Battery Electric Vehicle Sales Research Articles

Hybrid LSTM-GBRT based machine learning technique implementation for electric vehicle sales prediction analysis

ABSTRACT The investigation of machine learning models in Europe and India for predicting future sales of electric cars (EVs) worldwide has been the focus of present research. In this study, Long Short-Term Memory (LSTM), Support Vector Regression (SVR), Autoregressive Integrated Moving Average (ARIMA), Linear Regression, hybrid long- and short-term memory neural network model and gradient boosted regression trees model (LSTM-GBRT) models based machine learning techniques are compared for performance analysis to predict EV sales. Moreover, in this study, a hybrid LSTM-GBRT technique was developed, which forecasts EV sales, particularly for Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs) over the next five years. During the prediction of EV sales, it has been validated that hybrid LSTM-GBRT technique has better predictive power. In addition, the present study attempts to provide estimated sales statistics for the designated locations. The results indicate that EV industry is evolving, with India showing a strong growth rate in BEV sales and establishing itself as a major participant in the global EV scenario by showing a notable increase in its share of worldwide EV sales volume by 2027. Conversely, the performance of EV sales in Europe has been analysed and validated through the proposed LSTM-GBRT model.

The Environmental Impacts of Future Global Sales of Hydrogen Fuel Cell Vehicles

During the last decade, developing more sustainable transportation modes has become a primary objective for car manufacturers and governments around the world to mitigate environmental issues, such as climate change, the continuous increase in greenhouse gas (GHG) emissions, and energy depletion. The use of hydrogen fuel cell technology as a source of energy in electric vehicles is considered an emerging and promising technology that could contribute significantly to addressing these environmental issues. In this study, the effects of Hydrogen Fuel Cell Battery Electric Vehicles (HFCBEVs) on global GHG emissions compared to other technologies, such as BEVs, were determined based on different relevant factors, such as predicted sales for 2050 (the result of the developed prediction model), estimated daily traveling distance, estimated future average global electricity emission factors, future average Battery Electric Vehicle (BEV) emission factors, future global hydrogen production emission factors, and future average HFCBEV emission factors. As a result, the annual GHG emissions produced by passenger cars that are expected to be sold in 2050 were determined by considering BEV sales in the first scenario and HFCBEV replacement in the second scenario. The results indicate that the environmental benefits of HFCBEVs are expected to increase over time compared to those of BEVs, due to the eco-friendly methods that are expected to be used in hydrogen production in the future. For instance, in 2021, HFCBEVs could produce more GHG emissions than BEVs by 54.9% per km of travel, whereas in 2050, BEVs could produce more GHG emissions than HFCBEVs by 225% per km of travel.

Global material flow analysis of end-of-life of lithium nickel manganese cobalt oxide batteries from battery electric vehicles.

The global market for battery electric vehicles (BEVs) is continuously increasing which results in higher material demand for the production of Li-ion batteries (LIBs). Therefore, the end of life (EOL) of batteries must be handled properly through reusing or recycling to minimize the supply chain issues in future LIBs. This study analyses the global distribution of EOL lithium nickel manganese cobalt (NMC) oxide batteries from BEVs. The Stanford estimation model is used, assuming that the lifespan of NMC batteries follows a Weibull distribution. The global sales data of NMC batteries from 2009 to 2018 were collected and the sales data from 2019 to 2030 were estimated based on historical trends and BEV development plans in the top 10 countries for BEV sales. The result shows a view of EOL NMC batteries worldwide. In 2038, China, South Korea and the United States (US) will be the three leading countries in the recovery of NMC battery materials. An overall global flow of NMC battery materials (aluminium, copper, manganese, steel, lithium and graphite/carbon) was also predicted in this research. This study estimated the waste potential of NMC battery materials specifically in the top 10 countries and also in other countries. Finally, the economic value estimation results for recovered materials indicated that copper, aluminium and manganese will have cumulative economic values of 7.9, 4.4 and 3.9 billion US dollars in 2038, respectively. As this study considers the different specific energy of NMC batteries in the coming years due to technological advancement, the findings can provide a more realistic insight into the future demand for NMC battery materials. This study reveals that a high number of EOL NMC batteries will be accumulated in 2038 in several countries. Therefore, large-scale recycling infrastructures should be set up to improve the efficiency of the recovery of battery materials.

