Electric Cars Research Articles

Vehicle pricing considering EVs promotion and public transportation investment under governmental policies on sustainable transportation development: The case of Norway

The present research investigates the advancement of sustainable transportation by promoting electric vehicles, expanding public transit, and implementing tax increases on fossil fuels and automobiles, via crucial strategies. The present study has examined a market with a fossil fuel vehicle (FFV) manufacturer, an electric vehicle manufacturer, and the government. The manufacturers' pricing strategies are geared towards optimizing profits, whereas the government's objectives for transportation are centered on attaining sustainability across economic, environmental, and social dimensions. The government has considered two strategies, one taxation-based and the other non-taxation-based, to achieve its objectives. In the taxation-based strategy, fixed taxes on fossil-fuel vehicles and fossil fuels are considered, while in the non-taxation-based strategy, subsidies for purchasing electric vehicles and the number of buses purchased for public transportation are predefined. Based on this, eight scenarios with different values for the predefined factors of each strategy have been defined to attain their respective objectives. Game theory has been utilized to determine an optimal solution based on Norwegian data, owing to the interconnected decision-making among stakeholders. By analyzing the findings, managers can enhance their decision-making capabilities. The results suggest that appropriately adjusting subsidies, taxes, and bus numbers within specific thresholds is crucial for mitigating air pollution and achieving other objectives. The assertion that electric cars are a definitive solution may not be accurate, as it depends on the source of the generated electricity. While excessive subsidies in non-renewable energy countries can lead to increased pollution, even in Norway, where most electricity is renewable, rising demand for electric vehicles contributes to air pollution due to increased production. In countries where electricity generation is not primarily from renewable resources, the growth of electric vehicles further exacerbates pollution.Simultaneous increases in fuel taxes and tariffs on fossil fuel vehicles negatively impact the demand for fossil fuel vehicles and government revenues. Therefore, it is recommended that an increase in fuel taxes be implemented to optimize both government revenues and social welfare. This approach safeguards public revenues, promotes societal well-being, and mitigates air pollution.

Managing coopetitive innovation: sharing while protecting knowledge in separated project teams

Existing research on coopetition acknowledges the dilemma companies face regarding sharing and protecting knowledge when developing coopetitive product innovation. To manage this dilemma, coopetitors can rely on two different organizational designs: the coopetitive project team (CPT) or the separated project team (SPT). The CPT fosters high knowledge sharing but creates uncertainty about knowledge protection. In contrast, the SPT limits the knowledge sharing but offers higher knowledge protection. While the CPT design has been studied in‐depth, the SPT design remains an underexplored black box. We know little about how knowledge is shared and protected within the SPT. To fill this gap, we conducted an ethnographic case study of a joint innovation project using SPT in the Chinese electric car industry. Our research shows how the SPT design manages the necessary knowledge sharing while protecting the knowledge. The project managers facilitate knowledge sharing by acting as the interface coordinator with the coopetitor, and the knowledge protection is guaranteed by a strict separation between the two coopetitors' operators. In SPT, the nature and the management of knowledge flows are not rigid but evolve according to the project stage.

Green Politics and the Policy Cycle in Indonesia's Electrification Journey: A Comparative Analysis of Policy Priorities for Electric Cars and Public Transport

This paper presents a comprehensive Descriptive Study and Document Analysis of policy priorities for electric cars and public transport in Indonesia, within the context of the country's electrification journey. Utilizing secondary data sources including policy documents, government reports, academic studies, and news articles, we apply the principles of Green Politics and the stages of the Policy Cycle to interpret our findings. Our comparative analysis reveals distinct policy priorities for electric cars versus public transport, with implications for Indonesia's environmental, economic, and social goals. We discuss these findings in relation to the principles of Green Politics and the stages of the Policy Cycle, providing insights into the political and policy dynamics shaping Indonesia's electrification journey. The paper concludes with recommendations for future policy priorities and strategies, aimed at promoting a more sustainable and equitable transition to electric mobility in Indonesia, and suggests areas for future research. Our research contributes to the growing body of literature on electrification policies in developing countries, and offers valuable insights for policy makers, industry stakeholders, and researchers

