Internal Combustion Engine Vehicles Research Articles

Hybrid Simulation Model of Lifecycle Simulation and Replacement Simulation Considering Carbon Lock-In by Coal-Fired Power Plants

To meet the temperature goal set by the Paris Agreement, cumulative CO2 emissions must be kept below 300 GtCO2. Road transportation accounted for approximately 18% of the CO2 emissions from fuel combustion in 2017. Electric vehicles (EVs) have been rapidly adopted by environmentally conscious consumers in many countries to reduce CO2 emissions. EVs have lower emission intensities than do internal combustion engine vehicles (ICEVs) in most parts of the world, except where the penetration of renewable energy is low in the energy production mix. In such places, the CO2 emissions of EVs are larger than those of ICEVs. Despite the obvious need to increase renewable energy sources to reduce CO2 emissions, Japan and many other countries around the world have yet to shift away from fossil fuels. This is due in part to carbon lock-in, which refers to prior decisions related to technologies and infrastructure that constrain the implementation of better paths toward low-carbon technologies. Coal-fired power plants are the most problematic in terms of carbon lock-in because of their high carbon intensities and long physical lives. In addition, because carbon lock-in by coal-fired power plants has a significant impact on the embodied CO2 intensity of grid power, it impacts society through products that use electric power. In this study, we propose a hybrid simulation model of lifecycle simulation and replacement simulation, considering carbon lock-in by coal-fired power plants. In the replacement simulation, we simulated the replacement of end-of-life coal- and oil-fired power plants with renewable energy power plants using a probability called the lock-in rate and estimated the changes in the embodied CO2 intensity of grid power in Japan. In the lifecycle simulation, we evaluated cumulative CO2 emissions from entire product lifecycles of ICEVs and EVs based on three different EV diffusion scenarios. The results showed that the lock-in rate of coal-fired power plants strongly affects the decarbonization effect due to the market diffusion of EVs.

Social risk assessment of the transition from internal combustion engine vehicles to electric vehicles: Material supply chains in China, Japan, and South Korea

In order to reduce carbon emissions, the production of internal combustion engine vehicles (ICEVs) is being transitioned to the production of electric vehicles (EVs). However, the social unsustainability of this process needs further testing. This study explored the social risk characteristics of the transition from ICEVs to EVs based on the Social Hotspots Database (SHDB), combining with the Social Life Cycle Assessment (SLCA) and the Marginal Analysis Method (MAM). Here, we revealed the differences in social risks in the material supply chains between China, Japan, and South Korea, which may create incentives for 100 % supply concentration in a hypothetical game. In terms of social risk, common substitution trends in the iron‑aluminum sector and synergy patterns in the copper-rubber sector were observed in the three countries. As a key factor influencing social risks, cost factor may change, and cost changes due to transition were mainly influenced by production adjustments and sourcing differences, reflecting differences in production capacity trends. This study makes it possible to consider ICEVs and EVs as two endpoints for transition activity in a SLCA exercise and provides valuable insights focusing on transition, aiding in material selection for future product design and underscoring the importance of proactive consideration of social sustainability indices.

A Study on the Mid-frequency Tire-Sourced Cabin Noise in Electric Vehicles

ABSTRACT This study investigates and provides a framework for addressing a reported tire- sourced cabin noise in the mid-frequency range of 300–500 Hz for an electric vehicle (EV). Noise, vibration, and harshness (NVH) of EVs present new challenges compared with internal combustion engine vehicles because of significant design changes between the two vehicle types. In turn, the tire–road interaction noise becomes a more significant source of cabin noise in EVs. In this regard, some prominent EV manufacturers recently reported relatively high measured cabin noise, particularly in the mid-frequency range of 300–500 Hz. Identifying the root cause(s) of noise in that range is a challenging task, as both tire structure–borne and airborne sources are contributors in that frequency range of elevated noise. The current work presents the results of an experimental modal analysis to provide insight into some potential sources of the reported noise for an all-season tire/wheel assembly designed for an EV. The subsequent parametric simulations, conducted via the tire–vehicle finite element model, evaluate some of the mitigation solutions for the reported noise.

