Electric Vehicles Statistics

Written by Shishun Pan, Haoyi Zhou and Zhanlian Li

In IEEE Smart Grid’s January 2017 Bulletin, Xiaomei Wu and Loi Lei Lai discussed the current status of the development and future of electric vehicles [1], and proposed that charging electric vehicles (EV) with renewable energy minimizes greenhouse gas (GHG) emissions.

After six years since the publication of this article and increased interest in EV statistics, it is time to make an update. For example, in recent EV statistics reports [2], some findings are as follows:

  • 10.6 million EV sales were anticipated to take place in 2022, a 57% increase over 2021.
  • The V2G industry is expected to exceed $5 billion by 2024.
  • Globally, EV usage avoided more than 40 million tonnes of carbon dioxide equivalent to GHG emissions during 2021
  • In 2030, EVs will account for more than 30% of all vehicles sold globally.

To give further details, in this article, further information is provided for the benefit of the readers.

Battery electric vehicles (BEV) and Plug-in Hybrid Electric Vehicles (PHEV) would deploy Vehicle to Grid (V2G) technology to enable the grid to minimize negative consequences, such as voltage instability due to a high penetration of intermittent renewable energy connected to the grid [3].

Table 1 shows the global total number of electric vehicles from 2010 to 2030 [4]. It demonstrates that there is a huge increase in the numbers.

table 1 global total number of electrical vehicles

 Figure 1: Global total number of Electric Vehicles from 2010 to 2030 [4].


Electric vehicles include Electric Buses, EV-Cars, EV-Vans, EV-Trucks, etc. Electric Buses are used for urban public transportation [5], EV-Cars are used for private driving or taxi public services, EV-Vans and EV-Trucks are used for freight [5,6]. Electric vehicles contain BEV and PHEV forms [7].

Figure 1 to Figure 4 illustrate the total number of electric buses and vehicles in battery and plug-in hybrids from 2010 to 2030 [4].


fig 1 trend of battery electric bus stock

 Figure 1: Trend of battery electric bus stock from 2010 to 2030 [4].


Fig 2 trend of plug in hybrids electric bus stock

 Figure 2: Trend of plug-in hybrids electric bus stock from 2010 to 2030 [4].


Figure 1 and Figure 2 show the development trend of electric bus stock, with Europe having the lowest number of electric buses in 2010, only 88, rising to 9,200 in 2021 and expected to rise to 0.27 million by 2030. China had the largest number of electric buses in 2010 with 1,900 vehicles, which increased to 0.65 million in 2021, accounting for 97% of global electric bus stock, the largest increase of any country or region, and is expected to reach 2.06 million by 2030. Based on the fact that the rest of the world exhibiting an upward trend from 2010 to 2021, these figures show that the world stock of electric buses rose from 2,100 to 0.67 million and is expected to rise to 2.95 million by 2030, an increase of 338%.

fig 3 trend of battery electric vehicles stock

 Figure 3: Trend of battery electric vehicles stock from 2010 to 2030 [4].


fig 4 trend of plug in hybrids electric vehicles stock

 Figure 4: Trend of plug-in hybrids electric vehicles stock from 2010 to 2030 [4].


fig 5 trend of electic vehicles stock

 Figure 5: Trend of electric vehicles stock from 2010 to 2030 [4].



It is clearly shown that the number of electric buses is constantly increasing. Under the present smart cities development, this could lead much better chances of facilitating smart transportation and enhancing electric public transportation to contribute to the reduction of traffic-related fatalities. The government is likely to set up various policies to encourage residents to use different modes of public transportation.

Due to the increasing popularity of electric vehicles, global ownership of EVs is booming. Consequently, it is essential to develop and promote smart energy to fully make use of renewables and energy storages.




  1. X. Wu and L. L. Lai, ‘Current status of the development and future of electric vehicles,’ IEEE Smart Grid Bulletin, January 2017. https://smartgrid.ieee.org/bulletins/january-2017/current-status-of-the-development-and-future-of-electric-vehicles [Assessed on 9 February 2023]
  2. https://vehiclefreak.com/ev-statistics/ [Assessed on 9 February 2023]
  3. X. Xu et al. “A multi-agent reinforcement learning-based data-driven method for home energy management,” IEEE Transactions on Smart Grid, Volume: 11, Issue: 4, pp. 3201- 3211, July 2020.
  4. IEA (2022), Global EV Data Explorer, IEA, Paris https://www.iea.org/data-and-statistics/data-tools/global-ev-data-explorer
  5. Z. Li, A. Khajepour, J. Song, “A comprehensive review of the key technologies for pure electric vehicles,” Energy, 2019, 182, 824-839.
  6. D. S. Utomo, A. Gripton, P. Greening, “Analysing charging strategies for electric LGV in grocery delivery operation using agent-based modelling: An initial case study in the United Kingdom,” Transportation Research Part E: Logistics and Transportation Review, 2021, 148, 102269.
  7. L. Q. Luu, E. R. Sanseverino, M. Cellura et al., “Comparative life cycle impact assessment of electric and conventional bus in Vietnam”. Sustainable Energy Technologies and Assessments, 2022, 54: 102873.



This article was edited by Melkior Ornik.

To view all articles in this issue, please go to February 2023 eNewsletter. For a downloadable copy, please visit the IEEE Smart Cities Resource Center.

shihun pan
Shishun Pan is currently pursuing a bachelor's degree in electrical engineering and automation at the School of International Education in Guangdong University of Technology, Guangzhou China. His research interests are in electric vehicles, smart grid, and electricity markets.
haoyi zhou
Haoyi Zhou is currently pursuing a bachelor's degree in electrical engineering and automation at the School of International Education in Guangdong University of Technology, Guangzhou China. Her research interests are in microgrid energy management systems, power market, and renewable energy.
zhanlian li
Zhanlian Li received his master’s degree in electrical engineering from Guangdong University of Technology, Guangzhou, China, in 2021, He is currently working toward a PhD degree in control science and engineering at the same university. His research interests are in smart grid, clean energy and computational intelligence applications. He is an IEEE Student Member.

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