Vehicle Brands Research Articles

Electric Vehicle Sentiment Analysis Using Large Language Models

Sentiment analysis is a technique used to understand the public’s opinion towards an event, product, or organization. For example, sentiment analysis can be used to understand positive or negative opinions or attitudes towards electric vehicle (EV) brands. This provides companies with valuable insight into the public’s opinion of their products and brands. In the field of natural language processing (NLP), transformer models have shown great performance compared to traditional machine learning algorithms. However, these models have not been explored extensively in the EV domain. EV companies are becoming significant competitors in the automotive industry and are projected to cover up to 30% of the United States light vehicle market by 2030 In this study, we present a comparative study of large language models (LLMs) including bidirectional encoder representations from transformers (BERT), robustly optimised BERT (RoBERTa), and a generalised autoregressive pre-training method (XLNet) using Lucid Motors and Tesla Motors YouTube datasets. Results evidenced that LLMs like BERT and her variants are off-the-shelf algorithms for sentiment analysis, specifically when fine-tuned. Furthermore, our findings present the need for domain adaptation whilst utilizing LLMs. Finally, the experimental results showed that RoBERTa achieved consistent performance across the EV datasets with an F1 score of at least 92%.

Research on the Network Communication Strategy of New Energy Vehicle Brand in Xi an China -- Taking NIO as an Example

With the increasing global attention to sustainable development and environmental protection, new energy vehicles have become the main direction of transformation and upgrading of the global automotive industry and green development. As one of the world s largest auto markets, China is also actively promoting the development of the new energy vehicle industry. This project will visit the sales points and service centers of NIO in Xi an market to understand the specific implementation of its network communication strategy. Therefore, this research intends to establish a perceived intention model to analyze the related factors of network communication effect in the light of Technology Acceptance Model (TAM). At the same time, the questionnaire survey method is adopted to collect data on the network communication strategy and consumer feedback of NIO, learn consumers feedback and satisfaction on the network communication strategy of new energy vehicles, provide key market insights, and better understand consumers demands and expectations.

Implementation of An Application-Based Motor Vehicle Exhaust Emission Level Detection System

Currently, air conditions on earth are getting worse over time due to the impact of air pollution. One example of air pollution is motor vehicle exhaust emissions. Exhaust gas emissions are the result of combustion residue in motor vehicle engines that use fuel. Motor vehicle exhaust emissions contain carbon monoxide (CO), hydrocarbons (HC), carbon dioxide gas (CO2) which have a negative impact on the environment and living creatures. This research will create a motor vehicle exhaust emission detection device. In this design, an Arduino microcontroller was used and the manufacture of this tool used an MQ-7 gas sensor to detect carbon monoxide (CO) gas, an MQ-2 sensor to detect hydrocarbon gas (HC), and an MQ-135 to detect carbon dioxide (CO2) gas. The emission test results will be sent to the application, this data includes plate number, vehicle type, vehicle brand, vehicle year and emission test results. The results of the carbon monoxide (CO) gas sensor calibration test taken from 5 data showed an error of 5.51%. The results of the hydrocarbon (HC) gas sensor calibration test taken from 5 data showed an error of 4.23%. The results of the carbon dioxide (CO2) gas sensor calibration test taken from 5 data showed an error of 1.06%. In the implementation of the tool and application, the test results were obtained for 15 vehicles. Where the highest hydrocarbon (HC) gas content value was 412 ppm, the highest carbon monoxide (CO) gas content value was 1.48%, and the highest carbon dioxide (CO2) gas content value was 21.4%.