Economic implications of a phased‐in EV mandate in Canada

AbstractCanada plans to phase out internal combustion engine vehicle (ICEV) sales in favour of electric vehicles (EVs) by 2035 as part of its climate policy. Herein I examine the economic implications of a phased‐in electric vehicle mandate. I show using partial equilibrium analysis that when both types of cars are available, auto companies will overproduce electric vehicles and earn scarcity rents on internal combustion engine vehicles that partially offset the revenue loss on electric vehicles. I then present a numerical general equilibrium model of the Canadian economy to assess the overall macroeconomic consequences of the policy. The results depend critically on the assumed pace at which electric vehicles achieve cost parity with internal combustion engine vehicles on a quality‐adjusted basis. An electric vehicle mandate will have manageable economic consequences if technology improves so rapidly that the mandate is unnecessary. If the mandate outpaces achievement of cost parity the economic consequences can be severe and would likely cause the auto manufacturing sector to shut down. The cost per tonne of emission reductions are at least 10 times the Canadian carbon tax rate while the mandate is binding. The analysis provides insight into why automakers have been willing hitherto to develop and sell electric vehicles even though they currently lose money on them.

A comparative study of vehicle powertrain efficiency: Data-driven analyzing energy consumption and environmental impact

This study investigates the energy consumption of electric vehicles (EVs) in real-world driving conditions, using in-vehicle sensor data and location tracking. The energy consumption of EVs is compared to that of an internal combustion engine vehicle (ICEV) under similar driving tests. Furthermore, an energy-centric life cycle assessment was conducted to assess the environmental impact of the transition to electrified transportation by reporting the carbon emissions of the EVs and ICEV. Since a large volume of driving data was acquired in the experiment, machine learning (ML) techniques are employed to interpret the obtained data and identify a key feature. ML algorithms can help develop predictive models that estimate energy consumption and explain the major factors that impact such consumption. The findings also offer valuable insights into energy consumption, emission, and the underlying factors that can inform policy discussion related to transport electrification and enhance energy efficiency. This research is significant in comprehending the potential of current EVs and their superiority over traditional vehicles. It is vital to facilitate the shift toward electric transportation, which can be driven by the results.

Fuel Efficiency Optimization in Adaptive Cruise Control: A Comparative Study of Model Predictive Control-Based Approaches

This work investigates the fuel efficiency potential of Adaptive Cruise Control (ACC) systems, focusing on two optimization-based control approaches for internal combustion engine (ICE) vehicles. In particular, this study compares two model predictive control (MPC) designs. In the first approach, a strictly quadratic cost is adopted, and fuel consumption is indirectly minimized by adjusting the weights assigned to state tracking and control effort. In the second approach, a fuel consumption map is explicitly included in the MPC cost function, aiming to directly minimize it. Both approaches are compared to a globally optimal benchmark obtained with dynamic programming. Although these methods have been discussed in the literature, no systematic comparison of their relative performance has been conducted, which is the primary contribution of this article. The results demonstrate that, with proper tuning, the simpler quadratic approach can achieve comparable fuel savings to the approach with explicit fuel consumption minimization, with a maximum variation of 0.5%. These results imply that the first alternative is more suitable for online implementation, due to the more favorable characteristics of the associated optimization problem.

ICE to EV Conversion in Thailand: Evaluating Feasibility, Benefits, and Challenges

Abstract: The shift to electric vehicles (EVs) is vital for reducing greenhouse gas (GHG) emissions, but Thailand faces challenges in adopting new EVs due to high costs and limited infrastructure. This study investigates the feasibility of converting internal combustion engine (ICE) vehicles to EVs over the next decade, examining the economic, environmental, and social impacts. Findings show that EV conversions can reduce operational costs by 40-50% and lower GHG emissions by up to 70%, even when accounting for electricity-related emissions. In addition, the transition could significantly improve air quality, leading to public health benefits. However, barriers such as high upfront conversion costs, limited access to conversion kits, and the need for skilled labor remain. Addressing these challenges through government incentives, infrastructure development, and workforce training will be essential for scaling up EV conversions, enabling Thailand to accelerate its shift toward sustainable transportation and meet its climate goals.