Development of Public Electric Vehicle Charging Stations (SPKLU) in Makassar as an Electric Car Supporting Means

Development of Public Electric Vehicle Charging Stations (SPKLU) in Makassar as an Electric Car Supporting Means

Marketing Events Mediating BEV Features and Operating Costs: Impact on Purchase Intentions

This research aims to find out the lack of influence of Batery Electric Vehicle (BEV) features and vehicle operating perspective costs on the interest in purchasing electric cars with marketing events as a mediation and review from an Islamic. This devotional population is a society over 21 years old that is domiciled in Jabodetabek. The sample in this study was made up of people who drove more than three times in one week, for a total of 100 respondents. The sampling technique uses a non-probability method with purposive sampling techniques through the distribution of questionnaires with Google forms. The analytical method used is the Partial Least squares Structural Equation Modeling method (PLS-SEM). The results of the study show that Feature influences Purchase Intention, Feature influences Marketing Event, Vehicle Operating Cost influences Purchase Intention, Marketing Event influences Purchase Intentions, Marketing Event mediates the influence of Feature on Purchase Intentions, Features, Vehicle Operating Costs, Marketing Events, and Purchase Intention BEV cars among the people in Jabodetabek. The implications of the results of this study present that purchase intention towards BEVs encourages producer management to optimally utilize all the variables analyzed in this study proportionally.

Simulating the effects of tax exemptions for plug-in electric vehicles in Norway

For many years Norway has been in the forefront of promoting electromobility. Today, Norway has the world’s highest per capita fleet of plug-in electric cars. In 2021, 1.6% of the cars in the EU fleet were plug-in electric vehicles, whereas their share was 21% in Norway. Part of the successful market take-up rate is due to wide-ranging tax exemptions. Increasing plug-in electric vehicles numbers causes tax revenue losses, making exemptions unsustainable. Norway has the ambitious goal that from 2025, all newly registered cars shall be zero-emission vehicles. Keeping tax exemptions in place might be crucial for this goal. The objective of this paper is to provide information to solve this dilemma. Tax exemption reduction and abolition paths which offer a compromise between minimal effects on the development of zero-emission vehicles and tax revenues have been identified. An updated and re-calibrated version of the stock-flow-model SERAPIS was used to simulate and assess different scenarios. Results show that a controlled tax phase-in allows Norway to reach its environmental targets of 100% zero emission vehicles by 2025 and a 55% decrease of CO2-emissions in 2030 relative to 2005 while simultaneously increasing public revenues significantly.

Development of Smart Fire Safety System for Vehicles Using IOT

Today, fire accidents often occur in homes and industrial environments, where climate change and human negligence can be predicted. The proposed prototype is designed to detect such fire accidents and remotely extinguish the fire from the user, thus reducing the risk to firefighters. The main idea of ​​this concept is to propose a model that focuses on the cost-effective design and implementation of an automatic fire protection system for electric vehicles. In this system, the fire extinguisher is activated when it detects flame/smoke in the vehicle fire area and extinguishes the fire automatically. There are many reasons for an electric vehicle that can cause fire accidents. The main cause of electric car fires is the battery used in them. There have been many cases of cars catching fire for the reasons mentioned above and ending with the entire vehicle reduced to ashes. The installation of an automatic extinguishing system allows to minimize the financial losses that can arise from a fire and to increase the safety level of the vehicle, passengers and other road users. Keywords : Fire Situation, Controller, Emergency Alert, Accident Prevention, IOT Technology etc.

Analytical and Experimental Research for Development of the Airless Tires for Urban Micromobility Means

It is currently recognized that electric vehicles are the optimal type of passenger transport for urban usage. However, there are very few people willing to buy them, since today electric cars are very expensive. So the development of the personal light electric transport segment (electric bicycles, scooters, motorcycles, etc.) becomes very relevant. At the same time, the introduction of new technologies (in particular, 3D printing) and constructions (airless wheels) for their mass production is of particular importance. The range of problems that can be solved by modern additive technologies is expanding every day. FDM technology is one of the most commonly used additive methods. It is not only widely available, but it also provides significant possibilities for decision-making. However, most developments in this area are focused on obtaining the geometric accuracy of shapes without taking into account the mechanical properties of materials used. Therefore, the purpose of this study is to investigate experimentally the influence of filling density of parts manufactured by 3D printing on their mechanical properties and application of obtained results for the production of airless tires by using FDM technology.