Accelerating electric vehicle uptake: Modelling public policy options on prices and infrastructure

• We model policy options to accelerate passenger Battery EV diffusion in Australia. • Meeting recharger deployment targets as fleet grows is crucial to reach 100% uptake. • Subsidising BEV purchase brings forward price-parity tipping point. • Recharger and vehicle rebate policies costing AUD37.4 billion speed up transition. • Emissions reduction is best when policy introduced at earliest possible date. Transitioning to passenger battery electric vehicles (BEV) can mitigate climate change impacts of road transportation. We develop a novel BEV policy model, nesting it within a national-scale macroeconomic system dynamics model ( iSDG-Australia ) to simulate a suite of policy pathways. We model combinations of infrastructure support and subsidies, which bring forward the price-parity tipping point, thus rapidly accelerating BEVs’ share of new car sales. However, ongoing complementary charging infrastructure investment is critical to reach 100% new BEV car sales by 2050 in Australia. Even with a rapid transition, the modelled fleet would not achieve net-zero greenhouse gas emissions by 2050 due to vehicle longevity; and suddenly ceasing financial incentives could retard BEV sales by a decade. Based on our assumptions, results suggest emissions reductions are maximised by the fastest transition of the passenger vehicle fleet to BEVs, entailing government policy support from 2020 to 2050, for both adequate infrastructure deployment (AUD17.9b) and vehicle rebates (AUD19.5b), which achieves earlier BEV price-parity with fossil-fuelled vehicles.

Mirroring in production? Early evidence from the scale-up of Battery Electric Vehicles (BEVs)

AbstractThe mirroring hypothesis is central to modularity theory, positing isomorphism between technical interdependencies of a product and organizational arrangements. When a product’s design becomes more modular, a full mirroring response would change both its manufacturing and its supply chain. We evaluate this prediction for Battery Electric Vehicles (BEVs), observing whether automakers have mirrored the modular BEV architecture in either internal production processes, external sourcing arrangements, or both. Our data from 19 automakers show that, to date, BEVs are manufactured in their assembly plants alongside conventional internal combustion engine vehicles (ICEVs). New automakers with fully BEV plants utilize essentially the same production process. Furthermore, automakers make—or ally to make—key Electric Vehicle (EV) systems, rather than outsourcing them. We discuss the implications of this partial mirroring for modularity theory and ask whether these arrangements will persist once BEV sales surpass ICEVs.

The relationship between public charging infrastructure deployment and other socio-economic factors and electric vehicle adoption in France

Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs) offer a promising choice to replace fossil-fuel dependent Internal Combustion Engine Vehicles (ICEVs) with a low-emission transport solution. Governments, automotive manufacturers, and charging infrastructure operators have deployed market-boosting initiatives to incentivize purchase. Yet, their market diffusion is limited by several barriers. To shed light on the main barriers, and based on an extensive state-of-the-art, we used an original database and statistically analyzed the relationship of 21 socio-demographic, technical, and economic factors on BEV and PHEV market shares, separately, in 94 French departments from 2015 to 2019, using mixed-effect regression. We find different covariates related to BEV and PHEV sales, respectively, suggesting the two markets respond to different incentives. The number of available BEV/PHEV models and energy prices are positively correlated with BEV and PHEV adoption. Fast, ultrafast charger density and local incentives positively relate with BEV sales, while slow-and-normal charger density to PHEV sales. Contrarily, national subsidies, relative to vehicles’ prices, are negatively correlated with PHEVs sales and is open for further studies. Based on the results, policy recommendations are considered for the automotive industry, charging operators, and local authorities to draw a roadmap for electric mobility transition in France.