Comparative Stock Performance Analysis of Leading Electric Vehicle Brands: Tesla, BYD, and NIO Using Python Programming Language

This research paper aims to perform a comparative stock performance analysis of three leading electric vehicle brands: Tesla, BYD, and NIO, utilizing the Python programming language. The primary objective is to examine the financial trajectories of these companies by analyzing their historical stock prices, volatility, and return on investment over a defined period. Python programming language is also a key part of data analysis and data visualization. Methodologically, the study employs various Python libraries for data collection, preprocessing, and analysis, ensuring a robust and efficient analytical process. The key findings reveal distinct performance patterns and market behaviors for each company. Tesla demonstrated high volatility but significant long-term returns, while BYD showed consistent growth with moderate volatility. NIO, as a newer entrant, exhibited rapid growth with higher short-term risks. The conclusions drawn from this study provide valuable insights into the financial health and market positioning of these EV giants. By leveraging Python's powerful data analysis capabilities, this research not only enhances understanding of stock performance in the EV sector but also offers a practical framework for investors and analysts.

Research study of passenger cars repair costs depending on the vehicle make, type of spare parts and the entity providing the service

The high number of road accidents has significant social importance, both in the context of households and enterprises, because each vehicle damage entails financial outlays related to the repair of damaged vehicles. This article analyses the most common types of vehicle damage occurring in road traffic. The object of the research were the vehicles most frequently purchased in Poland in 2022. The research process involved numerical experiment method using the AUDATEX system to determine costs enabling to repair such damage. The analyses take into account various repair options, such as: Authorized Service Station, independent workshop, and conditions proposed by insurance companies in Poland. The research showed cost dependencies between variables such as the vehicle brand, the type of spare parts and the entity providing the service.

A case study and empirical examination of creating a new premium new energy vehicle brand by NIO

A case study and empirical examination of creating a new premium new energy vehicle brand by NIO

Analisis Karakteristik Pergerakan Moda Transportasi Pengangkut Bawang Merah Kabupaten Enrekang

Land transportation as a means of inter-city transportation has the advantage of being able to distribute people and goods with a larger capacity and relatively cheaper costs. The aim of this research is to determine the characteristics of onion transportation, performance, distribution time and the purpose of distributing the onion harvest in Enrekang Regency. This research used a quantitative method, which was carried out for 1 month, namely in September-October 2022 in Enrekang Regency, South Sulawesi, using SPSS analysis. The results of the research show that the characteristics of the 240 respondents were all men, with the most widely used vehicle brand being the Mitsubishi 4-wheeled type (medium truck), the most frequent distribution time range was between 10-15 times a month with an average speed of 50- 60 km/hour, departure time between 10:00 – 15:00 WITA, and arriving around 15:00 – 18:00 WITA, distance over 100 Km, and the longest loading time is over 120 minutes, with the aim of distribution most often to exporters with a percentage of 57.08%, while for distribution areas outside Enrekang Regency the most frequently is Parepare City with a percentage of 46.25%.

The Current Sales Status and Countermeasures of Chinese New Energy Vehicles in Europe

With the expansion of China's new energy vehicle overseas business, Europe has replaced Asia as China's largest export destination of new energy vehicles in 2021. As the world's second-largest and second-fastest-growing new energy vehicle market, Europe contains plenty of opportunities and challenges for Chinese car manufacturers. Through analysis, the author found that China's new energy vehicle brands have shown a rapid development trend in Europe in recent years and are operating well. This paper aims to deeply explore the main problems they face and find corresponding solutions based on this actual situation. After using two research methods: literature analysis and data analysis, this paper found that Chinese manufacturers have some problems with international competitiveness, brand image, sales and service capabilities, supporting facilities, and resistance to political risks, and measures need to be taken to solve them. In addition, Chinese car companies have also encountered the serious problem of insufficient basic charging facilities in the European market, and are affected by political factors such as the Russia-Ukraine conflict and countervailing investigations.

