Traditional Internal Combustion Engine Vehicles Research Articles

Comprehensive Comparison of Traditional Engines and Emerging Alternatives

As the natural environment deteriorates, electric vehicles will gradually replace internal combustion engines that use traditional fossil fuels. This paper compares traditional engines to alternatives regarding efficiency, emissions, price, and market share. In brief, alternative engines have advantages over traditional internal combustion engines in terms of efficiency, emissions, and long-term overhead, as evidenced by rising market share. In 2022, the share of electric vehicles in global sales has reached 14%. Compared to traditional internal combustion engine vehicles, electric vehicles have a higher well-to-wheel efficiency, up to more than twice of internal combustion engine vehicles. From a price perspective, electric vehicles have a higher original cost. However, lower maintenance costs allow electric vehicles to achieve the same cost as equivalent combustion engines in 5-8 years. Electric vehicles typically have low well-to-wheel and fuel emissions and are more sustainable. In the future, more research and development are needed for electric vehicles to make them suitable for most cities worldwide. At the same time, research into the traditional internal combustion engine should be addressed, as cleaner, more efficient engines such as the HCCI engines are already available for civilian use.

Review of Fuel-Cell Electric Vehicles

This paper presents an overview of the status and future prospects of fuel-cell electric vehicles (FC-EVs). As global concerns about emissions escalate, FC-EVs have emerged as a promising substitute for traditional internal combustion engine vehicles. This paper discusses the fundamentals of fuel-cell technology considering the major types of fuel cells that have been researched and delves into the most suitable fuel cells for FC-EV applications, including comparisons with mainstream vehicle technologies. The present state of FC-EVs, ongoing research, and the challenges and opportunities that need to be accounted for are discussed. Furthermore, the comparison between promising proton-exchange membrane fuel cell (PEMFC) and solid oxide fuel cell (SOFC) technologies used in EVs provides valuable insights into their respective strengths and challenges. By synthesizing these aspects, the paper aims to provide a comprehensive understanding and facilitate decision-making for future advancements in sustainable FC-EV transportation, thereby contributing to the realization of a cleaner, greener, and more environmentally friendly future.

Blockchain based crowdsourcing framework for Vehicle-to-Vehicle charging

Electric Vehicles (EVs) have become a promising solution to entirely replace traditional internal combustion engine vehicles. EV owners face the “Range Anxiety” problem which is the fear that their remaining charge would not be enough to reach their destination. Vehicle-to-Vehicle (V2V) charging is currently being used in exchanging energy between EVs. Most of the existing energy V2V frameworks depend on a centralized server that manages the energy exchange. However, these solutions may suffer from privacy leakage and misbehaving platforms. To overcome these limitations, the paper proposes a blockchain-based crowdsourcing framework for V2V charging. The framework features include registering users, maintaining user information, clustering requesters (charging tasks), collecting preferences lists from requesters and providers, and lastly selecting the requester-provider charging pair as well as the corresponding meeting point. These features are implemented using three types of smart contracts: User Management Contract, Task Management Contract, and Solution Management Contract while guaranteeing the transparency of the system and overcoming the main limitations of the centralized solutions. Experiment results with real-life dataset show that the proposed framework achieves a comparable performance at reasonable paid costs and execution times.

The transition to electrified vehicles: Evaluating the labor demand of manufacturing conventional versus battery electric vehicle powertrains

The shift from traditional internal combustion engine vehicles (ICEVs) to electric vehicles (EVs) has raised concerns about displacement of automotive manufacturing labor. Prior studies have mixed findings, and have been hindered by a lack of shop floor-level data on the labor hours required for ICEV and EV manufacturing. We collect detailed data from leading automotive manufacturers on the production process steps and labor inputs required to build key ICEV and battery electric vehicle (BEV) powertrain components. Our novel data set covers 252 process steps, with data on a further 78 process steps from the existing literature. We build a production process model that estimates the labor hours required to produce ICEV and BEV powertrain components at different production volumes and labor efficiency levels. We find that, accounting for production and assembly of battery packs, the labor intensity required for the manufacturing of BEV powertrain components is larger than for ICEV powertrain components. This difference in labor intensity holds even when comparing the highest-efficiency estimates for BEV production with the lowest efficiency-estimates for ICEVs. This finding depends on our shop-floor operations modeling approach and could not be derived from recent approaches focusing on part counts. Our results imply that vehicle electrification could lead to more automotive manufacturing jobs, at least in the short- to medium-term. While there are potential jobs to support transitions for incumbent automotive workers, the feasibility of these transitions will depend on geographic co-location of new battery production capacity with current ICEV production sites, and on matching between the skills of the automotive workforce and the demands of new EV jobs.

