Internal Combustion Engine Vehicles Research Articles

Laboratory characterization of VOC evaporative emissions from light-duty plug-in hybrid electric vehicles: Environmental impact comparison with conventional vehicles.

Vehicle electrification has been proposed as a strategy for decarbonizing the transport sector. However, companies operating fleets of light-duty internal combustion engine vehicles (ICEVs) for personnel and freight transportation still lack the data and decision-making tools necessary to evaluate the transition to electric vehicles (EVs). This study proposes a novel methodology that combines the use of web applications with longitudinal vehicle dynamics to determine energy consumption and regenerative braking potential. In addition, it incorporates energy consumption data, taxes, subsidies and vehicle discounts to conduct a comparative analysis of the total cost of ownership of EVs versus IECVs. The proposed methodology was applied to evaluate the feasibility of an energy transition in a fleet of vans and pickup trucks used for transporting personnel and materials. The results show that the model can estimate energy consumption with an average error of 7.6% compared to monitored data. Replacing 10 ICEVs with 5 electric vans and 5 electric pickup trucks could reduce energy consumption by up to 62%. The operating cost of the electric van is 8.5% lower than its ICEV counterpart, while the electric pickup achieves a 13.8% reduction in operating costs compared to the combustion model. The technical findings and the methodology of this study are expected to provide a solid basis for companies to evaluate the energy and economic feasibility of electrifying their fleets.

The automotive industry is witnessing a paradigm shift towards electric and hydrogen-powered vehicles, underscoring the pressing need for advancements in fuel efficiency for Internal Combustion Engine (ICE) vehicles to sustain their relevance. This paper presents a comprehensive project aimed at investigating and designing a lightweight three-wheeled vehicle for participation in the 2024 Shell Eco-marathon (SEM) prototype class competition, with a targeted fuel efficiency of 1500 km/L. Five primary focus areas were identified: Chassis, Bodywork & Canopy, Powertrain, Gearing & Clutch, and Vehicle Dynamics. Adhering to the Shell Eco-marathon (SEM) rules and regulations, each section underwent meticulous design and investigation processes, leveraging state-of-the-art computer software including Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Computer-Aided Design (CAD), and numerical modelling. This paper presents a comprehensive investigation and design approach towards achieving optimal fuel efficiency in a lightweight three-wheeled vehicle. With the ever-growing concern for environmental sustainability and the increasing demand for fuel-efficient transportation solutions, the development of lightweight vehicles has garnered significant attention. Through rigorous analysis and experimentation, this study explores the key factors influencing fuel efficiency in three-wheeled vehicles, including aerodynamics, vehicle dynamics, powertrain optimisation, and material selection. Leveraging advanced computational tools and experimental validation, novel design strategies are proposed to minimize energy consumption while maintaining structural integrity and safety standards. The research outcome provides valuable insights into the intricate balance between weight reduction, aerodynamic performance, powertrain efficiency, and material utilisation. Moreover, the study investigates the potential impact of emerging technologies, such as electric propulsion systems and lightweight materials, on enhancing the fuel efficiency of three-wheeled vehicles. The interdisciplinary nature of this investigation contributes to the ongoing discourse on sustainable mobility and underscores the potential of lightweight three-wheeled vehicles as a viable solution for achieving optimal fuel efficiency in urban environments. The resulting designs and concepts were meticulously crafted to align with the predefined objectives of each section. The culmination of these efforts represents a coherent framework poised for manufacturing, with most concept designs deemed ready for implementation in the vehicle assembly phase. Nonetheless, certain components have been identified as necessitating further development to meet the requisite standards. This study not only contributes to the advancement of fuel-efficient ICE vehicles but also lays the groundwork for future research endeavours in automotive engineering and design.

Replacement of internal combustion engine vehicles with battery electric vehicles (EVs) is expected to impact air quality. Previous projections, often relying on emissions inventories of precursors with high uncertainties, have yielded results that vary by model parameters and assumptions. There remains little empirical investigation of the real-world effects, particularly for the low yet growing levels of electrification in the United States. Here county-level vehicle registrations and measurements from ground-level air monitors from 2018 through 2023 were used to investigate the impacts of EV penetration on annual and seasonal concentrations of criteria air pollutants in the United States. Fixed effects regression analysis revealed that rising EV penetration was associated with reductions in mean annual concentrations of nitrogen oxides (NOx as the sum of NO2 and NO), carbon monoxide (CO), and fine particulate matter (PM2.5) and in mean summer season concentrations of ozone (O3). By contrast, there was a potential increase in sulfur dioxide (SO2). The findings demonstrate empirical improvements in air quality associated with EV adoption yet highlight the risk of a continued reliance on fossil fuels. Strategic policies that support enhanced EV adoption must support commensurate expansion of renewable energy access in order to maximize the air quality benefits of the technology.