Automotive Kit Demand Forecasting Using Advanced Forecasting Models: A Data-Driven Approach for Optimal Demand Forecasting

This study addresses the major challenges of forecasting automotive kit items(parts of vehicles) by enhancing the delivery of the products and managing the inventory. The kit items vary as per customers and it is unique on its own, where the uniqueness determines the vehicle parts. Customers are the major role players who provide the business hence, this study highlights various factors contributing to the customer’s choice of kit items with features consisting of vehicle name, original equipment manufacturer (OEM), Item Description (collection of vehicle parts) type of product (brand of vehicle) and monthly allotment of each kit item as per customer starting from 2021 April to 2024 January. We conducted an extensive analysis to assess a range of time series analysis techniques for predicting kit demand within the automotive industry, the methods we investigated encompassed Autoregressive (AR), Autoregressive Moving Average (ARMA) ,Autoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving Average (SARIMA), Simple Exponential Smoothing (SES), Holt's Linear Trend Method - Double Exponential Smoothing, Triple Exponential Smoothing - Holt Winters, Long Short-Term Memory (LSTM) and advanced forecasting models such as prophet in evaluating the accuracy of these models, we employed key metrics such as Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE), this study aims to drive significant progress in the automotive industry by optimising inventory management reducing storage costs and improving delivery efficiency to ensure smooth business operations moreover the integration of visually engaging dashboards for real-time analysis of projected values plays a pivotal role in identifying crucial monthly demand trends this integration not only enhances operational efficiency but also fosters enriched customer engagement thereby facilitating sustained advancement within the automotive sector.

The future of waste cooking oil and its carbon and economic benefits——An automotive energy perspective

As a crucial energy carrier, waste cooking oil poses a significant threat to land and water resources. Furthermore, there is a risk of its reintroduction into the restaurant system, posing a direct threat to public health. Hence, converting waste cooking oil into clean energy has emerged as a pressing concern. This study compares the CO2 emissions and economic benefits of two pathways applied to automotive energy consumption——the waste cooking oil produced biodiesel pathway and the waste cooking oil mixed with coal for power generation pathway. The results show that for both diesel and electric versions of the same brand of vehicles, the CO2 emission of an electric vehicle using waste cooking oil mixed coal produced electricity is 0.181 kg/km, which is a 26.12% reduction compared to a diesel vehicle using waste cooking oil converted to biodiesel. Consumers appreciate the low price of electricity. However, for producers, the waste cooking oil produced biodiesel pathway demonstrates superior economic benefits. At the current market price, converting waste cooking oil into biodiesel will result in a net gain of 112.89 billion Yuan for the producer, whereas the waste cooking oil mixed with coal for power generation pathway will result in only 2.08 billion Yuan in net gain. This disparity is primarily attributed to the lower electricity prices for electric vehicles. To encourage the widespread adoption of waste cooking oil energization technologies, Chinese government can raise electricity prices for electric vehicles to a minimum of 1.599 Yuan/kW·h, ensuring equal net gains in both pathways.

Design and Implementation of a Tailored Dealer Management System (DMS) for the Automotive Industry

This paper presents a thorough investigation into the design and implementation of a Dealer Management System tailored for the automotive industry. The DMS is intended to streamline after-sales processes such as inventory and expense management, service order creation, and financial data monitoring. The system integrates with a variety of other platforms, including ERP, CRM, and payment systems, which improves collaboration between dealers and distributors. The architecture of DMS, known as Copilot Next, is detailed, with a focus on the backend, frontend, and integration components. Sentinet and Dell Boomi are integration tools that allow for seamless connectivity with other systems. The findings show that the DMS effectively meets the needs of multiple vehicle brands, improves part ordering accuracy with AI tools, and ensures data consistency across systems. This study offers useful insights into the design and implementation of a DMS that can significantly improve dealership operations and customer service in the automotive industry.

ASSESSING THE DEVELOPMENT OF AUTONOMOUS CARS

With recent innovations regarding autonomous vehicles and the fact that several vehicle brands have started to deploy autonomous driving functionalities, it is still unknown what these innovations may offer to social lives. Owing to the ability to autonomously drive from one location to another, the concept of shared autonomous vehicles was created to let an individual turn their assets into a source of income while other individuals could use this service without having to own a vehicle. The development of this emerging concept was aided by an evaluation of an ontology already presented regarding the topic of shared autonomous vehicles performed by three different frameworks (OQuaRE, OntoMetrics and OOPS) that generally agreed with the validity of the proposed ontology.