Battery Management in Electric Vehicle Routing Problems: A Review

The adoption of electric vehicles (EVs) has gained significant momentum in recent years as a sustainable alternative to traditional internal combustion engine vehicles. However, the efficient utilization of batteries in EVs, coupled with the growing demand for sustainable transportation, has posed complex challenges for battery management in the context of electric vehicle routing problems in a broad sense, which includes vehicle routing problems, team orienteering problems, and arc routing problems, all of them using EVs. This paper presents a comprehensive review of the state-of-the-art approaches, methodologies, and strategies for battery management in each of the aforementioned optimization problems. We explore the relevant factors influencing battery performance and the interplay between routing, charging, and energy management in the context of EVs. The paper also discusses the advances in optimization algorithms, vehicle-to-grid integration, and intelligent decision-making techniques aimed at enhancing the range, reliability, and sustainability of EV operations. Key findings indicate a paradigm shift towards addressing uncertainties, dynamic conditions, and synchronization challenges inherent in large-scale and dynamic routing problems within the context of EVs that require efficient battery management.

Sustainability of Electric Vehicles Using Artificial Intelligence

Electric vehicles (EVs) are widely regarded as a more environmentally sustainable transportation option compared to traditional internal combustion engine vehicles. However, concerns persist regarding the sustainability impacts of EV battery manufacturing, specifically the mining of lithium used in lithium-ion batteries. This literature review examines the potential for artificial intelligence (AI) to improve the sustainability of lithium mining and battery manufacturing for EVs. An extensive literature search yielded insights into the environmental impacts of lithium mining such as high water usage, carbon emissions, and soil contamination. These impacts present a challenge to the sustainability narrative of EVs. However, researchers have identified numerous applications for AI across the lithium-ion battery supply chain that could mitigate these effects. From optimizing mineral exploration and mining operations to recycling spent batteries, AI solutions show promise to reduce the lifecycle impacts of lithium-ion batteries. Additional research is still needed to quantify these potential improvements and implement AI responsibly. Furthermore, technology alone cannot address the complex socio-economic challenges associated with lithium mining. Ultimately, a combination of technological innovation and ethical, inclusive resource management will be required to truly transition to sustainable EV mobility. Keywords: electric vehicles, lithium-ion batteries, lithium mining, sustainability, artificial intelligence.

Adaptive Integrated Thermal Management System for a Stable Driving Environment in Battery Electric Vehicles

With an increase in global warming, battery electric vehicles (BEVs), which are environmentally friendly, have been rapidly commercialized to replace conventional vehicles with internal combustion engines. Unlike traditional internal combustion engine vehicles, the powertrain system of BEVs operates with high efficiency, resulting in lower heat generation. This poses a challenge for cabin heating under low-temperature conditions. Conversely, under high-temperature conditions, the operating temperature of a high-voltage battery (HVB) is lower than the ambient air temperature, which makes cooling through ambient air challenging. To overcome these challenges, in this study, we proposed an integrated thermal management system (ITMS) based on a heat pump system capable of stable thermal management under diverse climatic conditions. Furthermore, to assess the ability of the proposed ITMS to perform thermal management under various climatic conditions, we integrated a detailed powertrain system model incorporating BEV specifications and the proposed ITMS model based on the heat pump system. The ITMS model was evaluated under high-load-driving conditions, specifically the HWFET scenario, demonstrating its capability to perform stable thermal management not only under high-temperature conditions, such as at 36 °C, but also under low-temperature conditions, such as at −10 °C, through the designated thermal management modes.