The Impacts of Battery Electric Vehicles on the Power Grid: A Monte Carlo Method Approach

Balancing energy demand and supply will become an even greater challenge considering the ongoing transition from traditional fuel to electric vehicles (EV). The management of this task will heavily depend on the pace of the adoption of light-duty EVs. Electric vehicles have seen their market share increase worldwide; the same is happening in Portugal, partly because the government has kept incentives for consumers to purchase EVs, despite the COVID-19 pandemic. The consequent shift to EVs entails various challenges for the distribution network, including coping with the expected growing demand for power. This article addresses this concern by presenting a case study of an area comprising 20 municipalities in Northern Portugal, for which battery electric vehicles (BEV) sales and their impact on distribution networks are estimated within the 2030 horizon. The power required from the grid is estimated under three BEV sales growth deterministic scenarios based on a daily consumption rate resulting from the combination of long- and short-distance routes. A Monte Carlo computational simulation is run to account for uncertainty under severe EV sales growth. The analysis is carried out considering three popular BEV models in Portugal, namely the Nissan Leaf, Tesla Model 3, and Renault Zoe. Their impacts on the available power of the distribution network are calculated for peak and off-peak hours. The results suggest that the current power grid capacity will not cope with demand increases as early as 2026. The modeling approach could be replicated in other regions with adjusted parameters.

Prediction of the “Tipping Point” to Widespread Uptake of Battery Electric Vehicles in China via Nonlinear Curve-Fitting Method

<p>The “Tipping Point” is a term that is widely used today to describe that a time or threshold once being surpassed would result in exponential growth in technology adoption or product sales in a specific industry. China’s BEV industry has grown tremendously in the past 10 years and recently, and China has been leading both BEV sales and manufacturing in the world. Thus, this paper aims to investigate the “Tipping Point” timeframe for Battery Electric Vehicles (BEVs) penetration in China. The major work is conducted in 3 steps. 1. This paper firstly defined the exactitude of “Tipping Point” as a 16% market penetration rate from Roger’s technology adoption model. 2. Then this paper used a simple exponential curve formula using the Levenberg–Marquardt Algorithm (LMA) calculation method to conduct nonlinear curve fitting modeling for various nations and testify the validity of our formula used. 3. Finally, after getting a positive result from these sample countries, this paper continues using this method to predict the 16% “Tipping Point” from several current predictions reports. It concludes with a calculated assumption that this 16% BEV market penetration rate would most likely occur by the end of 2024.</p>

A deployment model of EV charging piles and its impact on EV promotion

The construction of public-access electric vehicle charging piles is an important way for governments to promote electric vehicle adoption. The endogenous relationships among EVs, EV charging piles, and public attention are investigated via a panel vector autoregression model in this study to discover the current development rules and policy implications from the historical panel data in China. Five policies related to EV charging piles, EV purchase subsidies, commercial land prices, and retail gasoline prices are controlled as exogenous variables in the model. The results indicate that EV and charging piles diffusion do interact, and public attention plays a nexus role in EV and charging piles deployment. Reducing the electricity rate is the most effective policy approach to promote EV charging piles. Subsidising the construction cost has an insignificant impact on charging piles diffusion in this study, and several possible reasons have been discussed. The promotion effect of direct-current charging piles on EV sales is twice that of alternating-current charging piles in the one-year simulation of our model. Increasing the number of EV charging piles has a significant impact on battery electric vehicle sales but not on plug-in hybrid electric vehicle sales.