Evaluation of electric car styling based on analytic hierarchy process and Kansei engineering: A study on mainstream Chinese electric car brands

To evaluate the fuzzy and uncertain factors brought by human's emotional sensibilities during the design of new energy vehicle models, a scientific design evaluation method was adopted. This study combines the Analytic Hierarchy Process (AHP) and Kansei Engineering to assess the design of new energy vehicle models. It uses both objective criteria and subjective user perceptions. First, it quantified the design imagery vocabulary through Kansei Engineering and identified the target imagery vocabulary. Secondly, the AHP method was used to establish a relationship between design features and imagery vocabulary. Thrid, the study created an evaluation index system for design imagery, and adopted the fuzzy comprehensive evaluation matrix to rank the representative vehicles and brands in the Chinese new energy vehicle market. Based on the weight analysis results, the vehicle functionality (whether it is safe and reliable), the elegance of design, and the intricacy of vehicle structure were identified as the top three aspects that affect the impression of new energy vehicles. Therefore, we need to focus on these aspects during the design of new energy vehicles. Additionally, by integrating objective evaluation and emotional analysis results, we assessed the design for each new energy vehicle brand. The results of this study are important for developing the new energy vehicle market.

Taking BYD as an Example to Analyze New Energy Vehicles

With the development of the times, the environmental problems brought by fuel powered vehicles have gradually attracted people's attention, and new energy vehicles have also received increasing social attention. People seem to attach more importance to and want to understand new energy vehicles, and the technology and marketing strategies of new energy vehicles have gradually become more mature. This article will take BYD Automobile as an example to analyze and propose some suggestions for the sales strategy and supply chain management of new energy vehicles. The full text study found that both BYD and other new energy vehicle brands have their own methods to attract customers for consumption, and the sales of new energy vehicles are also getting better with the attention of society. The research significance of this article lies in identifying some problems encountered in the development of new energy vehicles and proposing solutions, as well as expectations for the future of new energy vehicles.

АНАЛИЗ ИСПОЛЬЗОВАНИЯ АВТОМОБИЛЬНОГО ТРАНСПОРТА В УСЛОВИЯХ АПХ «МИРАТОРГ»

The article analyzes the use of road transport of the Miratorg agricultural holding in the Bryansk region. The structure of the vehicle fleet is considered in terms of various characteristics: types of vehicles by purpose, brands of vehicles. Calculations of particular and general technical and operational indicators of vehicles are given. An assessment of the effectiveness of the use of agricultural holding vehicles is given.

전기자동차 제품 품질이 고객 만족도 및 고객 충성도에 미치는 영향

This study conducted an empirical analysis on the effect of electric vehicle product quality on satisfaction, electric vehicle brand and loyalty to consumers who have purchased and used electric vehicles in the Chinese electric vehicle market, and analyzed the mediating effect of customer satisfaction between electric vehicle product quality and customer loyalty.
 Garvin (1984) reviewed prior research using the eight components of the proposed product quality and established questionnaires on the eight components, and conducted a 12-day survey from August 07 to 18, 2023. The actual questionnaire collected the results of a total of 266 people, excluded 41 copies without experience in using electric vehicles, 18 invalid questionnaires, and analyzed the relationship between customer satisfaction and customer loyalty using 207 valid questionnaires.
 According to the results of the analysis, it was confirmed that core functions, appearance characteristics, reliability, aesthetics, and cognitive quality had a positive (+) significant effect on customer satisfaction in the product quality model, and core functions, reliability, consistency, and cognitive quality had a positive (+) significant effect on customer loyalty. In addition, customer satisfaction had a positive (+) effect on customer loyalty. In addition, customer satisfaction has a mediating effect in the relationship between core performance, reliability, cognitive quality, and customer loyalty of electric vehicle product quality. Finally, core performance, reliability, and cognitive quality, which are components of electric vehicle product quality, have all been shown to have a positive (+) effect on customer satisfaction and customer loyalty, so it is necessary to increase core performance, reliability, and cognitive quality to improve customer satisfaction and customer loyalty.