For the regeneration of spent graphite: The exploring of structural failure mechanism about commercial graphite

Along with the wide application of electric automobiles, the great “wave” of recycling for lithium-ion batteries would be upcoming due to their limited cycling lifespan. As the main components but without valuable elements, spent graphite suffers from effective recycling manners. Although the regeneration method has been deemed as a promising manner, the clarifying of their failure mechanism is prerequisite to the exploring of regeneration methods. Herein, commercial graphite with different healthy states is prepared through the disassembling of cells at different cycles. Assisted by the detailed structural analysis, the systematic failure process is clearly illustrated. At initial cycling, the shuttling of lithium ions renders the decomposing of unstable carbon atoms and some weak interlayer structures. With further cycling, the interlayer architecture and large-size grains were further damaged, to form small-size grains, accompanying enhanced anisotropy, finally resulting in the increasing internal resistance. Moreover, owing to the ion-diffusion behaviors, graphite sheets have an obvious moving, resulting in the transformation from 2H-phase to 3R-phase with the decreasing of energy-storage activity. Thus, from the perspective of internal structure, the decreasing of graphitized grains and the formation of 3R-phase served as crucial failure factors. Given this, the work is anticipated to illustrate the failure mechanism of graphite, meanwhile offering the basic regeneration direction of spent graphite samples.

Analysis of Factors that Influence Indonesia’s Automotive Customer Decisions towards the Repurchase of Electric Cars

To expand the EV ecosystem in Indonesia through consumer repurchases, it is necessary to understand what can cause consumers to repurchase electric vehicles. This research aims to determine the factors that influence consumers' decisions to repurchase electric cars in Indonesia using the application of the Extended Theory of Planned Behavior. 198 relevant respondents were selected to fill out the online questionnaire, and the collected data was then analyzed based on the SEM-PLS model. The results state that the satisfaction factor can influence consumers' positive opinions towards electric cars, resulting in interest in repurchasing electric cars. The existence of the Theory of Planned Behavior indicators along with the support of additional components in the form of monetary and non-monetary policies can also influence consumers' interest in repurchasing electric cars.

Speed Control of Electric Car Using Field Oriented Controlled Switched Reluctance Motor

Nowadays, global warming caused by carbon emission threatens the lives of human beings and living organisms. The problem of reducing carbon dioxide (CO2) has become urgent. Therefore, in the vehicle world, electric vehicles (EV) are being used instead in order for reducing the fuel consumption. The using of electric motor plays a significant role in the performance of electric cars. In most recent research, the application of switched reluctance motor (SRM) can be seen to improve the performance of electric cars. Thus, this research focuses on the testing the performance of SRM. Among the many benefits of SRM, torque ripple is a drawback. For reducing the torque ripple, the closed-loop vector control is applied to motor control. In this research, field oriented control (FOC) to SRM is used for NEVERA TECH EV car. The scenarios for Speed acceleration, deceleration, and torque change are considered for the performance analysis using MATLAB/Simulink.

Assessing the Additional Benefits of Thailand’s Approaches to Reduce Motor Vehicle Emissions

Air pollutants and greenhouse gases (GHGs) represent major challenges in our era, contributing to climate change and global health issues. These problems arise from a variety of well-known sources, including motor vehicles. Almost all nations, Thailand included, have formulated and implemented policies to curb greenhouse gas (GHG) emissions in line with the requirements and commitments of the Paris Agreement. The evaluation of specific air pollutants and GHG emissions originating from road vehicles utilises the Thailand database, referencing the year 2019. Data intersections from 2019 to 2022 are grounded in actual data collected from relevant departments in Thailand, while projections for 2023–2030 are forecasted based on the baseline year. The secondary database used in the International Vehicle Emission model is adjusted according to real-world driving data to accurately reflect country-specific emission factors. Dynamic emission factors for specific air pollutants and GHGs are evaluated and integrated with the average Vehicle Kilometres Travelled (VKT) for each vehicle category. The Business-As-Usual (BAU) scenario is then examined, based on existing policies aimed at reducing air pollutants and GHG emissions in Thailand’s transport sector. These policies include strategies for the adoption of electric vehicles and the promotion of public transport to reduce VKT. Under the BAU scenario, the overall number of road vehicles in Thailand, including passenger cars, motorcycles, pickups, vans, trucks, and buses, is expected to increase by approximately 6.58% by 2030, leading to a rise in specific air pollutants and GHG emissions compared to the 2019 baseline. However, by adhering to Thailand’s strategies and transitioning to new electric passenger cars and buses, greenhouse gas emissions and specific air pollutants from the road transport sector will be significantly reduced.