Electric Vehicle Health Monitoring with Electric Vehicle Range Prediction and Route Planning

The automotive industry is experiencing a revolutionary wave due to the rapid spread of electric vehicles (EVs), which is paving the way for a fundamental and long-lasting revolution in the way we approach transportation. The global movement to reduce greenhouse gas emissions and lessen the environmental impact of traditional internal combustion engine vehicles has seen a significant boost in the popularity of electric vehicles as people come together to support environmentally conscious and sustainable mobility solutions. But the ecology surrounding electric vehicles must continue to flourish if the particular problems that EVs present are to be successfully addressed. Chief among these are the formidable foes of range anxiety and battery health management. Range anxiety is a real issue felt by many potential EV owners worry about becoming stuck because their battery has run out before reaching their destination. This psychological barrier is very noticeable and makes present and future EV owners doubtful. In addition, the longevity and health of EV batteries are essential to their continued effectiveness and affordability. The driving range and operating efficiency of the vehicle are directly affected by the gradual degradation of the battery due to several factors like aging, charging patterns, and temperature. This research presents an integrative and holistic approach to address these pressing issues, enhancing and elevating the whole EV ownership experience by combining Electric Vehicle Health Monitoring (EVHM) with Electric Vehicle Range Prediction (EVRP) and Route Planning (EVRP). Combining these three essential elements creates an all-encompassing plan created to not only lessen these enormous obstacles but also accelerate the switch to electric vehicles by giving consumers the knowledge and assurance they require for a smooth, eco-friendly, and sustainable mobility in the future.

Zero emission freight transport and impacts on last mile delivery


 
 
 This literature review explores mainly the challenges and potential solutions in urban freight transportation, for last-mile logistics. The growing number of delivery vehicles in urban areas has led to problems such as traffic congestion, competition for parking spaces, noise, and air pollution. To address these issues, the paper focuses on the last mile problem in transportation logistics and the potential of disruptive innovations, a potential of disruptive innovations such as Unmanned Aerial Vehicles (UAVs) and Autonomous Delivery Robots (ADRs) as alternatives to traditional Internal Combustion Engine (ICE) vehicles. It highlights the drastic operational differences between aerial drones and ADRs and the need for changes in operational procedures to fully leverage these technologies. The study also discusses routing strategies and delivery routes, emphasizing the shift from one-route delivery to a point-to- point model with the advent of autonomous vehicle technologies. The paper concludes that while these technologies can reduce costs and emissions, their effectiveness depends on the specific urban setting and operational factors. 
 
 

A REVIEW ON ELECTRIC VEHICLE

Plug-in hybrid electrics vehicles (PHEVs) have been extensively studied, and advancements in power electrics and energy storage have made them quite competitive with traditional internal combustion engine vehicles (ICEVs). By using optimized control strategies and energy management systems (EMS), PHEVs can become even more efficient. In my own words, PHEVs are vehicles that combine the benefits of electric and gasoline power to provide a good driving range and fuel economy. Battery and super capacitor technologies are also being explored to increase the energy capacity of PHEVs. It's exciting to see how these advancements are shaping thefuture of transportation

(Keynote) Rapid Thermal Management for Fast Charging of Energy-Dense Lithium-Ion Batteries

Charging time trauma refers to the pain experienced by electric vehicle (EV) owners when the ‘refill’ time is significantly longer than that of traditional internal combustion engine vehicles. Worsening this trauma is the inconsistency of EV charging; for example, the same EV may take five times longer to charge on a cold day. Faster charging will alleviate this pain point and aid in the mass adoption of EVs, crucial for meeting near-term carbon emission goals. Reaching this goal will require smarter and more rapid thermal management to provide significantly faster safe charging.The results from the 2022 Nature article “Fast charging of energy-dense lithium-ion batteries” (DOI 10.1038/s41586-022-05281-0) where 265 Wh/kg lithium-ion pouch cells were charged from 0-70% in less than 12 minutes, 2,000 times in a row before end-of-life, will be presented. These cells used only proven materials, including a liquid electrolyte made from industrially-used components, and energy-dense, EV-grade electrodes. Key to success was smart cell thermal management. More recent advancements, including multi-cell battery-level data, will also be discussed. Figure 1

