Conventional Internal Combustion Engine Vehicles Research Articles

Forecasting the development trend of low emission vehicle technologies: Based on patent data

With the increasing awareness of environmental protection, there is a consensus on developing low emission vehicle (LEV) technologies but the trend is unclear. The LEV technologies, including hybrid electric vehicle (HEV), battery electric vehicle (BEV), and fuel cell electric vehicle (FCEV) technology, are considered as alternative technologies for the conventional internal combustion engine vehicles (ICEVs). The purpose of the paper is to forecast the future development trend of drivetrain technologies. In doing so, a revised method of technological forecasting is proposed on the basis of the S-curve simulation for growth curves and entropy weight method for ranking candidates, which leads to forecasting results are more objective and accurate. Our findings highlight that HEV has the most promising future, followed by BEV and ICEV, but FCEV develops slowly. The implications are that policymakers should maintain the principle of technology-neutral when implementing various policies, while enterprises should be aware of the hybridization trend of vehicles in the business strategy-making process.

Assessment of gasoline consumption and greenhouse gas emission reduction on using battery electric two-wheeler in India

A transformation from conventional internal combustion engine (ICE) vehicles to battery electric (BE) vehicles coupled with a low carbon electricity grid is considered to be effective in reducing greenhouse gas (GHG) emissions especially carbon dioxide (CO2) and a resulting drop in the oil demand. This study investigates the possible savings in the gasoline consumption and reduction in CO2 emission in India from the battery electric two-wheeler segment during the fiscal year 2021–2030. The CO2 emissions are estimated based on emission coefficients, average fuel consumption and the annual mileage of two-wheelers. In India, more than 70% of the total registered motor vehicles belong to the category of a two-wheeler. Hence, any policy actions intended at the reduction in CO2 emission and gasoline consumption from the transportation sector must focus on the two-wheeler segment. Older two-wheeler has higher gasoline consumption due to lower fuel economy which leads to larger CO2 emission. The study reveals that with 100% replacement of newly registered ICE two-wheelers with BE two-wheelers, a total savings of 322.50 billion litres of gasoline and a reduction of 571.49 million tonnes of CO2 emissions can be achieved during the period 2021–2030. With strict implementation of a scrapping policy whereby all ICE two-wheelers completing 15 years of service are taken off the road, the gasoline savings and reduction in CO2 emissions can be enhanced to 403.23 billion litres and 811.27 million tonnes, respectively, during the same period. The enhanced use of non-fossil fuel-based sources for electricity generation will lead to a further reduction in CO2 emission, as the energy required for the propulsion of BE two-wheeler is sourced from the grid.

A Review on Power Electronics Technologies for Electric Mobility

Concerns about greenhouse gas emissions are a key topic addressed by modern societies worldwide. As a contribution to mitigate such effects caused by the transportation sector, the full adoption of electric mobility is increasingly being seen as the main alternative to conventional internal combustion engine (ICE) vehicles, which is supported by positive industry indicators, despite some identified hurdles. For such objective, power electronics technologies play an essential role and can be contextualized in different purposes to support the full adoption of electric mobility, including on-board and off-board battery charging systems, inductive wireless charging systems, unified traction and charging systems, new topologies with innovative operation modes for supporting the electrical power grid, and innovative solutions for electrified railways. Embracing all of these aspects, this paper presents a review on power electronics technologies for electric mobility where some of the main technologies and power electronics topologies are presented and explained. In order to address a broad scope of technologies, this paper covers road vehicles, lightweight vehicles and railway vehicles, among other electric vehicles.

Elektrikli Araçla Periyodik Teknisyen Rotalama ve İstasyon Yeri Seçim Problemi

In this study, Electric Multiperiodic Technician Routing and Charging Station Location Problem is defined. A series of preventive and corrective maintenance-repair and spare parts supply services are offered to customers located in different geographical regions of the problem. In addition, the customers can request these tasks in different time windows throughout the planning horizon. Teams of technicians with different competencies are formed and allocated to these tasks that are provided in the customer locations. Considering that the workforce scheduling and routing problem is in the NP-hard class, thus the defined problem is also in the same class. Unlike the literature, in this study, it is taken into account that technicians reach customers with electric vehicles instead of using conventional internal combustion engine vehicles. In this way, it will be possible to reduce the use of fossil fuels and the environmental impact of these fuels due to transportation. In addition, due to the operating costs of electric vehicles are lower than those of conventional vehicles, electric vehicles emerge as an economical option for businesses. In addition to their advantages, the limited range of electric vehicles makes them dependent on using charging stations. For this reason, routing plans need to be made efficiently in order for these vehicles to compete with conventional vehicles. In the proposed problem, while creating a daily schedule and route for the teams throughout the planning horizon, tracking the state of charge of the vehicles and determining the location of the charging station are also considered. In addition, the legal rest periods of the technicians are also taken into account. The problem is modelled with the mixed integer programming formulation. Furthermore, the data set generated from the real-life instances. In order to solve the problem variable neighbourhood search heuristic is used. Computational comparisons are conducted to compare the performance of the heuristic. The results indicate that it can find the optimum solutions. Moreover, the heuristic is able to produces better results than the CPLEX solver in a reasonable time.

