Internal Combustion Vehicles Research Articles

Full Electric Vehicles

Full Electric Vehicles (FEVs) are among one of the three kinds of hybrid electric vehicles. FEVs are such motorized vehicles which utilize onboard electric motor or a couple of motors driven solely by batteries which use the stored charge on them as a fuel. FEVs do not drink up any petro-chemical fuel and consequently, do not emit greenhouse gases – decreasing harmful emissions. The concept and use of FEVs dates back to the 1890s when Lohner-Porsche produced the first full electric vehicle known as P1. FEVs provide with such a framework to lower the greenhouse gases to contribute in lessening the climate change and global warming. The paper essentially contends and elucidates that how and why FEVs can replace conventional internal combustion vehicles in a developing country like Pakistan while contributing positively in reducing the burden on economy and environment and making daily life comfortable while preventing the planet earth from global warming and climate change.

Modeling a periodic electric vehicle-routing problem considering delivery due date and mixed charging rates using metaheuristic method.

The coupling of ever-increasing consumption of fossil fuels around the globe with the decrease in the availability of fossil fuel supplies has led to an increased cost of energy commodities, which together with ever-expanding requirements for reducing the level of environmental pollutions has resulted in an ever-increasing deal of attention to alternative transportation schemes such as electric vehicles (EVs). Since decades ago, national governments and environmental activists have initiated various efforts towards reducing atmospheric pollutions. A part of such effort has been focused on reducing the use of internal combustion vehicles and rather replacing them with EVs. In this research, we attempt to fill in this research gap by presenting a mathematical model for minimizing the sum of traveled distance and recharging cost of EVs per a given period and then solving it by simulated annealing (SA) algorithm. Results of the proposed algorithm were then compared to those of coding in GAMS for 30 different sample problems with different counts of customers, EVs, and charging stations. Numerical results indicated good efficiency of the metaheuristic algorithm in terms of processing time and solution quality. Indeed, with the SA algorithm, the processing time was seen to increase gradually with increasing the problem complexity, while the rate of increase in processing time was much steeper with the GAMS.

The Current Situation of the Development of Electric Vehicle Technology in Turkey

The environmental damage caused by internal combustion vehicles used in transportation, the diminishing availability of fossil fuels, and the lower cost of electricity in comparison to gasoline and diesel, are the primary reasons for the trend toward electric vehicles (EV). In parallel to the increase in electric vehicles, the number of charging stations has increased as well, which has contributed to the widespread utilization of electric vehicles. When the history of electric vehicles has been investigated, it became clear that the first studies began in the early 1800s. During those years, as oil output expanded in response to the period's conditions, electric vehicles' popularity diminished in comparison to internal combustion vehicles. Additionally, range, charging durations, and power have limited the commercialization of electric vehicles. With global warming approaching alarming levels and new technology emerging, demand for electric vehicles has increased. Turkey, with its technological advancements and investments in electric vehicles, is observed to be following the global electric vehicle market. In this study, the electric vehicle development process in Turkey was assessed, as was the distribution of existing charging stations for businesses and domestic vehicles.

Decarbonization roadmaps for ASEAN and their implications

The objective of this paper is to derive, for the first time, decarbonization roadmaps for the ten nations of ASEAN. This study first presents a regional view of ASEAN’s fossil and renewable energy usage and energy-related CO2 emission. Results show that renewable energies have been losing ground to fossil energies in the last two decades and fossil fuels will likely continue to be an important part of ASEAN’s energy mix for the next few decades. Therefore, decarbonizing efforts should focus not only on increasing the share of renewable energies in electricity generation, but also on technologies to reduce CO2 emission from fossil power and industrial plants. This study next performs a technology mapping exercise for all ten ASEAN countries to determine decarbonization technologies that have high impact and high readiness for individual countries. Besides installing more sustainable renewable energies, common themes coming from these roadmaps include switching from coal to gas for power generation, using carbon capture and storage (CCS) technologies to decarbonize fossil and industrial plants, replacing internal combustion vehicles by electric vehicles, and for countries that have coal and natural gas resources, upgrading them to blue hydrogen by chemical processes and using CCS to mitigate the emitted CO2. Blue hydrogen can be used to decarbonize hard-to-decarbonize industries. Policy implications of these roadmaps include imposing a credible carbon tax, establishing a national hydrogen strategy, intergovernmental coordination to establish regional CCS corridors, funding research and development to improve carbon capture efficiency on a plant level and resolving sustainability issues of hydropower and bioenergy in ASEAN.

