, object detection often encounters the problem of small object detection. The detection accuracy often decreases when the detection distance increases. This is primarily because distant objects on the road take up few pixels in the image and object scales vary depending on different distances and perspectives. For the sake of solving the issues mentioned above, this paper utilizes a virtual dataset and open dataset to train the object detection model and cross-field testing in the field of Taiwan roads. In order to make the model more robust and stable, the data augmentation method is employed to generate more data. Therefore, the data are increased through the data augmentation method and homography transformation of images in the limited dataset. Additionally, Inverse Perspective Mapping is performed on the input images to transform them into the bird’s eye view, which solves the “small objects at far distance” problem and the “perspective distortion of objects” problem so that the model can clearly recognize the objects on the road. The model testing on the front-view images and bird’s eye view images also shows a remarkable improvement of accuracy by 18.62%.

Modeling and Optimization of Regenerative MacPherson Strut

<div>Throughout the vehicles industry and electrification, vehicle ride comfort, road holding, and fuel/charge economy have always been important considerations for the design and development of shock absorbers. Vehicle suspension is one of the oscillating power dissipation sources in which the undesired mechanical energy is dissipated into heat waste. Therefore, in this study a regenerative MacPherson strut is modeled and validated to investigate the vehicle vertical dynamics performance as well as the harvestable power that can be used to charge batteries or power vehicle electrical loads. The optimal design parameters of the regenerative MacPherson strut (RE.M.S) is obtained by using multi-object genetic algorithm (MOGA) optimization for a better trade-off between regenerated power, ride comfort, and road holding. The results showed that RE.M.S can function as a semi-active shock absorber as change of duty cycle of charging circuit. Furthermore, the optimal selection of the design parameters such as the inclination angle of the MacPherson strut and the external load have a very significant effect to stabilize the level of the harvested regenerated power, ride comfort, and road holding at different driving conditions.</div>

TERMOELEKTRIK GENERATOR DAN FUNGSINYA

This article summarizes and reviews various journals on the performance, applications, and development of Thermoelectric Generators (TEG) that convert temperature differences into electrical energy through the Seebeck effect. The aim of this review is to provide a comprehensive overview of advancements in TEG technology and its potential in enhancing energy efficiency and renewable energy utilization. The methodology includes a literature review of research methods applied in previous studies, including simulations and experiments aimed at improving TEG efficiency. Some studies also integrate TEG with phase change materials (PCM) to harvest energy from ambient temperature fluctuations. The review findings indicate that innovations in TEG materials and design can significantly improve the efficiency and sustainability of this technology. Additionally, this article discusses the applications of TEG in various fields, such as waste heat recovery from industrial processes and vehicles, as well as in wearable devices to harvest energy from body heat. A table presenting research methods and comparisons of previous studies is included to offer a thorough view of current developments in TEG technology. The conclusion of this review is that TEG has significant potential as a solution for waste heat recovery, wearable device applications, and as an efficient renewable energy source. The article also provides recommendations for future research, including the development of new materials and more optimal designs, to address existing challenges and maximize the potential of TEG.

Analysis of the Current Development Status and Problems of New Energy Enterprises: Taking Tesla as an Example

This paper aims to address the current development status and problems of new energy vehicle companies, taking Tesla as an example. The research question is to understand the challenges of low brand awareness and inadequate crisis public relations handling faced by Tesla in emerging markets and second- and third-tier cities. This is important to the academic field because it provides insights into the development and challenges of the new energy vehicle industry. This study adopts a case analysis method, taking Tesla as an example to study the current development status of new energy companies and some related problems, and proposes some countermeasures and suggestions for the problems found. The results show that in some emerging markets and smaller cities, Tesla has limited brand awareness due to less promotion compared with traditional car brands and consumers' trust in traditional brands. In terms of crisis public relations, Tesla's response is sometimes not timely or transparent enough. The solutions proposed include holding more events and developing personalized marketing strategies in these areas, as well as establishing a rapid response mechanism and strengthening communication with consumers and regulators. The impact of this work is to provide Tesla with practical suggestions to improve its brand image and competitiveness, and also provide valuable lessons for other new energy vehicle companies to deal with similar problems.