Are the electric vehicles more sustainable than the conventional ones? Influences of the assumptions and modeling approaches in the case of typical cars in China

In order to make the sustainable development of transport system, China has taken actions toward the electrification transition of vehicles. However, whether the electric vehicles (EVs) are more environmentally friendly than the conventional internal combustion engine vehicles (ICEVs) in China is still not clear due to a lack of complete and consistent environmental impact comparison of vehicles. This study takes the vehicle models from BYD Qin Pro series in China as illustrations to compare the environmental impact of battery electric vehicle (BEV) and plug-in hybrid electric vehicle (PHEV) with the conventional ICEV. The environmental profiles of vehicles across the whole life cycle within a set of environmental indicators are analyzed. The key aspects that may heavily influence the environmental impacts, i.e. regional heterogeneity, technology improvement and different modeling methods (attributional vs consequential) choices, are further tested, respectively. The results show that already today the BEV and PHEV powered by the current average Chinese electricity mix offer 23% and 17% reduction of global warming potential (GWP), respectively, compared to the gasoline ICEV. But it is achieved at the expense of considerable increases in mineral resource scarcity and ecological and human toxicity, etc. All of the factors considered show markedly influences on the environmental profiles of EVs, even up to 51% of GWP differences for different modeling methods application. And they all have the possibility to reverse the environmental priorities of some impact categories among ICEV, BEV and PHEV.

Public Health and Climate Benefits and Trade-Offs of U.S. Vehicle Electrification.

Vehicle electrification is a common climate change mitigation strategy, with policymakers invoking co‐beneficial reductions in carbon dioxide (CO2) and air pollutant emissions. However, while previous studies of U.S. electric vehicle (EV) adoption consistently predict CO2 mitigation benefits, air quality outcomes are equivocal and depend on policies assessed and experimental parameters. We analyze climate and health co‐benefits and trade‐offs of six U.S. EV adoption scenarios: 25% or 75% replacement of conventional internal combustion engine vehicles, each under three different EV‐charging energy generation scenarios. We transfer emissions from tailpipe to power generation plant, simulate interactions of atmospheric chemistry and meteorology using the GFDL‐AM4 chemistry climate model, and assess health consequences and uncertainties using the U.S. Environmental Protection Agency Benefits Mapping Analysis Program Community Edition (BenMAP‐CE). We find that 25% U.S. EV adoption, with added energy demand sourced from the present‐day electric grid, annually results in a ~242 M ton reduction in CO2 emissions, 437 deaths avoided due to PM2.5 reductions (95% CI: 295, 578), and 98 deaths avoided due to lesser ozone formation (95% CI: 33, 162). Despite some regions experiencing adverse health outcomes, ~$16.8B in damages avoided are predicted. Peak CO2 reductions and health benefits occur with 75% EV adoption and increased emission‐free energy sources (~$70B in damages avoided). When charging‐electricity from aggressive EV adoption is combustion‐only, adverse health outcomes increase substantially, highlighting the importance of low‐to‐zero emission power generation for greater realization of health co‐benefits. Our results provide a more nuanced understanding of the transportation sector's climate change mitigation‐health impact relationship.

Scenarios for transitioning cars from ICEV to BEVs and PHEVs using household level GPS travel data

There has been a continuous effort to quantify the expected greenhouse gas reductions from plug- in electric vehicles (PEVs). Most existing studies are based on standardized driving cycles to compare the performance of PEVs and conventional internal combustion engine (ICE) vehicles. This study is based on assigning the most efficient plug-in hybrid or full electric vehicle to a household based on the household travel behavior as collected by GPS tracking data of thousands of vehicles’ real trips in California, and it found that PEV adoption can reduce greenhouse gas emission by up to 65%. We further explore the market share difference in assigning optimal vehicle models by considering vehicle-based and household-based travel demand, and we found that, given currently available technology, in many cases adoption of Plug-in Hybrid Electric vehicles (PHEVs) will not necessarily result in significantly higher greenhouse gas (GHG) emissions (2.8% higher) compared to battery electric vehicles (BEVs), while PHEVs have advantages to satisfy household’s long-distance travel demand. However, if PHEV drivers never charge their vehicles, the achievable GHG emission reduction will be decreased by nearly 2/3.