Can China’s BEV market sustain without government subsidies?: An explanation using cues utilization theory

After several years of intensified implementing the subsidy policy for battery electric vehicles (BEVs) intending to boost China’s BEV market and the development of China’s domestic BEV industry, the Chinese government plans to totally abolish the government subsidy policy in 2020, one critical issue faced is that whether the BEV market can sustain without the subsidies. This work aims to answer this question, which firstly started by building a theoretical scheme for understanding the roles of China’s favorable government policies and market forces on motivating consumers to adopt BEVs based on the cues utilization theory. In particular, the commercial BEV demonstration policies and Chinese BEV brand reputation were considered in this scheme. And then by building several indexes to reflect the real effects of the market forces and government policies considered in this scheme, a structural equation model is constructed to explore how BEV sales and BEV battery technology were impacted during 2016/01–2019/12. The final results prove that China’s BEV policies succeeded a lot in providing consumers the extrinsic cues helping them to reduce perceived risks of purchasing BEVs, and thus contributed to boosting China’s BEV sales. Constructing more charging piles exerted the most significant effects, followed by the improving global reputation of Chinese BEV brands and increase in commercial BEV sales. The subsidy policy did not contribute the growth of China’s BEV sales directly, but indirectly through the mediation of improved BEV battery technologies and the magnitude is rather low, indicating that the growth of China’s BEV sales has already been less driven by the government subsidies, from which we can conclude that it is very possible for China’s BEV market to sustain without government subsidies. Policy implications for other governments are provided at the end.

Consumer intentions to purchase battery electric vehicles in Korea

In Korea, the sales of battery electric vehicles (BEVs) have increased since their introduction to the market in 2010. However, considering the government's plan to introduce BEVs, current BEVs sales in Korea are still below targeted numbers. Among several reasons for this, consumers' intentions and desired time to purchase BEVs are the most important. This study identifies the factors that affect and influence these two reasons. We used survey data containing these two reasons as stated preferences and applied a binary choice model to estimate consumers' intentions to purchase BEVs and an ordered model to estimate the desired period for purchasing BEVs. The study's results show that prior experience driving BEVs and other additional factors—including number of household vehicles, educational level, and perception of government incentives and public parking benefits—have a significant effect on consumers' intentions and desired time to purchase BEVs. Therefore, providing consumers with prior opportunities to drive BEVs is critical for BEVs' full market penetration in Korea.

The economic and environmental impacts of tax incentives for battery electric vehicles in Europe

Vehicle taxes and purchase subsidies have been used frequently to provide incentives for electric vehicle adoption. To examine the role of the incentives in reducing total ownership costs of battery electric vehicles (BEVs), increasing BEV sales, and obtaining environmental benefits from switching to BEVs, we carry out cost–benefit analyses and ordinary least square regressions. We study 10 pairs of BEVs and their internal combustion engine vehicle (ICEV) counterparts across 28 European countries from 2012 to 2014. The results show that, under the incentive schemes, the costs reduced by switching to large BEVs from their ICEV counterparts are larger than the costs reduced by switching to small BEVs from their ICEV counterparts. Owing to the cost-reduction effect, a 10% increase of the total tax incentive leads to an increase in the sales share of BEVs by around 3% on average. Finally, we find that it is still costly to use the tax incentives to reduce CO2 emissions and other environmental externalities through transport electrification, despite recent improvements in greening electricity generation and lowering battery costs.

The mobility revolution as seen through Norwegian eyes

ABSTRACTThe Norwegian electric vehicle deployment success came about for several reasons. The country's huge hydropower capacity delivering 99% of its electric energy has been the backbone of the argument for the introduction of electric vehicles here since 1988. This was coupled with the design and implementation of the world's most generous incentives for battery electric vehicles (BEV) from 1994, an act that later led to soaring sales. In 2012, 3% of all cars sold in Norway were BEVs and Norway was the World's 5th largest volume market for BEVs. By the end of 2017 there were over 142,490 BEVs and by 2020 it is forecasted that every second car sold will be a BEV. However, in addition to the BEV sales, the sales of Plug in Hybrid Electric Vehicles (PHEV) have soared. In the first two months of 2017, 49% of all sold personal cars, not vans and buses, in Norway were BEVs and PHEVs. The order book for March 2018 of one large supplier, Volkswagen (VW), showed that 70,4% of the personal car orders were electric (BEVs and PHEVs). The goal is an all-electric vehicle fleet. The paper responds to three questions: 1. How did this success come about? 2. What is the link between electric vehicles and buildings? 3. What can case studies such as that of Norway teach us about the mobility revolution?