Market Risk of Lithium Industry Chain—Evidence from Listed Companies

Lithium, a crucial raw material for new energy vehicles, is experiencing significant market price fluctuations due to escalating geopolitical conflicts, periodic mismatches in supply and demand, and increased attention to lithium resources from countries around the world. These factors may adversely affect the development of the new energy vehicle industry. This paper adopts the TVP-VAR-DY model, which measures dynamic spillover effects by allowing for variance changes through the estimation of a stochastic Kalman filter, thereby measuring risk spillover among upstream and downstream firms in the lithium industry chain. We selected 16 listed companies and six regional financial markets as the research sample, with the sample period from 4 July 2018, to 30 June 2023. The main conclusions are as follows: Between 2018 and 2020, the overall risk spillover in the lithium industry chain demonstrated a declining trend, though it experienced a sudden surge in 2020 as a result of the COVID-19 pandemic. This increase was followed by a gradual decline as the global economy improved and market stability was restored, leading to a reduction in risk aversion. Regarding the reception of risk spillovers, upstream firms exhibited a generally consistent level of directional risk spillovers, whereas downstream firms experienced more significant fluctuations. Chinese firms exhibited a higher level of received risk spillovers compared to their international counterparts, with less variation in these spillovers. From the perspective of risk spillover effects, significant variations were observed between firms in both the upstream and downstream markets. Chinese firms exhibited a higher level of risk inflow than international firms, with more pronounced changes in risk spillovers. Upstream enterprises should enhance their market competitiveness to mitigate the adverse effects of economic uncertainty. Downstream enterprises can alleviate the rise in raw material costs resulting from market price fluctuations through strategic cooperation. Additionally, the government should increase the market supply of resources, which will contribute to the establishment of a more robust lithium industry chain system.

Electrical contact with dielectric breakdown of interfacial gap

Abstract Electrical contact is fundamental to almost every aspect of modern industry including the fast-growing electric vehicle industry. In metallic contacts in atmospheric conditions, most of the electrical current passes via the micro-junctions formed between two electrodes. The classic electrical contact theory predicts an infinite current density at the circular contact periphery. In the present work, we explore the influence of the dielectric breakdown of air outside the contact area on the electrical contact interface. Incorporating the discharging boundary condition governed by the modified Paschen law, we develop the numerical model as well as two sets of closed-form solutions for low applied voltage cases where two electrodes are in solid-solid contact and complete separation, respectively. For Hertzian contact, the present work theoretically proves that the ignorance of discharge can lead to a singular current density at the contact periphery and an overestimation of the electrical contact resistance. The current density monotonically increases along the radial direction to a finite value at the contact area periphery and followed by a monotonic drop within the discharge zone. The present study serves as a foundation for the modeling of discharging rough surface electrical contact and sheds light on the machine element surface damages caused by the electrical discharge machining.

Technological innovation, product development, and operational efficiency for new energy vehicle industry: Basis for a synergistic framework

Technological innovation, product development, and operational efficiency for new energy vehicle industry: Basis for a synergistic framework

Investment Value Analysis of Leading Enterprises in the New Energy Vehicle Industry - Taking Li Automobile, XPeng Automobile, and BYD Automobile as Examples

Against the backdrop of rapid development in the emerging industry of new energy vehicles, China has also introduced some new policies to promote the further development of the new energy vehicle industry. Therefore, this measure has enhanced the confidence of investors in investing in the new energy vehicle industry. This article mainly takes Li Automobile, XPeng Automobile, and BYD Automobile, the leading enterprises in China's new energy vehicle industry, as examples to analyze how investors can maximize their investment in the new energy vehicle industry. This article mainly uses the risk indicator Beta in the CAPM model to analyze the risk level of three stocks and uses the DuPont analysis method to analyze the profitability of the three stocks. Finally, it is concluded that BYD Automobile and Li Automobile are relatively valuable investment stocks among these three stocks, while XPeng Automobile needs to further optimize the company's profit structure to achieve strong profitability.

Research And Enlightenment of China's Environmental Protection Policy on The Development of Carbon Finance: A Case Study of The New Energy Vehicle Industry

In recent decades, environmental problems continuously interfering with people's daily lives, and the new energy automobile industry has thus risen among big countries. Despite the rapid development of China's new energy vehicle industry, there are still many problems that need to be solved. By reading and collecting a large number of literatures, this paper comprehensively studies and summarizes a number of papers using the TRIZ theoretical research model, based on the research and analysis of the development status of BYD, a well-known industry in the field of new energy vehicles in China, discusses the methods and shortcomings of China's environmental protection policies to promote the development of carbon finance market in the context of the development of new energy vehicles in China in recent decades. The paper puts forward some feasible solutions to these problems, as well as some inspirations for the future development of China's new energy automobile industry in the carbon financial market.