Sound Quality Estimation of Electric Vehicles Based on GA-BP Artificial Neural Networks

The sound quality (SQ) and sound perception assessments of electric vehicles (EVs) clearly differ from those of conventional internal combustion engine vehicles (ICEVs). Therefore, it is essential to describe and evaluate the SQ of EVs. To evaluate the SQ in EVs, it is necessary to organize evaluators for conducting subjective jury tests, which are time-consuming and labor-intensive. In addition, the evaluation results are subject to the evaluators themselves and other external interferences. With the advancement of machine learning and artificial neural networks (ANNs), this problem can be well solved. This paper outlines a model for SQ estimation in EVs based on a genetic algorithm-optimized back propagation artificial neural network (GA-BP ANN). Moreover, the correlation between the physical-psychoacoustical parameters and the subjective SQ estimations obtained from the jury tests was investigated in this study. It was found that the GA-BP ANN SQ model has many advantages in comparison with the multiple linear regression (MLR) model in terms of precision and generalization. In addition, this method is ready to be applied for rapidly evaluating the SQ in EVs without jury tests, and it can also be of high significance in dealing with the acoustical designs and improvements of EVs in the future.

Environmental and Economic Benefits of a Battery Electric Vehicle Powertrain with a Zinc–Air Range Extender in the Transition to Electric Vehicles

Emissions and pollution from the transportation sector due to the consumption of fossil fuels by conventional vehicles have been negatively affecting the global climate and public health. Electric vehicles (EVs) are a cleaner solution to reduce the emission and pollution caused by transportation. Lithium-ion (Li-ion) batteries are the main type of energy storage system used in EVs. The Li-ion battery pack must be considerably large to satisfy the requirement for the vehicle’s range, which also increases the cost of the vehicle. However, considering that most people use their vehicles for short-distance travel during daily commutes, the large pack is expensive, inefficient and unnecessary. In a previous paper, we proposed a novel EV powertrain design that incorporated the use of a zinc–air (Zn–air) battery pack as a range-extender, so that a smaller Li-ion pack could be used to save costs. The design and performance aspects of the powertrain were analyzed. In this study, the environmental and economic benefits of the proposed dual-battery powertrain are investigated. The results from the new powertrain were compared with values from a standard EV powertrain with one large Li-ion pack and a conventional internal combustion engine vehicle (ICEV) powertrain. In addition, an air pollution model is developed to determine the total amount of pollution released by the transportation sector on Highway 401 in Ontario, Canada. The model was then used to determine the effects of mass passenger EV rollout on pollution reduction.

Battery-Aware Electric Truck Delivery Route Exploration

The energy-optimal routing of Electric Vehicles (EVs) in the context of parcel delivery is more complicated than for conventional Internal Combustion Engine (ICE) vehicles, in which the total travel distance is the most critical metric. The total energy consumption of EV delivery strongly depends on the order of delivery because of transported parcel weight changing over time, which directly affects the battery efficiency. Therefore, it is not suitable to find an optimal routing solution with traditional routing algorithms such as the Traveling Salesman Problem (TSP), which use a static quantity (e.g., distance) as a metric. In this paper, we explore appropriate metrics considering the varying transported parcel total weight and achieve a solution for the least-energy delivery problem using EVs. We implement an electric truck simulator based on EV powertrain model and nonlinear battery model. We evaluate different metrics to assess their quality on small size instances for which the optimal solution can be computed exhaustively. A greedy algorithm using the empirically best metric (namely, distance × residual weight) provides significant reductions (up to 33%) with respect to a common-sense heaviest first package delivery route determined using a metric suggested by the battery properties. This algorithm also outperforms the state-of-the-art TSP heuristic algorithms, which consumes up to 12.46% more energy and 8.6 times more runtime. We also estimate how the proposed algorithms work well on real roads interconnecting cities located at different altitudes as a case study.