Energy efficiency optimization of a compound coupled hydro-mechanical transmission for heavy-duty vehicles

The concept of carbon neutrality makes scholars not only intensify their exploration on the utilization of new energy, but also further optimizing the utilization of traditional energy by improving energy management. Nearly half of energy losing among traditional internal combustion vehicle is due to energy delivering and operation. The CCHMT prototype enabled the vehicle to run smoothly and efficiently under harsh conditions. However, the large number of parameters makes the optimization of energy management system difficult, which adds a lot of troubles to the subsequent product serialization. Thus, after finishing research on CCHMT-3, a comprehensive optimization algorithm based on NSGA-II&SA is constructed to optimize the transmission characteristic parameters of CCHMT-4. By using the algorithm-optimized parameters, the AMEsim model simulation with CCHMT-4 shows better static speed regulation characteristics, efficiency characteristics and load stiffness characteristics. Furthermore, the dynamic characteristics of CCHMT-4 are simulated by DP dynamic programming algorithm, and the result shows that under the operation condition of JN1015, the fuel consumption rate is reduced by 13.9% compared with CCHMT-3. Subsequently, CCHMT-4 prototype processing and test-bed construction were carried out to verify the relevant characteristics of CCHMT-4. The experiment results show that the actual efficiency of CCHMT-4 is 80.6%–86.0%, the experimental data of fuel consumption is 0.701 kg, which shows better operation performance than CCHMT's former research.

Introducing carsharing schemes in low‐density areas: The case of the outskirts of Le Mans (France)

AbstractNowadays, the issue of rural development has a central place on the agenda of policymakers, particularly in the field of transportation. In low‐density areas, there is a lack of alternatives to car use, but at the same time internal combustion vehicles are currently contested in Western societies for their impacts on global warming. As part of the solution, in the past couple of decades, carsharing (CS) schemes have been growing worldwide, but mainly in urban areas. This paper focuses on a recent socially oriented electric CS scheme launched in 2018 in the countryside of Le Mans, France. This program is supported by the local government whose goal is to provide new offers of transportation for those in need and also provide alternatives to cars. By studying the CS program's first year of implementation, we found a dichotomy between the social expectations of the local government and the reality of use by the population. On the basis of a filled‐out questionnaire and the analysis of the cars' navigation data, we first present the profile of the early adopters. We found that they are mostly male and tend to be over 60 years old. They are also highly motorized and from the upper‐middle and upper classes. Secondly, it appears that the program is having difficulties finding regular users. In this regard, this study shows how important it is for public policy to be based on a thoughtful and coherent planning strategy as well as to be led by a strong local governance.

Design and Analysis of Transmission System of Pure Electric Vehicle

The number of internal combustion vehicles continues to rise, which not only brings energy crisis, but also tail gas brings 
 great environmental harm. At present, the new energy vehicle represented by pure electric has attracted the attention of all sectors 
 of society. It not only effectively solves the problem of energy shortage, but also reduces the harm to the environment. This paper 
 will briefly introduce the transmission system of pure electric vehicle, and analyze its evaluation indexes and design parameters, 
 which is of great significance to establish the technology transformation strategy of pure electric drive.

Расчетные исследования динамических качеств дизельного двигателя и гусеничной машины

Power and dynamic characteristics are the most important indicators of internal combustion engines and vehicles equipped with them. The article considers a method for improving these indicators by transferring a four-stroke engine to work on a two-stroke cycle in modes with low rotational frequencies and the indicators of the dynamic qualities of a diesel engine and a vehicle. A dynamic model of a diesel engine and a tracked vehicle is proposed. Computational studies of the acceleration dynamics of a tracked vehicle weighing 6000 kg, equipped with a base D-245 diesel engine (4 ChN 11.0/12.5) and a modernized engine that can be switched from a four-stroke cycle to a two-stroke cycle in modes with low rotational speed, have been carried out. An analysis of the calculation results showed that when the base diesel engine was replaced with an upgraded one, the acceleration time of the tracked vehicle to a speed of 54.85 km/h went down by 12.4 %, and the acceleration distance decreased by 15.3 %.