Optimizing Electric Vehicle Charging Station Location on Highways: A Decision Model for Meeting Intercity Travel Demand

Electric vehicles have emerged as one of the top environmentally friendly alternatives to traditional internal combustion engine vehicles. The development of a comprehensive charging infrastructure, particularly determining the optimal locations for charging stations, is essential for the widespread adoption of electric vehicles. Most research on this subject focuses on popular areas such as city centers, shopping centers, and airports. With numerous charging stations available, these locations typically satisfy daily charging needs in routine life. However, the availability of charging stations for intercity travel, particularly on highways, remains insufficient. In this study, a decision model has been proposed to determine the optimal placement of electric vehicle charging stations along highways. To ensure a practical approach to the location of charging stations, the projected number of electric vehicles in Türkiye over the next few years is estimated by using a novel approach and the outcomes are used as crucial input in the facility location model. An optimization technique is employed to identify the ideal locations for charging stations on national highways to meet customer demand. The proposed model selects the most appropriate locations for charging stations and the required number of chargers to be installed, ensuring that electric vehicle drivers on highways do not encounter charging problems.

Tax policy or carbon emission quota: A theory on traditional ICEV transportation regulation

This study investigates the environmental consequences of consumers opting for traditional internal combustion engine vehicles (ICEVs), resulting in heightened pollution. Given the critical importance of addressing environmental degradation and its impact on societal welfare, our research aims to provide insights into effective policymaking strategies. In an ideal scenario, a benevolent planner would equitably distribute wealth, forming the first-best policy. Recognizing the impracticality of this ideal, we propose two viable second-best policies: an income-based tax and the implementation of a carbon emission quota. Theoretical analysis highlights the efficacy of the tax policy in pollution reduction, particularly with the growing number of mid-income electric vehicle consumers. The optimal tax policy adeptly navigates the delicate balance between pollution and income effects. Furthermore, we establish that the optimal pollution quota under the carbon emission policy is lower than in both competitive and first-best scenarios. A numerical comparison of the four equilibrium outcomes underscores these findings. In addition, we advocate for a blockchain-based decentralized carbon emission quota trading platform to digitize and optimize allocation and compliance processes, fostering more efficient and transparent environmental management.

Electrification of Motorway Network: A Methodological Approach to Define Location of Charging Infrastructure for EV

Environmental issues have reached global attention from both political and social perspectives. Many countries and companies around the world are adopting measures to help change current trends. Awareness of decarbonization in the transportation sector has led to an increasing development of energy storage systems in recent years, especially for ground vehicles. Batteries, due to their high efficiency, are one of the most attractive energy storage systems for vehicle propulsion. As for road vehicles, the growing interest in Electric Vehicles (EVs) is motivated by the fact that they reduce local emissions compared to traditional Internal Combustion Engine (ICE) vehicles. The purpose of the paper is to present a study on how to plan and implement vehicle charging infrastructure on motorways. In particular, a specific road in Italy is analyzed: the motorway A1 from Milan to Naples with a length of about 800 km. This motorway can be considered representative because it passes through some of Italy’s most important cities and regions and may represent the backbone of Italy. A useful model for defining the optimal location of electric vehicle charging stations is presented within the paper. Starting with the data on the average daily traffic flows passing through the main nodes of the motorways section, the demand for the potential vehicles needed to define the number and dimension of charging stations and provide an adequate supply is estimated. The analysis was performed considering five-time horizons (year 2022 to year 2025) and four Scenarios involving the installation of 4, 8, 16, and 32 Charging Stations (CSs) in each service area, respectively.