Indonesia's Movement to Become the Main Player in The Electric Vehicle (EV) Market in Southeast Asia

This article discusses Indonesia's position in the electric vehicle market with a focus on investment from multinational companies such as Hyundai. Globalization plays an important role in the development of the electric vehicle industry, with the aim of reducing pollution and exhaust emissions. Multinational companies are often involved in the production of environmentally friendly vehicles as part of efforts towards a green economy. Through descriptive qualitative research methods, this research describes the relationship between state policies and the behavior of investment actors in the phenomenon of global capitalism in globalization and its impact on the electric vehicle market in Indonesia. With investment from multinational companies, Indonesia is expected to become the leading electric car battery producer in ASEAN. The steps and strategies for cooperation between Indonesia and Hyundai in developing the electric car battery industry are also discussed in this article.

CAPM Model and Optimal Risky Portfolio for American Stock Market

The stock market has high risks. The purpose of this project is to calculate the beta coefficients and build the optimal risky portfolio consisting of eight different stocks each representing different significant industries (which includes information technology, electric cars etc.) to diversify risk and gain a high return. Putting more stocks into the portfolio can help analysts carry out comprehensive analysis on different situations, periods, and types of investment portfolio, so as to disperse risks and obtain high returns, also, ensure the diversity of portfolio and a lower risk. The empirical results in this paper shows that by allocating their money appropriately in different stocks, investors can gain returns multiple times higher than putting all of them in merely one single stock, which proves the validity of this paper

Estimating Inhaled Nitrogen Dioxide from the Human Biometric Response

Breathing clean air is crucial for maintaining good human health. The air we inhale can significantly impact our physical and mental well-being, influenced by parameters such as particulate matter and gases (e.g. carbon dioxide, carbon monoxide, and nitrogen dioxide). Building on previous research that explored the effects of particulate matter (PM) in specific environments, analyzed using biometric indicators and machine learning models; this work focuses on the effects and estimation of inhaled nitrogen dioxide (NO<sub>2</sub>). This study involved a cyclist equipped with sensors to monitor various biometric parameters. In addition, an electric car following the cyclist measured the ambient NO<sub>2</sub> levels using an onboard sensor. A total of 329 biometric variables have been taken into account, of which 320 biometric variables are cognitive responses extracted using an electroencephalogram (EEG) and 9 biometric variables are physiological responses extracted using several sensors. Inhaled NO<sub>2</sub> levels are first estimated initially by making use of all 329 variables, then using 9 physiological responses and finally using only 6 of the 9 physiological responses. The study also uses a ranking method to pinpoint which biometric variables most significantly estimate inhaled NO<sub>2</sub> levels. Furthermore, it investigates the linear and non-linear relationship between certain variables and inhaled NO<sub>2</sub>. The general precision of the prediction for the data set was moderate, as indicated by the coefficient of determination (R<sup>2</sup>) and the root mean square error (RMSE) between the true and estimated values of NO<sub>2</sub> to be 0.35 and 5.41 ppb, respectively, in the test set. A higher accuracy in the prediction of lower values of NO<sub>2</sub> levels was qualitatively observed using a scatter diagram and a Quantile-Quantile plot where the data were more plentiful. For more robust conclusions, additional data and refined machine learning models are necessary.