Designing Android Software Applying Augmented Reality on the Teaching and Studying of Gasoline Engine Sensors

Nowadays, the gasoline engine is still the heart of transportation in Vietnam. The total number of internal combustion vehicle in Vietnam is over 4 million, which is approximately 2.4 million petrol vehicles. The need of knowledge in the vehicle, especially the gasoline engine control system, is vital for maintenance and diagnostic process in this field. This paper is an introduction for applying the augmented reality and smartphone in teaching and studying input signals of the engine control system of gasoline engine in the Vehicle and Energy Faculty, HCMC University of Technology and Education, focusing on sensors. Augmented Reality (AR) is a new way of information sharing and interaction in mobile device (smartphone, tablet, etc.). AR in education brings truly realistic for teaching and learning process. Additional reality provides the unique cognition path with immersive real-life simulations, which help student accesses resources as real and freely as possible especially in the COVID-19 pandemic.

Electric vehicles local flexibility strategies for congestion relief on distribution networks

Due to the rising concern for the environment and sustainability issues, the transportation system is experiencing important changes to its paradigm, with the increasing replacement of internal combustion vehicles by electric ones. Consequently, the electric systems need to adapt to the ever-increasing load demand from the grid and the challenge to identify driving patterns in electric vehicle users’ behavior. To prepare the grid for these changes, it is necessary to study the behavior of EV users and develop strategies to cope with the growing demand for electric vehicles. Knowing that electric vehicles experience long-parked periods at the charging stations (more than necessary to fully recharge the battery), this research paper proposes an EV charging strategy that intelligently explores these long-parked times. It interrupts charging of EVs that have enough charge to start their trip from certain charging stations to alleviate problems in the network in exchange for a certain incentive. This methodology is then applied in a realistic smart city to investigate its application. The results show that the proposed methodology brings benefits to the distribution network to relieve line congestion and improve the voltage magnitude at the network buses.

How to compare sustainability impacts of alternative fuel Vehicles?

• Well-to-wheel life cycle sustainability assessment of electric vehicles is analysed. • An integrated sustainability assessment framework is developed. • Spherical fuzzy sets and analytic hierarchy process are used to rank the alternatives. • Battery electric vehicles performed best when charging through solar energy. • Battery electric vehicles performed the worst when charging through electricity grid (100% natural gas). Environmental, economic, and social comparisons of alternative fuel vehicles come with various conflicting objectives. For example, adopting electric vehicles might reduce greenhouse gas emissions but It can also cause more water consumption. To overcome such challenges when comparing alternatives, we developed an integrated sustainability assessment framework combining hybrid multi-regional input–output based life cycle sustainability assessment and multi-criteria decision-making methods including Spherical fuzzy sets. Fourteen different sustainability indicators, encompassing the economic, environmental, and social pillars of sustainability, are quantified for well-to-wheel (operation phase) impacts of internal combustion, hybrid, plug-in hybrid, and full battery electric vehicles. Qatar is investigated as a case study, where electricity generation is mainly from natural gas, but with high solar energy potential. The model favors battery electric vehicles charged through solar energy. The proposed framework is scalable and can be helpful towards developing effective national policies and strategies for sustainable transportation around the world.

Hydroprocessing and Blending of a Biomass-Based DTG-Gasoline

The number of annually registered internal-combustion vehicles still exceeds electric-driven ones in most regions, e.g., Germany. Ambitious goals are disclosed with the European Green Deal, which calls for new technical approaches and greenhouse gas neutral transition technologies. Such bridging technologies are synthetic fuels for the transportation sector, e.g., using the bioliq® process for a CO2-neutral gasoline supply. Fuels must meet the applicable national standards to be used in existing engines. Petrochemical parameters can be variably adapted to their requirements by hydroprocessing. In this work, we considered the upgrading of aromatic-rich DTG gasoline from the bioliq® process. The heavy gasoline was therefore separated from the light one by rectification. We investigated how to selectively modify the petrochemical parameters of the heavy gasoline, especially the boiling characteristics, to make the product suitable as a high-quality blending component. Three commercially available Pt/zeolite catalysts were tested over a wide range of temperature and space velocity. We achieved high gasoline yields, while the content of light end compounds up to a boiling temperature of 150°C could be increased significantly. In contrast to the high naphthenic content of the gasoline, the obtained octane numbers were satisfactory. Especially the Motor Octane Number turned out unexpectedly high and showed a dependency on the isomerization of the naphthenic rings. By blending the upgraded heavy gasoline with the previously separated light gasoline, we could finally show that hydroprocessing is suitable for adjusting petrochemical parameters. The aromatic concentration was 37.5% lower than that in the original raw gasoline, while the boiling characteristics improved significantly. Additionally, the final boiling point was 82°C lower, which is beneficial for the emission behavior.