Impact of public electric vehicle charging infrastructure

This work uses market analysis and simulation to explore the potential of public charging infrastructure to spur US battery electric vehicle (BEV) sales, increase national electrified mileage, and lower greenhouse gas (GHG) emissions. By employing both scenario and parametric analysis for policy driven injection of public charging stations we find the following: (1) For large deployments of public chargers, DC fast chargers are more effective than level 2 chargers at increasing BEV sales, increasing electrified mileage, and lowering GHG emissions, even if only one DC fast charging station can be built for every ten level 2 charging stations. (2) A national initiative to build DC fast charging infrastructure will see diminishing returns on investment at approximately 30,000 stations. (3) Some infrastructure deployment costs can be defrayed by passing them back to electric vehicle consumers, but once those costs to the consumer reach the equivalent of approximately 12¢/kWh for all miles driven, almost all gains to BEV sales and GHG emissions reductions from infrastructure construction are lost.

Effectiveness of incentives on electric vehicle adoption in Norway

Battery Electric vehicles (BEVs) shift pollution off the road and to potentially less damaging and more varied sources than petroleum. Depending on the source of electricity, a transition to electrified personal transportation can dramatically reduce greenhouse gas emissions and air pollutants. However current EVs tend to be more expensive and have shorter range, which can hinder public adoption. Government incentives can be used to alleviate these factors and encourage adoption. Norway has a long history incentivizing BEV adoption including measures such as exemption from roadway tolls, access to charging infrastructure, point of sale tax incentives, and usage of public bus use limited lanes. This paper analyzed the sales of electric vehicles on a regional and municipal basis in Norway and then cross analyzed these with the corresponding local demographic data and incentive measures to attempt to ascertain which factors lead to higher BEV adoption. It was concluded that access to BEV charging infrastructure, being adjacent to major cities, and regional incomes had the greatest predictive power for the growth of BEV sales. It was also concluded that short-range vehicles showed somewhat more income and unemployment sensitivity than long-range vehicles. Toll exemptions and the right to use bus designated lanes do not seem to have statistically significant predictive power for BEV sales in our linear municipal-level models, but this could be due to neighboring major cities containing those incentive features.

Capturing the Usage of the German Car Fleet for a One Year Period to Evaluate the Suitability of Battery Electric Vehicles – A Model based Approach

The low driving range of battery electric vehicles (BEV) is often considered as relevant reason for the low BEV sales. In order to verify this assumption, the usage of conventional cars in Germany needs to be analyzed. These analyses may help to make more reliable and realistic statements to what extent German cars could be replaced by BEVs without restrictions for their users. Most travel surveys do only consider a single day or a short period of time in the analysis. Longer time periods should be taken into consideration when analyzing the travel data since the daily car usage is not identical every day. Since there are no representative and detailed car usage surveys over longer periods available a hybrid car usage model was developed to close that gap. This model is mainly based on three mobility surveys: the German Mobility Panel (MOP), the car mileage and fuel consumption survey, and the long distance travel survey INVERMO. We show that 13% of the modeled German private car fleet never exceeds 100km per day during a full year and could be replaced by BEVs without any usage restrictions for their car owners. Another 16% of the modeled private car fleet is driven more than 100km on 1-4 days during a full year and can be substituted with slight adjustments. These cars are often second cars of a household and used less intensively (6,600km/year resp. 7600km/year) than cars not suited for BEV substitution (14,800km/year). Households that could replace their cars tend to have a lower disposable income. The crux of the matter, however, is that substitution of conventional cars is often not feasible since the mobility budget of BEV suited households tends to be too low or does not make economic sense due to the low annual mileage.