Quantifying the impacts of micro- and mild- hybrid vehicle technologies on fleetwide fuel economy and electrification

Abstract Micro- and mild-hybridization (jointly labeled as M-HEV) is gaining popularity as a cost-effective technology for fuel economy improvement, but whether and how M-HEV may compete against less efficient conventional internal combustion engine vehicles (ICEV), more efficient full hybrid electric vehicles (HEV), and plug-in electric vehicles (PEV) is not well understood. This study aims at evaluating the impact of the market adoption of M-HEV on the average fuel economy of the new vehicle fleet and on the sales share of PEVs. The study reviews recent sales trends and market forecasts, and uses published estimates of manufacturing cost and fuel economy of M-HEV with an existing discrete choice model (Market Acceptance of Advanced Automotive Technologies or MA3T) to project the market penetration and impacts of M-HEV under different scenarios of M-HEV choice positions, designed to enhance conclusion robustness. It is found that among engine-based powertrain choices, micro-HEV appears to be the most cost-effective, followed by ICEVs, mild-HEV and finally full HEVs. M-HEV technologies are likely to improve fleetwide average fuel economy without significant adverse effects on sales of plug-in electric vehicles, and are likely to remain highly competitive outside PEVs through 2050.

Characteristics of Battery SOC According to Drive Output and Battery Capacity of Parallel Hybrid Electric Vehicle

To mitigate global warming caused by vehicles, emission regulations have been implemented for all automobiles. Hybrid electric vehicles (HEVs) are being designed to meet consumer demand for eco-friendly vehicles that offer increased power and improved fuel efficiency. HEVs are powered by an internal combustion engine (ICE) in combination with one or more electric motors that use electrical energy stored in a secondary battery, which is typically a lithium-based battery. With the use of such a hybrid drivetrain system, the fuel efficiency can be improved over that of conventional ICE vehicles. In this study, we conducted a vehicle-driving experiment to evaluate a transmission-mounted electric device (TMED) type parallel HEV using a chassis dynamometer and on-board diagnostics (OBD) signal-measuring equipment. In addition, we performed a numerical analysis using the CRUISE vehicle simulation code with experimental data. In our analysis, the engine output, which affects the torque of the drive motor, and the capacity (energy density) of the lithium-ion polymer battery were set as variables that affect the fuel-economy performance. As a result of this numerical analysis, a hybrid power-drivetrain model based on CRUISE was developed, and the current balance was evaluated according to the change in the battery capacity. We found that the battery state of charge (SOC) dropped because of a decrease in battery capacity. Thus, we predicted that the lithium-ion battery capacity would be reduced.

Forecasting the value of battery electric vehicles compared to internal combustion engine vehicles: The influence of driving range and battery technology

Battery electric vehicles (BEVs) are now clearly a promising candidate in addressing the environmental problems associated with conventional internal combustion engine vehicles (ICEVs). However, BEVs, unlike ICEVs, are still not widely accepted in the automobile market but continuing technological change could overcome this barrier. The aim of this study is to assess and forecast whether and when design changes and technological improvements related to major challenges in driving range and battery cost will make the user value of BEVs greater than the user value of ICEVs. Specifically, we estimate the relative user value of BEVs and ICEVs resulting after design modifications to achieve different driving ranges by considering the engineering trade-offs based on a vehicle simulation. Then, we analyze when the relative user value of BEVs is expected to exceed ICEVs as the energy density and cost of batteries improve because of ongoing technological change. Our analysis demonstrates that the relative value of BEVs is lower than that of ICEVs because BEVs have high battery cost and high cost of time spent recharging despite high torque, high fuel efficiency, and low fuel cost. Moreover, we found the relative value differences between BEVs and ICEVs are found to be less in high performance large cars than in low performance compact cars because BEVs can achieve high acceleration performance more easily than ICEVs. In addition, this study predicts that in approximately 2050, high performance large BEVs could have higher relative value than high performance large ICEVs because of technological improvements in batteries; however low performance compact BEVs are still very likely to have significantly lower user value than comparable ICEVs until well beyond 2050.

Life Cycle Cost Assessment of Electric Vehicles: A Review and Bibliometric Analysis

The transportation sector has been reported as a key contributor to the emissions of greenhouse gases responsible for global warming. Hence, the need for the introduction of electric vehicles (EVs) into the transportation sector. However, the competitiveness of the EVs with the conventional internal combustion engine vehicles has been a bone of contention. Life cycle cost analysis (LCCA) is an important tool that can be employed to determine the competitiveness of a product in its early stage of production. This review examines different published articles on LCCA of EVs using Scopus and Web of Science databases. The time trend of the published articles from 2001 to 2019 was examined. Moreover, the LCC obtained from the different models of EVs were compared. There was a growing interest in research on the LCC of EVs as indicated by the upward increase in the number of published articles. A variation in the LCC of the different EVs studied was observed to depend on several factors. Based on the LCC, EVs were found not yet competitive with conventional internal combustion engine cars due to the high cost of batteries. However, advancement in technologies with incentives could bring down the cost of EV batteries to make it competitive in the future.