Assessing the environmental benefits of passenger cars electrification in metropolises: A case study of Singapore

Land-based transportation is a significant contributor to global greenhouse gas (GHG) emissions, with internal combustion engine vehicles being the predominant mode of transport in this sector. As the world population grows and urbanization accelerates, transport demand in metropolitan areas is projected to double by 2050, underscoring the critical need for sustainable transportation strategies, forecasting, and planning within an urban context. One challenge in this endeavor is the insufficient attention given to the distribution of vehicle grades within the overall car population during GHG impact assessment, despite the recognized importance of car grade by researchers and policymakers. In this study, we incorporate both engine type and vehicle grade distribution, derived from data on over 30,000 passenger cars registered with the Land Transport Authority of Singapore between 2018 and 2022, into our life cycle assessment analysis. This approach ensures that our scenario-based studies on prediction and planning are more comprehensive than those that consider only the most popular models. Furthermore, while Singapore benefits from a relatively clean electricity supply, the current limitations in charging infrastructure negatively affect the GHG impact of electric vehicles. The insights from this research will inform the development of transportation policies for metropolises like Singapore, contributing to the advancement of a more sustainable transportation system.

Exploration of the Traffic Safety of Battery Electric Vehicles: A Case Study of Tesla Vehicle-Involved Crashes in Pennsylvania, USA

After decades of efforts, the number of battery electric vehicles (BEV) has increased greatly around the world. Meanwhile, their unique technical features also bring many new traffic safety challenges. Using traffic crash data from Pennsylvania from 2018 to 2021, this study aims to identify characteristics and trends of BEV crashes by comparing those crashes involving Tesla vehicles (the premier BEV brand in the auto market of the United States) with crashes involving internal combustion engine vehicles (ICEV). First, Tesla and ICEV crashes are compared for crash severity, collision type, spatial and temporal distributions, and environmental features. Tesla crashes show no significant difference from those of ICEVs in severity, but they have many more rear-end and angle collisions. In addition, Tesla crashes are found to concentrate in peak hours and around noon, occurring mainly in urban areas, at intersections, and on state roads. A logistic regression model is then built to identify the important factors influencing the severity of Tesla crashes. The findings are expected to provide new insights which will help researchers understand better traffic safety issues around BEVs.

Evaluation of potential electric vehicles load-induced damage on flexible pavements

The adoption of Electric Vehicles (EVs), driven by policies like the Zero Emission Vehicle (ZEV) mandate, is rapidly transforming transportation infrastructure. In 2021, over 1.25-million light-duty EVs were registered in the United States, signaling a shift that extends to heavy vehicle categories. This study evaluates the implications of this transition on road networks, focusing on the increased gross weight of EVs compared to traditional Internal Combustion Engine (ICE) vehicles and its impact on flexible pavement structures. The study investigates the deterioration patterns and potential damage to road infrastructures resulting from integrating EVs into the traffic mix, utilizing both the AASHTO 1993 and Mechanistic-Empirical (ME) pavement evaluation methodologies. The analyses reveal a significant acceleration in road degradation, necessitating urgent consideration of EV-induced stresses by transportation authorities. Recommendations for future research and practical strategies for mitigating these impacts are provided to guide policymakers and engineers in adapting to this evolving vehicular landscape.

The window of opportunity: a case study of the battery electric vehicle in Thailand

Purpose Thailand, although a late entrant, has emerged as a significant center for the production and export of internal combustion engine (ICE) vehicles in Asia. With the arrival of a disruptive battery-electric vehicle (BEV), this study aims to investigate whether Thailand can exploit this window of opportunity to leapfrog. Design/methodology/approach This paper uses data sourced from Thailand’s Department of Intellectual Property to analyze electric vehicle (EV) patent applications. This paper collected qualitative data and conducted interviews with several EV manufacturers. Findings Although Japanese automakers dominate essential EV technology patents, they trail behind Chinese automakers, which benefited from the Free Trade Agreement (FTA) in EV sales. The incumbents, Japanese and Western, choose to expand their production of hybrid electric vehicles (HEVs) and plug-in hybrid vehicles. ICE technology does not constrain new entrants, such as Chinese automakers, Japanese newcomers and Thai newcomers. Compared to Japanese carmakers stuck with ICE and HEV technologies, they have been transitioning to BEVs at a faster pace. BEV has opened the door for large Thai indigenous energy corporations to enter the automotive industry by focusing on niche areas (nonfour-wheel vehicles) and supporting businesses like charging stations. In summary, Thailand has successfully attracted foreign direct investment (FDI) into the EV sector, but it has not yet succeeded in developing indigenous technologies related to EVs. The Thai automobile sector fails to leapfrog because it is too tied up with Japanese automotive production networks and has an unfavorable FTA with China. Originality/value This study sheds light on the limitations of an industrial development strategy relying on openness to trade and FDI without adequately strengthening indigenous technologies and firms, as the country adopting the strategy fails to leapfrog when the window of opportunities created by disruptive technologies arrives.