A Study on The Impact of New Energy Vehicle Subsidy Policies on BYD Company's Financial Performance

In recent years, the domestic economy has grown rapidly, people's living standards have been significantly improved, and cars have become a necessary means of travel for almost every family. However, with the sharp increase in automobile consumption, the harm to the environment is becoming more and more significant, and the green of the global ecological environment continues to pose a great threat, so the new energy vehicle product was born, catering to the theme of green and environmental protection, and has received widespread attention from consumers at home and abroad, and China has also put forward a number of subsidy policies since 2009 to encourage the development of the new energy vehicle industry, as an important breakthrough in China's industrial transformation and upgrading. Therefore, according to field research, the impact of new energy vehicle subsidy policies on the financial performance of car companies is of great significance. This paper attempts to explain the impact of the new energy vehicle subsidy policy on the financial performance of new energy vehicle enterprises over the years, and takes BYD, a leader in today's new energy vehicle companies, as the research object, and analyzes the impact of the subsidy policy from 2016 to 2023 on the financial performance of BYD Group in the same period.

Situational Awareness Errors in Forklift Logistics Operations: A Multiphase Eye-Tracking and Think-Aloud Approach

Background: This study explores forklift operators’ situational awareness (SA) and human errors in logistic operations using a multiphase approach as an innovative methodology. Methods: Ethnography, eye tracking, error taxonomy, and retrospective think-aloud (RTA) were used to study the diverse cognitive, behavioral, and operational aspects affecting SA. After analyzing 566 events across 18 tasks, this research highlighted eye tracking’s potential by offering real-time insights into operator behavior and RTA’s potential as a method for cross-checking the causal factors underlying errors. Results: Critical tasks, like positioning forklifts and lowering pallets, significantly impact incident occurrence, while high-cognitive demand tasks, such as hoisting and identifying pedestrians/obstacles, reduce SA and increase errors. Driving tasks are particularly vulnerable to errors and are the most affected by operator risk generators (ORGs), representing 42% of incident risk events. This study identifies driving, hoisting, and lowering loads as the tasks most influenced by system factors. Limitations include the task difficulty levels, managing physical risk, and training. Future research is suggested in autonomous industrial vehicles and advanced driver assistance systems (ADASs). Conclusions: This study provides valuable insights into how we may improve safety in logistics operations by proposing a multiphase methodology to uncover the patterns of attention, perception, and cognitive errors and their impact on decision-making.

Predicting Success Factors of Electric Vehicle Industry in the Future with Futures Wheel and Text Mining

Predicting Success Factors of Electric Vehicle Industry in the Future with Futures Wheel and Text Mining

Electric airport ferry vehicle scheduling problem for sustainable operation

This study discusses the challenges and solutions surrounding the scheduling of electric airport ferry vehicles (EAFVs) in the aviation industry. With the rise of electric vehicle technology and the push for sustainability, the adoption of EAFVs presents a significant opportunity for reducing emissions in airport ground transportation. However, scheduling EAFVs involves integrated considerations of operational scheduling and charging scheduling. To address these challenges, this study proposes a mixed-integer nonlinear programming (MINLP) model aimed at minimizing total costs associated with EAFV utilization while adhering to flight time window constraints and ensuring electric power availability. Furthermore, we transform the proposed MINLP model into a solvable mixed-integer linear programming model, facilitating its solution using off-the-shelf commercial solvers. To meet the requirements of the large international airport, we propose a stabilization approach for solving the large-scale instances. Finally, we further analyze the influence of crucial parameters, including the number of EAFVs deployed, the number of flights for servicing, and the charging power of charging facilities. Managerial policies are proposed for the airport managers based on the findings. This research addresses both theoretical and practical aspects, offering valuable policy recommendations for the effective EAFV management and providing a foundation for further exploration in EAFV scheduling. The findings contribute to the advancement of sustainable transportation practices in the aviation industry.