Self-Diagnostic Opportunities for Battery Systems in Electric and Hybrid Vehicles

The number of battery systems is also growing significantly along with the rise in electric and hybrid car sales. Different vehicles use different types and numbers of batteries. Furthermore, the layout and operation of the control and protection electronics units may also differ. The research aims to develop an approach that can autonomously detect and localize the weakest cells. The method was validated by testing the battery systems of three different VW e-Golf electric vehicles. A wide-range discharge test was performed to examine the condition assessment and select the appropriate state of charge (SoC) for all three vehicles. On the one hand, the analysis investigated the cell voltage deviations from the average; the tests cover deviations of 0 mV, 12 mV, 60 mV, 120 mV, and 240 mV. On the other hand, the mean value calculation was used to filter out possible erroneous values. Another important aspect was examining the relationship between the state of charges (SoC) and the deviations. Therefore, the 10% step changes were tested to see which SoC level exhibited more significant voltage deviations. Based on the results, it was observed that there are differences between the cases, and the critical range is not necessarily at the lowest SoC level. Furthermore, the load rate (current) and time of its occurrence play an important role in the search for a faulty cell. An additional advantage of this approach is that the process currently being tested on the VW e-Golf can be relatively simply transferred to other types of vehicles. It can also be a very useful addition for autonomous vehicles, as it can self-test the cells in the system at low power consumption.

Development of an electric drive for personal light electric vehicles

Problem. The article addresses the challenge of enhancing inclusive mobility and environmental cleanliness by developing a traction electric drive for personal light electric vehicles. A study was conducted on modern electric drive systems for personal light electric vehicles. Goal. The aim is to boost inclusive mobility and environmental cleanliness through the development of a traction electric drive for a personal light electric vehicle, specifically based on a tricycle. Methodology. The methodology involves scientific analysis and synthesis of traction electric drives for electric vehicles. An assessment of the nominal capacity of the battery module from the Nissan Leaf electric car was conducted using both partial discharge procedures and the Leaf Spy Pro program. Results. Based on an analysis of existing electric drive systems, a traction electric drive for a tricycle was developed. A functional diagram of the electric bicycle drive was generated. A control system for a sensorless brushless motor was developed, determining rotor position by measuring EMF in the free phase. This led to the creation of a stable voltage electrical circuit with a virtual midpoint. The tricycle's electric drive utilizes two 10-inch motor wheels on the rear wheels, enabling high speed and efficiency. Controllers specifically designed for electric wheel motors with a power of 350 W were selected to control the traction electric drive. Modules from the 2015 Nissan Leaf electric car's battery, which had depleted 20% of their capacity, were chosen to power the electric drive. The battery health status is 77.95%. A model of the battery's electrical equivalent circuit was constructed, and partial discharge graphs of the Nissan Leaf battery module were analyzed. Originality. The results provide a comprehensive insight into the development of a traction electric drive for personal light electric vehicles, using a tricycle as an example. Practical value. The research led to the development of an electric drive for a three-wheeled vehicle, with two motor wheels of 350 W nominal power each. The power supply voltage ranges from 36 V to 48 V, powered by six battery modules from the Nissan Leaf electric car, totaling 48 V. The energy capacity of one battery module is 0.3898 kWh, resulting in a total energy capacity of 2.3388 kWh for the vehicle's battery. However, the realizable capacity does not exceed 1.871 kWh, providing a travel distance of approximately 75 km on one battery charge. These findings demonstrate the feasibility of reusing batteries from electric cars with diminished capacity to power light electric vehicles. The results are relevant for scientific and technical professionals involved in electric vehicle development.

Enhancing electromagnetic compatibility and energy efficiency of electric vehicle charging stations