Estimating the tipping point for lithium iron phosphate batteries

Uncertainty surrounding NMC cathode chemistry prices have prompted increasing interest in less expensive alternative technologies. Chief among these is lithium iron phosphate (LFP), a chemistry that offers a cost advantage at the expense of energy density. We estimate which chemistry offers a lower cost at targeted vehicle ranges consistent with those consumers can expect from internal combustion engine vehicles. Our model – which considers tradeoffs between battery capacity and weight – enumerates a range ‘tipping point’ of 373.52 miles, beyond which NMC batteries consistently demonstrate a cost advantage over LFP batteries, despite the latter's reliance on less costly minerals. Using this tipping point as a benchmark, we leverage trip-level data from the National Household Travel Survey to explore which U.S. households may benefit from EVs equipped with LFP versus NMC batteries. Among multi-vehicle households, only 1 % of all trips taken exceed 160.53 miles, a figure analogous to our most conservative tipping point. To the extent that EVs may be utilized for relatively short commutes or as secondary or tertiary vehicles, our results suggest that LFP batteries can offer lower costs relative to NMC batteries while satisfying most households' travel demands. We subsequently discuss the policy implications of these findings.

A Review on Advanced Battery Thermal Management Systems for Fast Charging in Electric Vehicles

To protect the environment and reduce dependence on fossil fuels, the world is shifting towards electric vehicles (EVs) as a sustainable solution. The development of fast charging technologies for EVs to reduce charging time and increase operating range is essential to replace traditional internal combustion engine (ICE) vehicles. Lithium-ion batteries (LIBs) are efficient energy storage systems in EVs. However, the efficiency of LIBs depends significantly on their working temperature range. However, the huge amount of heat generated during fast charging increases battery temperature uncontrollably and may lead to thermal runaway, which poses serious hazards during the operation of EVs. In addition, fast charging with high current accelerates battery aging and seriously reduces battery capacity. Therefore, an effective and advanced battery thermal management system (BTMS) is essential to ensure the performance, lifetime, and safety of LIBs, particularly under extreme charging conditions. In this perspective, the current review presents the state-of-the-art thermal management strategies for LIBs during fast charging. The serious thermal problems owing to heat generated during fast charging and its impacts on LIBs are discussed. The core part of this review presents advanced cooling strategies such as indirect liquid cooling, immersion cooling, and hybrid cooling for the thermal management of batteries during fast charging based on recently published research studies in the period of 2019–2024 (5 years). Finally, the key findings and potential directions for next-generation BTMSs toward fast charging are proposed. This review offers an in-depth analysis by providing recommendations and potential solutions to develop reliable and efficient BTMSs for LIBs during fast charging.

Exploring disparities and similarities in daily travel mode choices between electric vehicle owners and internal combustion engine vehicle owners

ABSTRACT This study proposes a novel instrument for measuring private car owners’ travel-related lifestyle (PCTRL) based on a survey (N = 2045) conducted in China’s four first-tier cities and ten quasi first-tier cities. By employing principal component analysis (PCA) and cluster analysis, the study classifies electric vhehicle (EV) owners and internal combustion engine vehicle (ICEV) owners into five distinct PCTRL segments, respectively. The findings reveal that only 66% of EV owners have similar PCTRLs to 67% of ICEV owners, with the most notable disparity being the higher likelihood of EV owners choosing private cars for their daily commutes. Furthermore, a random forest model was developed to predict the daily activity-based travel mode choices behavior of both EV and ICEV owners. The findings offer valuable insights into understanding the behavior of EV and ICEV owners in their daily travel mode choices and help formulating more effective traffic management strategies.