Wireless Power Transfer Topologies used for Static and Dynamic Charging of EV Battery: A Review

AbstractElectric vehicles (EV) are found to be a good alternative for the conventional internal combustion (IC) engine vehicles in transportation sector due to its various advantages. Now-a-days, wireless charging of EV battery is preferred among the various methods used for charging EV battery. In this paper, extensive review is carried out on various methods used for wireless charging of an EV battery. Different techniques used for transferring power in wireless mode to charge the EV battery are static EV charging technique and dynamic EV charging technique. Static wireless EV battery charging technique adopts inductive and capacitive method for transferring power whereas, dynamic wireless EV battery charging technique adopts only inductive method for transferring power. These techniques are discussed thoroughly in this paper and broad review is carried out with a focus on the compensation circuit topologies, types of core for magnetic coupled inductors, different converters and controllers used for wireless power transfer (WPT) system. Also, design aspects of an static wireless EV battery charging system along with its equivalent circuit analysis is presented in this paper. Challenges and future development in wireless charging of EV battery is also explained in this paper.

Comparing Fuel Consumption and Emission Levels of Hybrid Powertrain Configurations and a Conventional Powertrain in Varied Drive Cycles and Degree of Hybridization

Hybrid electric powertrains in automotive applications aim to improve emissions and fuel economy with respect to conventional internal combustion engine vehicles. Variety of design scenarios need to be addressed in designing a hybrid electric vehicle to achieve desired design objectives such as fuel consumption and exhaust gas emissions. The work in this paper presents an analysis of the design objectives for an automobile powertrain with respect to different design scenarios, i. e. target drive cycle and degree of hybridization. Toward these ends, four powertrain configuration models (i. e. internal combustion engine, series, parallel and complex hybrid powertrain configurations) of a small vehicle (motorized three wheeler) are developed using Model Advisor software and simulated with varied drive cycles and degrees of hybridization. Firstly, the impact of vehicle power control strategy and operational characteristics of the different powertrain configurations are investigated with respect to exhaust gas emissions and fuel consumption. Secondly, the drive cycles are scaled according to kinetic intensity and the relationship between fuel consumption and drive cycles is assessed. Thirdly, three fuel consumption models are developed so that fuel consumption values for a real-world drive cycle may be predicted in regard to each powertrain configuration. The results show that when compared with a conventional powertrain fuel consumption is lower in hybrid vehicles. This work led to the surprisingly result showing higher CO emission levels with hybrid vehicles. Furthermore, fuel consumption of all four powertrains showed a strong correlation with kinetic intensity values of selected drive cycles. It was found that with varied drive cycles the average fuel advantage for each was: series 23 %, parallel 21 %, and complex hybrids 33 %, compared to an IC engine powertrain. The study reveals that performance of hybrid configurations vary significantly with drive cycle and degree of hybridization. The paper also suggests future areas of study.

A case for the internal combustion engine powered vehicle

The damaging effect of climate change has made mankind to continuously pursue means of reversing global warming caused by greenhouse gases. CO2 gas according to available data for the year 2010 represents a whopping 76% of the emitted global greenhouse gases hence, making it a focal point in the reduction of greenhouse gases. Many nations are looking at the halt of the internal combustion engine powered vehicles and are making favourable policies for the adoption of electric vehicles to reduce the emission of greenhouse gas. This study reviews the contribution of the internal combustion engine powered vehicle to the global CO2 gas emission, comparison of its CO2 emission rate to that of the electric vehicle based on their life cycle assessment, and the health challenges that the disposal of the electric vehicle batteries can pose to human. The CO2 emission rate of electric vehicles based on life cycle assessment is comparable to that of internal combustion engine vehicles power on gasoline and diesel, and based on emission per KWh of electricity generation in the UK, Germany, India, and China, the diesel powered internal combustion engine was observed to be better than that of the average electric vehicle based on a kilometer of road travel, asides the potential health risk which the subsequent disposal of batteries can cause. A great boost in the reduction of CO2 emission can be made with the development of the commercial production and adoption of synthetic fuel for use with the conventional internal combustion engine vehicles.