Tesla’s Enlightenment on the Development of New Energy Vehicle Brands in China

Tesla’s Enlightenment on the Development of New Energy Vehicle Brands in China

Exploring the Cargo Potential: A Comprehensive Analysis of Kertajati Airport

Motorized vehicle can’t be apart from our daily activity, because it’s very significantly save our time and energy. According to Erwin (in Sasongko, 2014: 1) mentioned air pollution that comes out from motorized vehicle is very high, so it can pollute the environment and harm human health. Besides, the fossil fuel is an unrenewable which is running low and will cause an energy crisis. So we need alternative energy that is more eco friendly, common, and easy to obtain. Therefore, electric vehicle are one solution to this problem. Electric vehicle is a fuelless vehicle that ran by electric motor with battery for the energy supplier. In accordance with the Kepmen ESDM No. 13 Tahun 2020 about “that to increase the energy efficiency, energy resilience, and energy conservation in transportation sector, it needs to accelerate the battery-based electric motor vehicle program” so that it is necessary to develop innovations to support electric vehicle infrastructure in Indonesia. BLDC Motor is one of the motor type that used in electric vehicle. BLDC Motor used by one of the electric vehicle brands in Indonesia named GESITS, experienced an overheat on the BLDC motor after travelling 30 kilometers around Bekasi (GESITS, 2016). Finally to add cooling to the BLDC Motor, an external fan is installed. This experience shows the importance of cooling to maintain BLDC Motor durability. In addition to cooling the electric motor, it is necessary to pay attention to the efficiency produced by the electric motor. So that it can make consideration of battery consumption on the motorcycle design. Based on the problems above, this research will analyze the efficiency and thermal of a 3000 Watt BLDC Motor in the design of an electric motorcycle. The data collection will be carried out by using the Dynotest tool or Chassis Dynamometer to obtain amount of power, torque, electric current and thermal on the electric motor being tested. From these data calculations will be carried out for the efficiency of a 3000 Watt BLDC Motor. So that this research can be used as a reference for the further development of electric vehicles.

Research on the Purchase Intention of Electric Vehicles Based on Customer Evaluation and Personal Information

With the continuous development of electric vehicle (EV) technology, there is an increasing need to analyze the factors influencing customers’ purchase intentions. According to the data of customers’ vehicle experience evaluation and personal information, this paper develops the analysis models of influencing factors using the analysis of variance algorithm (ANOVA) and Kruskal–Wallis algorithm. Then, the purchase intention model for EVs is proposed using the random forest method. Finally, the optimization model for the EV sales plan was built. The results show that the main factors influencing customers’ purchases are different for different vehicle brands. However, the customer’s evaluation of the vehicle experience has a greater influence on the customer’s purchase. Compared to other prediction models, the random forest model has the highest accuracy. For 3 EV brands, the prediction accuracies are 97.8%, 98.9%, and 97.6%. In addition, this paper predicts the purchase intentions of 15 customers. By optimizing the sales plans for 3 EV brands, the predicted purchase rate of 15 customers increased from 40% to 53%. The research work contributes to the sales of electric vehicles, the accurate positioning of customers, and the identification of more potential customers.

The impact of public climate change concern on sustainable product consumption: a case study of new energy vehicles in China

AbstractWith global climate change problems becoming increasingly serious, sustainable consumption has become an inevitable trend. In this paper, we take the Chinese new energy vehicle market as an example and research the relationship between the public climate change concern and sustainable product consumption behaviour, while considering the time decay effect of public concern. We collect authoritative secondary data on climate change Baidu search index and the monthly sales of new energy vehicle brands and use panel data to test the hypotheses empirically. The result shows that there is a significant positive effect of public climate change concern on new energy vehicle consumption behaviour. This effect is also present when the time decay effect is considered. The result shows that public new energy vehicle concern has a significant negative effect on new energy vehicle consumption behaviour. The findings provide theoretical support for government policymakers and corporate managers to promote the adoption and diffusion of sustainable products.