Health benefits of US light-duty vehicle electrification: Roles of fleet dynamics, clean electricity, and policy timing

We present a dynamic perspective to quantify the air quality-related health impacts of the electrification of light-duty vehicles in the United States between 2022 and 2050. Using a fleet turnover model and future electricity generation mix scenarios, we compare ambitious vehicle electrification to fleet renewal relying on newer internal combustion engine vehicles, without electric vehicles. The model includes vehicle-level pollutant emission factors and a reduced complexity air quality and valuation model and covers direct (tailpipe, brake wear, and tire wear) and indirect (production of electricity and liquid fuels) emissions of NOx, SO2, PM2.5, NH3, and VOCs, with a breakdown at the county level to identify geographical disparities in the distribution of health impacts. Short-term health benefits are mostly generated by reductions in NOx emissions from newer gasoline vehicles, while fleet electrification generates further benefits in the long term. The electricity mix plays a crucial role in the success of electrification policies. With continued grid decarbonization, electrification would reduce harmful air quality-related health impacts cumulatively by 84 to 188 billion USD over the study period, compared with fleet renewal without electric vehicles. In contrast, artificially freezing the 2022 grid would make electrification responsible for 32 to 71 billion USD additional health disbenefits compared with fleet renewal. Finally, we show that while fleet electrification achieves most of its benefits over fleet renewal in the long term, delaying the implementation of such policies would sacrifice meaningful cumulative benefits.

Drivers of Electric Vehicle Adoption in Nigeria

Electric vehicles (EVs) represent a significant advancement in automotive technology, utilizing electricity as a power source in place of traditional fossil fuels and incorporating sophisticated navigation and autopilot systems. These vehicles align with multiple Sustainable Development Goals (SDGs) by offering a more environmentally sustainable alternative to internal combustion engine vehicles (ICEVs). Despite their potential, the adoption of EVs in developing nations such as Nigeria remains constrained. The Unified Theory of Acceptance and Use of Technology (UTAUT) framework is expanded in this study by including important enablers such as poor infrastructure, problems with affordability, and government support in the broader category of facilitating conditions. Additionally, it scrutinizes variables such as trust, performance expectations, social influences, and network externalities to identify the primary determinants influencing Nigerian consumers' propensity to adopt EVs. Results show that the percentage increase of H6 (facilitating conditions → behavioral intentions) compared to H5 (network externalities → behavioral intentions) is approximately 32.35%, indicating that traditional drivers significantly influence individuals' willingness to purchase EVs and are particularly strong factors in adoption decisions. The paper concludes with a discussion of these findings and proposes strategies for future research to further explore the barriers and drivers of EV adoption in Nigeria.

Anticipatory climate policy mix pathways: a framework for ex-ante construction and assessment applied to the road transport sector

ABSTRACT Globally, climate policy implementation is failing to deliver on the ambitions outlined in the Paris Agreement and countries’ Nationally Determined Contributions. We argue that a more strategic and anticipatory approach to policy mix design and implementation can help contribute to realizing these ambitions. Policy mixes need to co-evolve as energy transitions progress, in order to effectively target multiple transition challenges as these change over time. Accordingly, policy assessments need to both consider interactions between instruments and adopt a dynamic perspective, in terms of design logics and evaluative criteria. We highlight the need for a construction and assessment methodology for designing policy mix pathways which explicitly considers durability risks which could weaken support and lead to dismantling, and anticipatory design principles which can help mitigate these risks. Our paper addresses this gap by proposing and illustrating a novel framework for policy instrument mix pathway construction and ex-ante assessment. We identify generalizable durability challenges for effective anticipatory design: dynamic cost effectiveness, the distributive impacts and acceptance of pathways, along with fiscal and governance requirements for effective implementation. We demonstrate the value of the approach by application to the German light-duty vehicle sector transition. We construct and comparatively assess three illustrative pathways promising to deliver the German LDV sector 2030 GHG targets. The pathways differ in logic, and which of three main market dynamics driving a diffusion-stage transition they emphasize: battery electric vehicle (BEV) purchase, vehicle stock usage, and internal combustion engine (ICE) vehicle scrappage. Accordingly, the pathways utilize different instrument combinations, design features and calibrations. We also assess the illustrative pathways and discuss trade-offs. We argue that this approach can help improve climate policy planning and implementation processes, and increase the likelihood attaining ambitious mitigation targets.