Strategic Environmental Assessment with the Penetration of Electric Vehicles in Transport Network

The ownership of electric vehicles, including plug-in electric vehicles (PEVs) and hybrid electric vehicles (HEVs), begins to be prevalent at present and poses as a promising way to alleviate environmental pollutions. However, the traditional method of environmental impact assessment is encountering challenges due to the large differences between conventional internal combustion engine vehicles (ICEVs) and electric vehicles. This paper proposes a novel SEA method for the penetration of electric vehicles at link level. An absorbing Markov chain model is formulated to represent the transition process among ICEVs, PEVs, and HEVs in the future, where PEV is an absorbing state. In addition, both HEV and PEV travelers are assumed to behave in the same manner as conventional ICEV travelers. As a result, the vehicle fleet composition is consistent with their market shares on each link. However, the three vehicle types are distinguished by their respective emissions rates. Therefore, the strategic environmental assessment can be worked out based on market penetration level and link traffic flows. For a given road network, transport system equilibrium is proposed to calculate link traffic flows. It is a four-step sequential model with feedback channel which can be solved by method of successive averages (MSA) effectively. For sustainable development, China plans to build a new city named Xiong’an nearby the capital Beijing. The strategic environmental assessment is conducted using the development of Xiong’an as an experimental study to demonstrate the effectiveness of proposed method. This research is very useful in urban planning with environmental constraints.

Cathode Chemistries and Electrode Parameters Affecting the Fast Charging Performance of Li-Ion Batteries

Abstract Li-ion battery fast-charging technology plays an important role in popularizing electric vehicles (EV), which critically need a charging process that is as simple and quick as pumping fuel for conventional internal combustion engine vehicles. To ensure stable and safe fast charging of Li-ion battery, understanding the electrochemical and thermal behaviors of battery electrodes under high rate charges is crucial, since it provides insight into the limiting factors that restrict the battery from acquiring energy at high rates. In this work, charging simulations are performed on Li-ion batteries that use the LiCoO2 (LCO), LiMn2O4 (LMO), and LiFePO4 (LFP) as the cathodes. An electrochemical-thermal coupling model is first developed and experimentally validated on a 2.6Ah LCO based Li-ion battery and is then adjusted to study the LMO and LFP based batteries. LCO, LMO, and LFP based Li-ion batteries exhibited different thermal responses during charges due to their different entropy profiles, and results show that the entropy change of the LCO battery plays a positive role in alleviating its temperature rise during charges. Among the batteries, the LFP battery is difficult to be charged at high rates due to the charge transfer limitation caused by the low electrical conductivity of the LFP cathode, which, however, can be improved through doping or adding conductive additives. A parametric study is also performed by considering different electrode thicknesses and secondary particle sizes. It reveals that the concentration polarization at the electrode and particle levels can be weaken by using thin electrodes and small solid particles, respectively. These changes are helpful to mitigate the diffusion limitation and improve the performance of Li-ion batteries during high rate charges, but careful consideration should be taken when applying these changes since they can reduce the energy density of the batteries.

Comparison of the Overall Energy Efficiency for Internal Combustion Engine Vehicles and Electric Vehicles

Abstract The tremendous growth in the transportation sector as a result of changes in our ways of transport and a rise in the level of prosperity was reflected directly by the intensification of energy needs. Thus, electric vehicles (EV) have been produced to minimise the energy consumption of conventional vehicles. Although the EV motor is more efficient than the internal combustion engine, the well to wheel (WTW) efficiency should be investigated in terms of determining the overall energy efficiency. In simple words, this study will try to answer the basic question – is the electric car really energy efficient compared with ICE-powered vehicles? This study investigates the WTW efficiency of conventional internal combustion engine vehicles ICEVs (gasoline, diesel), compressed natural gas vehicles (CNGV) and EVs. The results show that power plant efficiency has a significant consequence on WTW efficiency. The total WTW efficiency of gasoline ICEV ranges between 11–27 %, diesel ICEV ranges from 25 % to 37 % and CNGV ranges from 12 % to 22 %. The EV fed by a natural gas power plant shows the highest WTW efficiency which ranges from 13 % to 31 %. While the EV supplied by coal-fired and diesel power plants have approximately the same WTW efficiency ranging between 13 % to 27 % and 12 % to 25 %, respectively. If renewable energy is used, the losses will drop significantly and the overall efficiency for electric cars will be around 40–70% depending on the source and the location of the renewable energy systems.