With rising travel demand and the need to tackle both the air quality and climate change challenges caused by fossil fuel vehicles, there is an urgent need to transition to cleaner and more sustainable fuels. While lithium-ion battery electric vehicles (BEVs) produce no emissions during operation, they increase electricity consumption, affecting emissions from that activity. Furthermore, there is an ongoing debate about the overall cleanliness of lithium-ion batteries when assessing emissions throughout their lifecycle compared to fossil fuels. To address these concerns, we use the Global Change Analysis Model (GCAM) integrated assessment model (IAM) to evaluate criteria air pollutants and carbon dioxide (CO 2 ) emissions across four scenarios of increasing BEV adoption in the United States (US). We include emissions from fuel and battery production, vehicle manufacturing, and operation for both BEV and fossil-based internal combustion engine (ICE) vehicles. Results indicate that each additional kWh of lithium-ion battery output leads to an average reduction of 220 kg of CO 2 in 2030 and 127 kg of CO 2 in 2050. There are also substantial decreases in CO emissions, although relatively small changes in SO 2 and NO X . In a life cycle assessment, all else equal, the CO 2 emissions associated with BEVs are 30% higher than those of ICE vehicles during the first two years. However, after the second year, BEVs result in a reduction in cumulative CO 2 emissions. Accounting for the effects of both air pollution and climate change, the economic value of the damages attributable to ICEs over their lifetime is currently 2 to 3.5 times that of BEVs. This ratio increases over the coming decades as the emissions intensity of the electricity sector decreases.

As more and more technology advancement of transportation and electrification of heating system, residents nowadays usually had the less demand for using the fossil fuel which causes the carbon emission. For instance, most peoples vehicles had converted from ICE (internal combustion engine) vehicles to the BEVs (Battery electric vehicles). Another example, domestic heating pumps, use electricity instead of using fossil fuel (natural gas, propane, heating oil, charcoal etc.) nowadays to transfer heat from a cool space to a warm space and reverse this process if in summer. Electrification refers to the source of generating the electricity and their usage are renewable such as photovoltaic, wind electricity, hydrogen-powered electricity etc. These source of electricity can supply the electric vehicles and the electric heat pumps sufficiently. However, the cost of source of generating the electricity and technology impede the electrification. For materials perspective, like battery, electromotor, conductors & insulators, heat exchange, and refrigeration materials. These materials can determine the efficiency, energy density and the life span. Nevertheless, these materials are also limited and difficult to manufacture. Thus, this paper will provide the clear and executable ideas for the strategies and material selection of small cars and heat pump renovations in electrification and explain the limitation in mechanism perspective.

Under the backdrop of low-carbon transformation in the global automotive industry, New Energy Vehicles (NEVs) in Chinese market have achieved market dominance over traditional Internal Combustion Engine (ICE) vehicles through business model innovation. This study employs case analysis and SWOT methodology, focusing on leading NEV manufacturers in China (Tesla, BYD, NIO, Huawei, etc.), to systematically examine successful innovations in three key areas: sales strategies, product definition, and ecosystem development. Key findings include: 1. Motor technology has disrupted the engine performance-based premium pricing system; 2. Integrated hardware-software-aftermarket ecosystems have established new competitive barriers; 3. Significantly shortened R&D and manufacturing cycles have transformed traditional automotive development systems; 4. Direct/hybrid sales models have markedly improved channel efficiency and quality (35% increase in customer satisfaction). The research confirms that NEVs' competitive advantage stems from "technology + model" dual drivers, while also highlighting challenges including inadequate charging infrastructure (rural coverage <12%) and consumer concerns regarding safety and range. The core contribution of this study lies in demonstrating that Chinese NEV leadership stems not merely from technological breakthroughs, but more fundamentally from systematic business model innovation. These findings provide both a replicable framework for traditional automakers transitioning to electrification and new market entrants, as well as theoretical foundations for policymakers to optimize industry support measures. NEV business practices are actively redefining the competitive rules and development trajectory of the global automotive industry.

