The Earth is currently undergoing climate change due to the increase of anthropogenic emissions of greenhouse gases such as CO2
]. Thus, many nations around the globe are making efforts to reduce their carbon footprint [2
]. The U.S. Energy Information Administration (EIA) estimates that motor vehicles contribute to about 30% of total U.S energy-related CO2
]. Hence, over the years, the U.S. has attempted to reduce the amount of CO2
emitted by Internal Combustion Engines (ICEs). ICE vehicles (ICEVs) are also a major source of air pollution in many urban areas. Many “green” methods of propulsion have been developed and improved over the past 20 years such as hydrogen fuel cell and electric vehicles [4
]. In an effort to reduce air pollution and emissions of greenhouse gases, the California Air Resources Board aims to increase the sales of Zero Emission Vehicles (ZEVs) significantly by 2050 [5
Original Equipment Manufacturers (OEMs) have chosen Battery Electric Vehicles (BEVs) over hydrogen fuel cell technology for light duty vehicles in recent years considering the former has been more widely commercialized than fuel cell models. This phenomenon is intriguing because besides very luxurious models such as Tesla model X and S, selling other battery-powered vehicles is not very economically profitable for OEMs at the current volume of sales and prices. True vehicle costs over a 20-year lifetime for a 2015 mid-sized ICEV and BEV are estimated to be $
19,000 and $
38,000 respectively. The majority of the BEVs cost results from the battery fabrication process [6
] which utilizes lithium, a scarce resource. At current lithium extraction levels, the production of BEV at significant annual vehicle sales market share is not likely [7
]. In the U.S. over 1 million vehicles were sold in 2017 and approximately 12,000 of those vehicles were BEVs [8
]. This means that less than 1% of vehicles sold in the U.S. were BEVs and yet, OEMs have produced and sold more BEVs in the past few years than at any time in history.
Mass production of battery for vehicle use will lead to price reduction due to the increased scale, cost saving, and improved manufacturing technologies. The Joint Agency Draft Technical Assessment Report [9
] predicts an increase in battery content and associated costs even with the reduced battery prices for a BEV equivalent to an ICE vehicle. Battery technologies have improved and will continue to do so. However, there is no quantum leap yet in the energy density of the battery. The batteries OEMS use in their BEVs are all based on lithium ion battery technologies and there is no sign of big change for the commercially available and mass-produced batteries for now. The California Air Resource Board’s midterm review report on ZEV [5
] states “while there are lots of promising advancements happening in research labs around the world every day, there is unlikely to be a ‘silver bullet’ that will suddenly meet the goals [10
] for energy storage technology”.
While there are many BEVs commercially available, there is no standard which can regulate and promote high energy efficiency of BEV. The motivation of this study is to characterize the status of BEV technology with respect to BEV performance parameters so that the public and regulators can understand limitations and potentials of BEV. Components such as vehicle curb weight and battery capacity are important to determine a vehicle’s energy efficiency. An and Santini [11
] compared the relationship between vehicle mass (or weight) and fuel economy for conventional vehicles (CV) and hybrid electric vehicles (HEV). They reported that fuel economy of HEVs is significantly improved with little or no change in vehicle mass (or weight) compared to CV. Once a switch to hybrid powertrain is made, then mass reduction in improving fuel economy is diminished relative to conventional vehicles. In a similar context, the vehicle mass vs. fuel economy relationship may be different for BEV compared to CV and HEV. This is an important topic to be investigated but there is no literature reporting on the impact of vehicle mass (or weight) to fuel economy for BEVs using data from multiple vehicles. The closest comparisons available in the literature were found to be: impact of vehicle weight on energy efficiency (which can be translated to fuel economy) at constant vehicle speeds for EV during 1994 Department of Energy (DOE) EV competition [12
], and impact of two EV masses on energy consumption over different driving cycles [13
Though BEVs themselves produce no emissions, they do consume electrical energy for charging and the battery fabrication process. This electricity is generated from power plants which burn fossil fuels. As such, BEVs are considered to be efficient as they compensate for this usage of electrical energy to minimize their impact on global warming. Regardless, there is no fuel economy standard for BEVs worldwide. Analysis of vehicle performance parameters with respect to fuel economy can be essential information if agencies are to consider legislating fuel economy standards for BEVs.
This paper investigates BEVs based on vehicle specification, fuel economy, and experimental testing data available to fill this gap in literature knowledge. The paper aims to find general relationships between vehicle performance parameters such as driving range, fuel economy, and vehicle parameters such as vehicle weight and battery capacity. As BEV manufacturers are not required to provide key vehicle parameters publicly, they often keep from disclosing them for marketing purposes, claiming them to be proprietary information. Hence, it has been challenging to collect data necessary for analysis. Vehicles of investigation in this study are all light duty passenger BEVs. The analysis is limited to commercially available BEVs due to the availability of the data. The results of this study will help the public to understand the current capabilities and limitations of the BEV technology and regulators to legislate fuel economy standards for BEVs.