What Is the Level of People’s Acceptance for Electric Taxis and Buses? Exploring Citizens’ Perceptions of Transportation Electrification to Pay Additional Fees

Electric vehicles (EVs) are gradually addressing the environmental problem in cities created by internal combustion vehicles. However, to be widely used, a major challenge will still have to be tackled. Some significant challenges are the resistance to new technologies and EVs’ purchase cost, which is significantly higher than that of internal combustion vehicles. These challenges are similar to the adoption of EVs for public transportation, such as buses and taxis. Thus, this paper proposes valuable insights into attitudes and preferences for taxi and bus users for the willingness to travel in EVs, by performing a convenience sampling, focusing especially on young users. Moreover, this study highlights the possibility of the users paying additional fees to travel in electric taxis (ETs) or electric buses (EBs). Pearson’s chi-squared analysis was also performed to validate the hypotheses.

Fatigue Strength Detection Method for Crankshaft of Vehicle Internal Combustion Engine Based on Dynamics

To accurately determine the load boundary conditions required for the finite element calculation of crankshaft fatigue strength, a dynamic-based fatigue strength detection method for the crankshaft of the automotive internal combustion engine is proposed. Taking a certain type of automotive internal combustion engine as the research object, the multi-body system dynamics model of crank-connecting rod mechanism is established and the dynamic load spectrum of a crankshaft in a working cycle of the internal combustion engine is obtained through dynamic simulation analysis. The load boundary conditions of crankshaft finite element analysis are obtained and the finite element model which can simulate the contact state between crankshaft and bearing is established. The crankshaft fatigue strength is based on the dynamic load spectrum. Degree detection provides load boundary, the fillet sub-model is constructed and the stress distribution of the fillet sub-model under 12-unit displacement loads is obtained by calculating the stress field. The working fatigue safety factor of the crankshaft under dynamic stress is calculated. The analysis results show that the detection error of the proposed method is less than 5% under different noise intensities and the average energy consumption is lower than that of the comparative detection methods, which are 251.37 J and 617.37 J respectively and shows that the proposed method has strong anti-interference and low energy consumption.

How Long Will Combustion Vehicles Be Used? Polish Transport Sector on the Pathway to Climate Neutrality

Transformation of road transport sector through replacing of internal combustion vehicles with zero-emission technologies is among key challenges to achievement of climate neutrality by 2050. In a constantly developing economy, the demand for transport services increases to ensure continuity in the supply chain and passenger mobility. Deployment of electric technologies in the road transport sector involves both businesses and households, its pace depends on the technological development of zero-emission vehicles, presence of necessary infrastructure and regulations on emission standards for new vehicles entering the market. Thus, this study attempts to estimate how long combustion vehicles will be in use and what the state of the fleet will be in 2050. For obtainment of results the TR3E partial equilibrium model was used. The study simulates the future fleet structure in passenger and freight transport. The results obtained for Poland for the climate neutrality (NEU) scenario show that in 2050 the share of vehicles using fossil fuels will be ca. 30% in both road passenger and freight transport. The consequence of shifts in the structure of the fleet is the reduction of CO2 emissions ca. 80% by 2050 and increase of the transport demand for electricity and hydrogen.