Understanding vehicle acceleration behavior during intersection departures is critical for advancing traffic safety, sustainable mobility, and intelligent transport systems. This study presents a high-resolution kinematic analysis of 714 vehicle departures from signalized intersections, encompassing straight crossings, left turns, and right turns, and involving a diverse sample of internal combustion engine (ICE), hybrid electric (HEV), and battery electric vehicles (BEV). Using synchronized Micro Electro-Mechanical Systems (MEMS) accelerometers and Real-Time Kinematic (RTK)-GPS systems, the study captures longitudinal acceleration and velocity profiles over fixed distances. Results indicate that BEVs exhibit significantly higher acceleration and final speeds than ICE and HEV vehicles, particularly during straight crossings and longer left-turn maneuvers. Several mathematical models—including polynomial, arctangent, and Akçelik functions—were calibrated to describe acceleration and velocity dynamics. Findings contribute by modeling jerk and delay propagation, supporting better calibration of AV acceleration profiles and the optimization of intersection control strategies. Moreover, the study provides validated acceleration benchmarks that enhance the accuracy of forensic engineering and road accident reconstruction, particularly in scenarios involving intersection dynamics, and demonstrates that BEVs accelerate more rapidly than ICE and HEV vehicles, especially in straight crossings, with direct implications for traffic simulation, ADAS calibration, and urban crash analysis.

Electric vehicles (EVs) are a transformational and environmentally friendly means of transportation that are powered by electricity and are increasingly being acknowledged as a sustainable alternative to traditional internal combustion engine vehicles. This paper investigates the field of EV charging standards and explores the innovative charging technologies in North America, Europe, and China. It underscores the importance of established schemes in supporting smooth charging processes which accordingly facilitate the global adoption of EVs. Advanced charging technologies, including Vehicle-to-Grid (V2G) systems, wireless charging, and off-grid solutions, highlighting their potential to transform the EV ecosystem, are introduced. The on-ground deployment of these technologies is demonstrated by exploring a few real-world implementation examples. The paper also emphasizes how charging regulations and standards can boost sustainability, mitigate the concerns of limited driving ranges, and establish resilient infrastructure. The transition to electrified transport depends on the deployment of interoperable charging standards, advances in charging technologies, and coordinated business models that enable renewable-integrated and storage-enabled charging infrastructure.

Global transportation sector is experiencing a profound transformation with the rapid adoption of electric vehicles (EVs) as a cleaner and more sustainable alternative to conventional internal combustion engine vehicles. Over the past decade, advances in battery technology, powertrain efficiency, and vehicle-to-grid (V2G) integration have significantly accelerated EV development and deployment. This comprehensive review summarizes recent technological innovations while also analyzing the critical challenges hindering large-scale EV adoption. Key obstacles include limited charging infrastructure, grid capacity constraints, standardization issues, high upfront costs, and concerns about charging convenience and range anxiety. Furthermore, disparities in urban and rural charging access raise concerns about equity and inclusiveness in the EV transition. Recent research and pilot programs demonstrate the potential of emerging solutions such as smart charging, wireless power transfer, micro grid integration, and coupling EV charging with renewable energy sources to alleviate grid stress and enhance sustainability. Additionally, innovative business models and policy interventions, including government incentives and standardization efforts, are essential to promote investment in fast-charging networks and interoperability. The integration of stationary energy storage systems, time-of-use pricing strategies, and advanced energy management systems offers promising pathways to achieve efficient load balancing and demand-side flexibility. Finally, future research should focus on harmonizing charging standards, enhancing user experience, and fostering cost-effective, large-scale deployment strategies to accelerate the global transition toward sustainable, electrified transportation systems.

Against the backdrop of global efforts to combat climate change and promote the transition of the transportation sector toward sustainability-given that transportation is a major source of greenhouse gas emissions-the United Kingdom has emerged as a leader in the shift to electric vehicles (EVs). The country has implemented ambitious policies, including a ban on the sale of new petrol and diesel cars from 2030 and a mandate for all new cars and vans to achieve 100% zero emissions by 2035. Simultaneously, evolving consumer preferences for sustainable mobility have contributed to a rapidly growing yet intensely competitive EV market. Within this context, Arnold Clark faces dual pressures: aligning with national carbon neutrality goals while sustaining its market leadership. The company must also navigate a series of complex challenges: first, traditional competitors and direct-to-consumer EV manufacturers are aggressively pursuing market share through various purchase incentives; second, the EV industry depends on intricate global supply chains, with battery production and raw material procurement heavily reliant on international markets, creating risks of potential disruptions; third, consumers continue to express concerns regarding EV technology sustainability-particularly battery lifespan and reliability-as well as limitations in charging infrastructure and range anxiety compared with conventional internal combustion engine vehicles.