2. Vehicle Data Collection
For the driving range per full charge and fuel economy investigation, commercially available light duty vehicles in the U.S. from 12 auto manufacturers with model years ranging from 2011 to 2018 were used (Table A1
). Currently, there is a lack of information on the specification of BEVs, and BEV manufacturers should disclose more of the aforementioned in the near future for better analysis and studies. The data collected depended on the availability to the public. The raw data was extracted from three main sources: INL (Idaho National Laboratory) website, EPA Fuel Economy website, and the websites of BEV manufacturers and internet in general. INL had most of the vehicle specification data for the cars because of their advanced vehicle testing activity. EPA-rated vehicle performance data was obtained from the fuel economy website. Curb weight and other data were obtained from internet sources such as “vehicle history” or directly from the manufacturers’ websites. A small subset of data was also found from Argonne National Laboratory (ANL) website and the majority of their data overlapped with our existing data set in Table A1
and so the ANL data was not referred to in this analysis.
Peak battery power vs. 0–60 mph acceleration time (Table A2
) and the influence of weather conditions on fuel economy (Table A3
) used the data obtained from INL. The car models are from various manufacturers commercially available in the U.S. like Chevrolet, Kia, Mercedes, Volkswagen, BMW, Ford, Nissan, and Mitsubishi. The model years ranged from 2011 to 2015. Battery weight vs. battery capacity data were collected all above three sources and the raw data is provided in Table A4
4. Discussion and Conclusions
The results from this study can be used in many ways. BEV manufacturers can use the scaling relationships for preliminary designs of new BEVs. The public (and/or engineers and scientists) can use them to understand limitations and possibilities of current technologies and required improvement of BEV parts for the future, especially in terms of battery weight, power density, and power output for required and/or desired BEV performance. For instance, consider designing a BEV which has 400 miles driving range. Table 1
shows a sample calculation using regression lines in Figure 1
, Figure 2
, Figure 3
, Figure 4
, Figure 5
, Figure 6
and Figure 7
with assumed vehicle weights. It provides required battery weights and capacities with expected fuel economies for different hypothetical vehicle weights. As expected, the results show that high power density of battery and low curb weight of the vehicle are key parameters for the increasing BEV efficiency. It is recommended to investigate other important aspects of BEV batteries especially in terms of charging and discharging abilities in the future research.
More models of electric vehicles are available in recent years and it is important for engineers, the public, and manufacturers to know the limitations and capabilities of the current technology. This study provided these answers by looking into scaling trends of electric vehicle performance parameters from model year 2011 to 2018. Excellent correlations were found between the EPA driving range per full charge of a battery and the battery capacity normalized by vehicle weight (i.e., battery capacity divided by vehicle curb weight). Short-driving-range BEVs (driving range < 150 miles) have a slope of 5002 miles/(kWh/kg) with R2 = 0.73 while long-driving-range BEVs (driving range > 150 miles) have a slope of 6074 miles/(kWh/kg) with R2 = 0.91. When a regression line was drawn for all vehicles, the slope was found to be 8356 miles/(kWh/kg) with R2 = 0.96. A relatively strong correlation was found between EPA city fuel economy (MPGe) and vehicle curb weight with a slope of −0.04 MPGe/kg and R2 = 0.73 while a weak correlation was found between EPA highway fuel economy (MPGe) and vehicle curb weight with a slope of −0.01 MPGe/kg and R2 = 0.16. Unique separate trend lines existed between Tesla and non-Tesla vehicles for correlations between city and highway fuel economy. Non-Tesla vehicles showed better city fuel economy for the vehicles with the same highway fuel economy as Tesla vehicles. An inverse power correlation was found between 0–60 mph acceleration time and peak power output from battery/vehicle curb weight for 10 BEVs investigated in Idaho National Laboratory. For a linear relationship, 0.18 kWh/kg, between battery capacity and battery weight, the value of the x-intercept was 124 kg, which is the average weight of inactive materials such as battery housing. Fuel economy data over the UDDS cycle was normalized against that of a normal temperature of 72 F with no AC on. On average, fuel economy drops by 19 ± 5% for the summer driving condition with AC on and 47 ± 7% for the winter driving condition.
A lot of researchers want to improve vehicle parameters such as range and fuel economy but do not have available material to refer to and draw assumptions from. With the graphs available from this study, researchers can focus on developing one parameter using expected results of other parameters. Battery technology varies with manufacturers and Tesla cars had the highest ranges. However, they had lower city fuel economy owing to higher vehicle curb weight. While most of the lighter cars were not as efficient as Tesla, there were some new vehicles like 2017 Hyundai Ioniq and 2017 Chevy Bolt EV that had better fuel economy with lower curb weight than Tesla. Battery technology used for these outlier cars can be investigated for future research. Improving battery technology and enabling a longer driving range has an effect on Li-ion extraction rates and might require technology beyond Li-ion. For this purpose, trends between current rates of Li-ion extraction, battery cost and capacity are all factors that need to be further analyzed. The results of this study follow our intuition with specific parameters and linear correlations. This study proposes key BEV specifications and performance test results to be made publicly available and required by regulations in the future to promote research and development of BEV technologies and to facilitate analysis like this study for the benefit of the public.