AI-Driven Circular Economy of Enhancing Sustainability and Efficiency in Industrial Operations

This study investigates integrating circular economy principles—such as closed-loop systems and economic decoupling—into industrial sectors, including refining, clean energy, and electric vehicles. The primary objective is to quantify the impact of circular practices on resource efficiency and environmental sustainability. A mixed-methods approach combines qualitative case studies with quantitative modelling using the Brazilian Land-Use Model for Energy Scenarios (BLUES) and Autoregressive Integrated Moving Average (ARIMA). These models project long-term trends in emissions reduction and resource optimization. Significant findings include a 20–25% reduction in waste production and an improvement in recycling efficiency from 50% to 83% over a decade. Predictive models demonstrated high accuracy, with less than a 5% deviation from actual performance metrics, supported by error metrics such as Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). Statistical validations confirm the reliability of these forecasts. The study highlights the potential for circular economy practices to reduce reliance on virgin materials and lower carbon emissions while emphasizing the critical role of policy support and technological innovation. This integrated approach offers actionable insights for industries seeking sustainable growth, providing a robust framework for future resource efficiency and environmental management applications.

EXPLORING ELECTROMECHANICAL SYSTEMS IN THE DEVELOPMENT OF NEXT-GENERATION ELECTRIC POWERTRAINS

In the rapidly evolving electric vehicle industry, the study of electromechanical systems in next-generation electric powertrains is of particular relevance. This is driven by the need to enhance energy efficiency, reduce costs, and improve the reliability of vehicles. The article examines the role of innovative materials, advanced design methods, and control algorithms in creating high-efficiency and reliable electric powertrains. Specifically, the impact of nanomaterials such as graphene and carbon nanotubes on reducing motor weight and increasing heat dissipation is analyzed, contributing to improved efficiency and extended driving range. The adoption of additive manufacturing (3D printing) and digital twins accelerates prototyping and component optimization in electric powertrains. Adaptive control algorithms ensure optimal system performance in real-time, enhancing overall efficiency and reliability. Research methods included the analysis of modern materials and technologies, prototyping using additive manufacturing, and the implementation of predictive and adaptive control algorithms. The results demonstrate significant improvements in the performance of electric powertrains due to the use of innovative materials and cutting-edge design technologies. Conclusions confirm that the application of advanced materials and adaptive control algorithms is critical for ensuring the sustainable development of the electric vehicle industry. Future research prospects focus on further refining materials and technologies to enhance scalability and reduce production costs, making electric powertrains more accessible and efficient.

Blockchain’s role in operation strategy of power battery closed-loop supply chain

With the rapid development of the electric vehicle industry, the issue of recycling retired power batteries is becoming increasingly prominent. Considering the adoption of blockchain technology to enhance information traceability for retired power batteries, we construct three closed-loop supply chain decision-making models: a supply chain that does not adopt blockchain technology, a manufacturing enterprise that independently bears the input cost of blockchain technology, and a scenario which both manufacturing and selling enterprises jointly bear the blockchain technology input costs. Through the comparative analysis of the equilibrium solutions of these models, including the profits of each supply chain member, consumer surplus, environmental impact, and social welfare, it is concluded that the level of information traceability increases with the increase of the blockchain technology input cost-sharing ratio λ by the selling enterprise. However, there is a threshold for λ and λ cannot be infinitely increased. The profits of both manufacturing and selling enterprises increase with the adoption of blockchain technology, yet the ladder-utilizing enterprise achieves the highest profits when not adopting blockchain technology. Furthermore, the adoption of blockchain technology can increase consumer surplus and social welfare while reducing the impact on the environment. These studies provide theoretical guidance on both economic and social environment for the operation decision of each member in the closed-loop supply chain of power batteries.

Analisis Hubungan Citra Merk dan Kualitas Produk Terhadap Kepuasan Konsumen Pengguna Kendaraan Listrik di Indonesia

This study aims to analyze the influence of brand image and product quality on customer satisfaction in the electric vehicle industry in Indonesia. A strong brand image and high-quality products are critical factors for electric vehicle manufacturers to build consumer trust and increase sales. In the context of the growth of electric vehicles as an environmentally friendly alternative, this research is grounded in the concepts of customer satisfaction, brand image, and product quality. The study employs a quantitative approach, utilizing a survey involving 154 respondents who are users of two- and four-wheeled electric vehicles. The collected data were analyzed using multiple linear regression to examine the partial and simultaneous effects of the two independent variables on the dependent variable. The results show that brand image and product quality have a significant positive influence, both partially and simultaneously, on customer satisfaction. These findings contribute theoretically to the marketing literature by reinforcing the role of brand image and product quality in enhancing customer satisfaction. Furthermore, the results can be useful for the electric vehicle industry in Indonesia in efforts to improve customer satisfaction through the optimization of brand image and the quality of products offered.