Overlooked crisis: cold temperature amplifies particle number emissions from gasoline vehicles.

Accurate fuel consumption prediction is crucial for focusing on pressing environmental concerns, optimising fuel efficiency, and reducing operational costs in the transportation sector. Despite its importance, existing prediction models often struggle with high dimensionality, complexity, and low computational speed, simultaneously achieving high prediction accuracy. To address these gaps, this study explores an approach using Vehicle Energy Data to predict the fuel consumption of Internal Combustion Engine vehicles with enhanced performance. Firstly, the Autoencoder was used on a large real-world vehicle energy dataset to convert into a low-dimensional spaces. Secondly, low-dimensional data was fed to the Extreme Gradient Boosting model to predict fuel consumption accurately. To prove the effectiveness of the proposed model, its performance was compared with state-of-the-art approaches. The results revealed that the proposed model performs better than other state-of-the-art models with 98% accuracy. Further sensitivity analysis disclosed that the proposed model simultaneously reduces the computational complexity and increases the predictive performance of the downstream model. The study demonstrates an effective and innovative method for analysing fuel consumption during real vehicle operating conditions in terms of accuracy and real-time capability. This study can be applied to other high-dimensional data to extract various insights regarding fuel consumption.

Hybrid systems have recently become widespread in motorsports due to advantages such as increased power through the use of electric motors and reduced fuel consumption thanks to regenerative braking. Achieving high performance from a hybrid powertrain requires a highly efficient control system for managing power flows between the internal combustion engine (ICE) and the electric motor. The goal of this study is to develop a control algorithm for a hybrid powertrain aimed at minimizing lap times compared to traditional vehicles equipped with an ICE. To achieve this objective, a mathematical vehicle model based on the tractive balance equation was used. Lap time simulations were conducted for both a traditional ICE vehicle and a hybrid system. The results showed that the hybrid vehicle has a significant advantage in lap time; however, the energy from a fully charged battery would only be sufficient for two laps. To address this issue, a hybrid system control algorithm is proposed, which maintains the energy balance of the battery throughout the entire lap while still providing better lap times compared to a vehicle equipped with a traditional ICE.

As many countries transition to electric vehicles (EVs) to reduce tailpipe emissions from internal combustion engine vehicles (ICEVs), both vehicle types continue to generate non-exhaust particulate matter (PM), including tire wear, brake wear, road surface wear, and particularly road dust resuspension. Among these, road dust resuspension is a major contributor to non-exhaust PM. While factors such as vehicle weight and drivetrain configuration have been extensively studied in fleet-level research, direct comparisons between ICEVs and EVs of the same model have not been explored. This study investigates the effects of drivetrain, vehicle weight, and payload on road dust resuspension emissions from ICEV and EV models. Two experimental approaches were employed: (1) acceleration from 0 to 60 km/h, and (2) a simulated real-world driving cycle (RDC). Each test was conducted under both light and heavy payload conditions. The results show that the EV consistently emitted more PM than the ICEV during both acceleration and RDC tests, based on factory-standard vehicle weights. Under identical vehicle weight conditions, the EV demonstrated higher PM resuspension levels, likely due to its higher torque and more immediate power delivery, which increases friction between the tires and the road, particularly during rapid acceleration. Both vehicle types exhibited significant increases in PM emissions under heavy payload conditions. These findings underscore the importance of addressing non-exhaust emissions from EVs, particularly road dust resuspension, and highlight the need for further research into mitigation strategies, such as vehicle lightweighting.

At the international level, new measures, policies, and technologies are being developed to reduce greenhouse gas emissions and, more broadly, air pollutants. Road transportation is one of the main contributors to such emissions, as vehicles are extensively used in logistics operations, and many fleet owners of fossil-fueled trucks are adopting new technologies such as electric, hybrid, and hydrogen-based vehicles. This paper addresses the Hybrid Fleet Capacitated Vehicle Routing Problem with Time Windows (HF-CVRPTW), with the objectives of minimizing costs and mitigating environmental impacts. A mixed-integer linear programming model is developed, incorporating split deliveries, scheduled arrival times at stores, and a carbon cap-and-trade mechanism. The model is tested on a real case study provided by Decathlon, evaluating the performance of internal combustion engine (ICE), electric (EV), and hydrogen fuel cell (HV) vehicles. Results show that when considering economic and emission trading costs, the optimal fleet deployment priority is to use ICE vehicles first, followed by EVs and then HVs, but considering only total emissions, the result is the reverse. Further analysis explores the conditions under which alternative fuel, electricity, or hydrogen prices can achieve competitiveness, and a further analysis investigates the impact of different electricity generation and hydrogen production pathways on overall indirect emissions.