Analysis on the Thermal Behavior of Lithium-Ion Battery with Nickel-Rich Cathode and Silicon-Carbon Composite Anode

<div>Compared with traditional internal combustion engine vehicles, electric vehicles still have shortfall in driving range and energy replenishment time. In order to continuously improve the driving range of electric vehicles, the high-nickel/silicon-carbon lithium-ion battery with high energy density is a promising industrialized application route. However, with the increase of battery energy density, the heat generation of battery usually increases, which will inevitably bring greater heat dissipation problems to the battery thermal management system. To design a good thermal management system, the first thing is to accurately measure and deeply understand the heat generation characteristics of the battery. In this work, the heat generation behavior of a high-nickel LiNi<sub>0.8</sub>Co<sub>0.1</sub>Mn<sub>0.1</sub>O<sub>2</sub>/silicon-carbon pouch-type battery under different operating conditions were tested by an isothermal battery calorimeter. The influence of current rate, current direction, and operating temperature on the heat generation characteristics of the battery was systematically analyzed. A comparison between heat generation power of batteries with different cathode/anode materials was provided. The research results of this article can deepen the understanding of the heat generation behavior of LiNi<sub>0.8</sub>Co<sub>0.1</sub>Mn<sub>0.1</sub>O<sub>2</sub>/silicon-carbon battery and provide guideline for the design of thermal management system.</div>

Mathematical Analysis of the Impact of French Standardization Strategy and Electric Vehicle Development on the Breakthrough Development of EVs in China

The problems of operating range and costs are the two most critical bottlenecks restricting the extensive application of electric vehicles (EVs) in China and some other countries. There are also some prominent problems in China’s EVs, which lead to poor competitiveness of EVs compared with traditional internal combustion engine vehicles. This paper analyzes the key mathematical factors restricting the development and popularization of EVs in China from the aspects of strategic policy, sales situation, and self-problems. For the best-selling family cars in China, select the representative models with the same body structure, and make statistics on various parameters most concerned by consumers, establish a database through data statistics and analysis software. Through summarizing France’s standardization development strategy and relevant issues reflected by the development data of its EVs, this paper puts forward the hypothesis leading the development of EVs through standardization to enhance their competitiveness, gives the specific suggestions, and briefly analyzes the feasibility from the aspects of product situation. The research content of this paper provides a certain basis and ideas for the future research work.

A REVIEW ON INTEGRATION OF ELECTRIC VEHICLES AND OPTIMAL POWER MANAGEMENT STRATEGY FOR SUSTAINABLE DEVELOPMENT

The integration of electric vehicles (EVs) into our transportation system is a pivotal step towards sustainable development. EVs are gaining traction as a cleaner and more energy-efficient alternative to traditional internal combustion engine vehicles. Their adoption holds the promise of reducing greenhouse gas emissions and decreasing our reliance on fossil fuels, contributing significantly to environmental sustainability .One of the critical aspects of effective EV integration is the development and implementation of optimal power management strategies. These strategies play a pivotal role in ensuring that the charging and discharging of EV batteries are not only efficient but also seamlessly integrated with the existing power grid infrastructure. An optimal power management system takes into consideration factors such as load balancing, peak demand management, and the integration of renewable energy sources, making it a key component of a sustainable and resilient energy ecosystem. By efficiently scheduling when and how EVs charge or discharge, these strategies can reduce the strain on the electrical grid during peak periods, lower electricity costs, and minimize the carbon footprint associated with charging. Moreover, they can contribute to grid stability and reliability, making the entire energy system more sustainable. This research explores the synergistic potential of EVs and smart grid technologies, aiming to create a harmonious relationship between transportation and energy systems. Key Words: Electric Vehicles, Sustainable Development, Optimal Power Management, greenhouse gas emissions, fossil fuels, clean environment, smart grid technology.