Regional vehicle energy consumption evaluation framework to quantify the benefits of vehicle electrification in plateau city: A case study of Xining, China

Vehicle electrification holds significant potential for driving both decarbonization and improved energy efficiency within the realm of road transportation. However, accurate quantification of energy consumption advantages offered by electric vehicles (EVs) has remained elusive, thus impeding their long-term development due to variations across cities and vehicle types. To address this challenge, we propose a novel regional vehicle energy consumption assessment framework that integrates a region-specific driving cycle (DC) database and advanced high-precision energy consumption models. The regional DC database is constructed using a Markov chain approach. The database is stochastic and diverse, while taking into account real driving features and regional geographic environments. Energy consumption models for internal combustion engine vehicle (ICEV), plug-in hybrid electric vehicle (PHEV) and battery electric vehicle (BEV) are constructed based on machine learning approach. These models have good generalization ability and prediction accuracy, with R2 of 0.86, 0.86 and 0.77 on the test set, respectively. According to the interpretability of the models, vehicle acceleration and vehicle specific power are considered to be the most important features affecting vehicle energy consumption. According to the evaluation results, compared to using ICEV, the promotion of PHEV and BEV in Xining, a plateau city, can reduce energy consumption by 27.83 % and 32.05 %, respectively. The framework not only unifies the scale of energy consumption evaluation among different vehicle types, but also its good generalization ability can be migrated and extended to the evaluation of vehicle energy consumption in various regions. The establishment of this framework will contribute to the promotion and popularization of electric vehicles, as well as the advancement of energy-saving initiatives in the transportation sector.

The role of battery electric vehicles in off-peak hour deliveries: Sustainability assessment of a case study in Stockholm

City logistics faces critical challenges in optimising resource management, utilising time effectively, and reducing costs, particularly in the context of growing environmental concerns. Battery Electric Vehicles (BEVs) and Off-Peak Hour Deliveries (OPHD) have emerged as promising solutions. Despite considerable research efforts, more research is needed to evaluate the impacts of using BEVs during OPHD. To address this need, this paper describes how data from a case study in Stockholm were used to develop a comprehensive overview of the sustainability impacts of OPHD carried out with BEV. A multi-method approach was applied, including an indicator framework, Life Cycle Costing, and a Social Life Cycle Assessment to consider all sustainability dimensions holistically. Our findings reveal that, while BEVs are not yet cost-competitive with Internal Combustion Engine vehicles for daytime operations, OPHD can mitigate these costs by increasing the vehicle utilisation and distances travelled. Furthermore, OPHD with BEV can offer substantial benefits by increasing accessibility and reducing emissions. However, challenges such as increased employee-related transport costs and infrastructure needs must be addressed. The main contributions of this paper are practical, as we add knowledge about the impacts of OPHD using BEV, and methodological, as we used a multi-method approach to holistically assess sustainability impacts. Future research should focus on long-term impacts and refine assessment methods to support the sustainable development of urban logistics. This study highlights the importance of using holistic sustainability assessment to inform and enable stakeholders and decision-makers to leverage the full potential of OPHD when shifting to more sustainable transport.

A study on a micro perforated panel applied luggage board design for road noise reduction

The automotive industry is on the age of rapid transformation from internal combustion engine vehicles to electric vehicles powered by motors. The main source of noise in conventional internal combustion engine vehicles is the engine, while electric vehicles are mainly affected by road and wind noise. A road noise in the medium and low frequency bands, caused by friction between tires and road surfaces, can be improved by increasing the thickness and weight of the insulation material. Still, this countermeasure causes other challenges that related to driving efficiency decrease because of limitations space and weight. As a new method to reduce road noise, therefore, the study introduces the luggage board which applied the micro-perforated panel system. This system utilizes a resonance-type sound absorbing material with excellent sound absorption characteristics at specific frequencies so that a tire pattern noise within the 800-1,000 Hz could be reduced. Because the thickness of the luggage board is partially limited, the study set a number of variations such as changing the porosity, perforated diameter in the perforated panel system. As a result, the study confirmed 2% improvement A.I. (Articulation Index) in the interior with installation of the designed luggage board on the vehicle.