Problem. The article proposes a single-link structure for an electric vehicle charging station utilizing an active four-square rectifier with power factor correction. A Matlab model of the proposed charging station is developed, taking into account parameters such as the power network, the switches of the active rectifier, its automatic control system, and an equivalent model of the battery compartment. Additionally, a mathematical model for calculating static and dynamic losses is created based on polynomial approximation of the energy dependencies of IGBT modules. The analysis investigates power quality parameters, components of energy losses, and efficiency of the charging station across various charge currents and PWM frequencies during a full battery charge interval. Goal. The aim of this study is to propose a single-link structure for an electric vehicle charging station using an active four-square rectifier with power factor correction. It includes an analysis of power quality parameters, components of energy losses, and efficiency of the charging station at different charge currents and PWM frequencies during a full battery charge interval. Methodology. To achieve the goal, several key steps are considered. These include theoretical substantiation of the scheme of the electric microgrid charging station for electric vehicles with one-stage energy conversion, analysis of the battery connection scheme in the Tesla Model S electric car, research and calculation of efficiency, modeling of the charging station, development of a Matlab model of a microgrid system for the charging station, SAC analysis of battery charge voltage and current of a three-phase AV with PWM, modeling of losses in IGBT modules by polynomial approximation of dependencies, distribution of losses in the charging station system, and analysis of energy efficiency parameters. Results. The study presents the energy efficiency parameters of an external DC EV charging station using an active rectifier. It reveals that maximum efficiency of the system is achieved at minimum charge current. However, decreasing the charge current prolongs the charge process and slightly affects power quality parameters. Originality. A mathematical model for calculating static and dynamic losses was developed based on polynomial approximation of the energy dependencies of IGBT modules. The analysis encompasses power quality parameters, components of energy losses, and efficiency of the charging station across various charge currents and PWM frequencies during a full battery charge interval. Practical value. This study contributes to the further development of electric vehicles by improving the energy indicators of electric vehicle batteries and converters of electric vehicle charging stations, enabling fast charging modes. Active development is observed in each of these directions.

An environmental life cycle assessment of electric race car: a case study of eVarta

AbstractThe study concerns the life cycle assessment (LCA) of a prototype electric racing car, Formula Student, developed by students of the Poznan University of Technology under the name of eVarta. The main objective of this study is to identify critical environmental points and indicate key elements of the vehicle's life cycle, along with the impact of the assumptions made. In the first part of the work, a literature review and standard review are conducted to organise the information and methodological steps for the LCA components and their application in the subsequent stages of the study. The work focusses on defining the right assumptions, the process of data collection and its appropriate aggregation, as well as the creation of a functional structure for the object under study. SimaPRO software is used to perform the assessment. The results of the evaluation show the high importance of the vehicle transportation stage in the entire life cycle and the significant impact of the transport-related processes, mostly considering the fact that the eVarta is a concept racing car, used only in specific conditions of Formula Student races around the world. Most of the distances between races are covered using external transport means, and eVarta is used only for racing. The second main source of environmental impacts is related to the use of resources associated with the production of the high-voltage traction battery and the use of aluminium and related processes. eVarta is a custom concept race car, designed and built by the team of students from different faculties at Poznan University of Technology (Poland). As a prototype, eVarta demonstrates high levels of environmental burden related to the production of materials and techniques. The proportion of these impacts may be limited by using a 3D CAD model to improve the information flows regarding the production of all parts. Moreover, the reduction of the environmental impacts may be reached by: (a) enhancement of production of traction battery, (b) substitution of construction materials, and (c) improvements during use, e.g. implementation of energy recovery systems during braking. Graphical Abstract

An Improved Analysis of Distributed Resource Access Location and Capacity on Voltage Stability of Distribution Networks in Smart Grid

Concerns about how Distributed Energy Resources (DERs) may affect distribution network voltage stability have been brought up by the widespread usage of DERs in the elegant Grid. A Smart Grid connects a range of distributed energy resources (DERs) to the distribution network, including electric cars, wind turbines, and solar panels. This connection can alter the working conditions of the network. These changes can lead to voltage stability problems, which can affect the overall efficiency and reliability of the Smart Grid. Thus, there is a need for an improved analysis of the effects of Distributed Resource Access Location and Capacity (DRALC) on voltage strength in distribution networks. Here, we propose an improved analysis of the impact of DRALC on voltage stability in distribution networks in the Smart Grid. Our analysis considers the location and capacity of DERs and their effect on voltage stability using a combination of analytical and simulation methods. We first develop a mathematical model to represent the distribution network, which includes the DERs as voltage sources. Next, we use the voltage stability index and load flow analysis to evaluate the voltage stability of the network under different DRALC scenarios. Finally, we validate our analysis by performing simulations on a real-world distribution network.