Revenue opportunities by integrating combined vehicle-to-home and vehicle-to-grid applications in smart homes

A smart integration of electric vehicles (EVs) in the future energy system will be crucial in decarbonizing the energy sector. Bidirectional EVs can provide flexibility for the system and generate revenues for the user through multiple use cases. We model both exclusive photovoltaic (PV) self-consumption optimization and the combined usage of PV self-consumption optimization and arbitrage trading for a household with an unmanaged, smart, and bidirectional charging EV in a linear (LP) and mixed-integer linear programming (MILP). Since power flows in a typical household are low, varying non-linear charging and discharging efficiencies of the bidirectional EV in the MILP result in more realistic revenues that are 30% lower than in the LP with fixed efficiencies. For a typical German household using a bidirectional EV for optimizing PV self-consumption, these revenues are about 310 €/a, mostly generated during the summer. Arbitrage trading well complements this vehicle-to-home use case in the winter months, resulting in revenues up to 530 €/a. These significant revenue potentials can lead to more profitable and interactive EVs incentivizing users to change from internal combustion vehicles to electric mobility.

A Two-Echelon Electric Vehicle Routing Problem with Time Windows and Battery Swapping Stations

Driven by the new laws and regulations concerning the emission of greenhouse gases, it is becoming more and more popular for enterprises to adopt cleaner energy. This research proposes a novel two-echelon vehicle routing problem consisting of mixed vehicles considering battery swapping stations, which includes one depot, multiple satellites with unilateral time windows, and customers with given demands. The fossil fuel-based internal combustion vehicles are employed in the first echelon, while the electric vehicles are used in the second echelon. A mixed integer programming model for this proposed problem is established in which the total cost, including transportation cost, handling cost, fixed cost of two kinds of vehicles, and recharging cost, is minimized. Moreover, based on the variable neighborhood search, a metaheuristic procedure is developed to solve the problem. To validate its effectiveness, extensive numerical experiments are conducted over the randomly generated instances of different sizes. The computational results show that the proposed metaheuristic can produce a good logistics scheme with high efficiency.

Data-Driven Prediction and Optimization of Energy Use for Transit Fleets of Electric and ICE Vehicles

Due to the high upfront cost of electric vehicles, many public transit agencies can afford only mixed fleets of internal combustion and electric vehicles. Optimizing the operation of such mixed fleets is challenging because it requires accurate trip-level predictions of electricity and fuel use as well as efficient algorithms for assigning vehicles to transit routes. We present a novel framework for the data-driven prediction of trip-level energy use for mixed-vehicle transit fleets and for the optimization of vehicle assignments, which we evaluate using data collected from the bus fleet of CARTA, the public transit agency of Chattanooga, TN. We first introduce a data collection, storage, and processing framework for system-level and high-frequency vehicle-level transit data, including domain-specific data cleansing methods. We train and evaluate machine learning models for energy prediction, demonstrating that deep neural networks attain the highest accuracy. Based on these predictions, we formulate the problem of minimizing energy use through assigning vehicles to fixed-route transit trips. We propose an optimal integer program as well as efficient heuristic and meta-heuristic algorithms, demonstrating the scalability and performance of these algorithms numerically using the transit network of CARTA.

A review on potentials and challenges of nanolubricants as promising lubricants for electric vehicles

AbstractThe most remarkable difference between electric vehicles (EVs) and conventional ones is the fuel burning dependency of the internal combustion engine, while the emerging EVs operate on electric motors. These alternations create staggering shifts in both lubricants' market demand and performance specifications. Lubricants for electrical powertrain constitutes greases, transmission oils, and lubricants for auxiliary systems and do not rely on engine oils as internal combustion vehicles. The new standards will be more focused on lubricants' electrical properties such as breakage voltage and conductivity, coupled with tribological performance under high rpm, corrosion resistance and thermal management benchmarks. This paper thematically reviews the different studies performed with nanolubricants, and how they match EVs' operational requirements. Conclusions from this study can be considered as guidelines for the potential application of nanolubricants in EVs and possible future research that can be accomplished on the topic.

Editorial Mechatronics as an Enabler for Intelligent Transportation Systems

The automotive industry is at the forefront of the smart, connected and autonomous vehicle (SCAV) revolution to improve social mobility with safety and road utilization. Also, more and more countries and cities have announced restrictions on future internal combustion vehicle sales or use for cleaner transport. Hence, together with urgent demands for highly energy-efficient transport systems, the need to make them safer, greener, and smarter has been increasing rapidly in recent years. As a result, the development of intelligent transportation system (ITS) underpinned by advanced propulsion and innovative control systems is known as a feasible solution to address all of these challenges.