The rapid adoption of Electric Vehicles (EVs), driven by stringent environmental regulations and rising fuel costs, is reshaping the landscape of Vehicle Routing Problems (VRP). This shift has led to the Electric Vehicle Routing Problem (EVRP), which incorporates EV-specific operational constraints such as limited driving range, energy consumption, recharging strategies, and detour-related charging costs. The challenge becomes even more critical in modern mixed fleets , where Electric and Internal Combustion Engine Vehicles (ICEVs) coexist and must be co-routed efficiently. A widely adopted two-step strategy first uses Capacitated VRP (CVRP) algorithms to generate energy-oblivious routes, then makes EV routes energy-feasible via charging station insertion. While VRP and CVRP are extensively studied, methods for efficiently ensuring energy feasibility for EVs on fixed routes remain limited. This article introduces the Fixed Route Vehicle Charging Problem with Discrete Partial Charging (FRVCP-DPC) , extending FRVCP by allowing partial recharging up to predefined discrete levels. We develop a scalable optimal Dynamic Programming algorithm, Best Energy Feasible Route Generator (BEFRG) , to select detour points, charging stations, and charge levels that minimize total route time while maintaining energy feasibility. To evaluate BEFRG in dynamic traffic conditions, we introduce EFRGen , a traffic-aware EVRP simulator built on Simulation of Urban Mobility (SUMO) and OpenStreetMap (OSM). Experiments on the Montoya benchmark—spanning 120 instances with up to 320 demand points and 38 charging stations—show that BEFRG computes optimal solutions for all cases within one minute.

This study applies a Life Cycle Assessment (LCA) framework to compare the environmental footprint of Battery Electric Vehicles (BEVs) and Internal Combustion Engine Vehicles (ICEVs) across production, use, and end-of-life phases. Results indicate that while BEVs generate higher emissions during manufacturing, particularly from battery production, their operational phase offers significant reductions in greenhouse gas (GHG) emissions compared to ICEVs. The environmental advantage of BEVs is strongly influenced by the regional electricity mix; grids with higher shares of renewable energy amplify their benefits, whereas coal-dependent grids diminish them. Sensitivity analysis highlights the importance of vehicle lifetime, charging efficiency, and recycling strategies in shaping life-cycle outcomes. Overall, BEVs demonstrate a net advantage in most scenarios, though achieving true environmental sustainability requires parallel efforts in energy system decarbonization, battery recycling, and circular economy practices.

We assess the cradle-to-grave greenhouse gas (GHG) emissions of current (2025) light-duty vehicles (LDV) across powertrains, vehicle classes, and locations. We create driver archetypes (commuters, occasional long-distance travelers, contractors), simulate different use patterns (drive cycles, utility factors, cargo loads) and characterize GHG emissions using an attributional approach. Driven by grid decarbonization and improved electric vehicle efficiency, we are first to report electric vehicles have lower GHG emissions than gasoline vehicles in every county across the contiguous United States. On average, a 300-mile range battery electric vehicle (BEV) has emissions which are 31-36% lower than a 50-mile range plug-in hybrid electric vehicle (PHEV), 63-65% lower than a hybrid electric vehicle (HEV), and 71-73% lower than an internal combustion engine vehicle (ICEV). Downsizing also reduces emissions, with a compact ICEV having 34% lower emissions than an ICEV pickup. We present the first evaluation of LDV emissions while hauling cargo, showing that carrying 2500 lbs. in a pickup increases BEV emissions by 13% (134 to 152 g CO2e/mile) compared to 22% (486 to 592 g CO2e/mile) for an ICEV. Emissions maps and vehicle powertrain/class matrices highlight the interplay between vehicle classes, powertrains, locations, and use patterns, and provide insights for consumers, manufacturers, and policymakers.

Towards zero CO2 emissions: Insights from EU vehicle on-board data.