Signal pre-processing techniques for fault signature enhancement in a bearing health monitoring system used in the automotive industry

Traditional internal combustion engine vehicles have low transmission bearing failure rates in their lifespans. However, the prolonged lifespan of electric and autonomous vehicles can surpass the reliable life of bearing designs, which poses a risk of bearing failure and loss of propulsion. Compared to replacing bearings on a fixed schedule to ensure reliability, a bearing health monitoring system is a more cost-effective solution. Despite extensive research on bearing condition monitoring, implementing well-known methods such as vibration spectrum analysis in vehicles can be challenging due to vibrations from vehicle components and the road. This paper explores and compares the effect of various pre-processing techniques on the spectrum of a faulty bearing with various fault levels. To achieve this objective, faults with the width size of 0.1 mm (mild), 0.5 mm (moderate) and 2 mm (severe) were injected into the inner race of a ball bearing. A bench setup was then used to capture the vibrations of multiple vehicle components including the faulty ball bearing under various speed/ load conditions. Phase domain transform, envelope and Fourier transform were used as the core signal processing steps, and advanced signal processing methods for removing discrete frequencies from other components and enhancing the fault signature were explored. 4 health indicators were then developed from the vibration spectrum of the vibration signals and calculated for the captured data. Next, for each fault level, the area under Receiver operating characteristic (ROC) curve was calculated and used as a metric to compare the performance of our health monitoring system for classification of faulty and healthy bearings. For our best health indicator, the results show that applying minimum entropy deconvolution, and spectral kurtosis-based band pass filtering increases the ROC area from 0.40, 0.99, 1.0 to 0.86, 1.0 and 1.0 for the mild, moderate, and severe inner race faults, respectively. This implies that although applying only phase domain transform, envelope and Fourier transform might be enough for moderate and severe faults, advanced signal processing is needed to enhance the fault signature for early detection of mild faults.

Technology and limitation of electrification of transportation

In the modern world, electric vehicles (EVs) are becoming more and more prevalent, and many individuals are beginning to consider getting one for their mobility. In comparison to traditional internal combustion engine vehicles, EVs are more environmental-friendly, have higher energy conversion efficiency and produce lower noise. However, in terms of electrification of transportation, EVs also have some inherent limitations. This paper provides an overview of electrification of transportation. First, this paper will focus on the related technologies such as motor drive technology, power electronic technology and battery management. In addition, the limitations of the electrification of transportation, include range anxiety, long charging time, charging station accessibility and unsatisfactory performances in extreme temperatures, will also be presented. Despite these challenges, EVs still exhibit promises for further development and will play a leading role in transportation electrification. Considering the technological factors will help address the issues and push the future development of EV forward.

Superhydrophobic Microchannel Heat Exchanger for Electric Vehicle Heat Pump Performance Enhancement

Battery-powered electric vehicles (EVs) have emerged as an environmentally friendly and efficient alternative to traditional internal combustion engine vehicles, while their single-charge driving distances under cold conditions are significantly limited due to the high energy consumption of their heating systems. Heat pumps can provide an effective heating solution for EVs, but their coefficient of performance (COP) is hampered by heat transfer deterioration due to frost accumulation. This study proposes a solution to this issue by introducing a microchannel heat exchanger (MHE) with superhydrophobic surface treatment (SHST) as a heat pump evaporator. A computational fluid dynamics MHE model and a dynamic heat pump model are developed and rigorously validated to examine the detrimental impact of frost accumulation on heat transfer, airflow resistance, and heat pump performance. When the frost layer thickness is 0.8 mm at a given air-side velocity of 1.0 m/s, the air-side heat transfer coefficient can be reduced by about 75%, and the air-side pressure drop sharply increases by 28.4 times. As frost thickness increases from 0 to 0.8 mm, the heating capacity drops from 3.97 to 1.82 kW, and the system COP declines from 3.17 to 2.30. Experimental results show that the frost thickness of the MHE with SHST reaches approximately 0.4 mm after 30 min, compared to that of 0.8 mm of the MHE without SHST, illustrating the defrosting capability of the superhydrophobic coating. The study concludes by comparing the performance of various heating methods in EVs to highlight the advantages of SHST technology. As compared to traditional heat pumps, the heating power consumption of the proposed system is reduced by 48.7% due to the defrosting effect of the SHST. Moreover, the single-charge driving distance is extended to 327.27 km, an improvement of 8.99% over the heat pump without SHST.