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Electric Vehicles and Infrastructure

Electric Vehicles and Infrastructure is a research topic within Electrical and Electronic Engineering. Science Explorer counts 37k research works in it since 1953. 21.1% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the integration of electric vehicles into power systems, including topics such as vehicle-to-grid technology, charging infrastructure, renewable energy integration, grid impact, battery technology, consumer adoption, smart grid interactions, life cycle assessment, and sustainability.

  • Electric Vehicles
  • Vehicle-to-Grid
  • Charging Infrastructure
  • Renewable Energy Integration
  • Grid Impact
  • Battery Technology
  • Consumer Adoption
  • Smart Grid
  • Life Cycle Assessment
  • Sustainability
Research works
37k
fractional, since 1953
In the world top 10%
7.8k
per year above
Top-10% rate
21.1%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+106%
the tick is no change

Which countries lead Electric Vehicles and Infrastructure research?

By volume, China and India publish the most (4.3k and 2.2k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 4.3k works
  2. 2 India 2.2k works
  3. 3 United States 1.4k works
  4. 4 Germany 626 works
  5. 5 United Kingdom 522 works
  6. 6 Italy 483 works
  7. 7 Indonesia 328 works
  8. 8 Canada 295 works
  9. 9 Australia 280 works
  10. 10 South Korea 276 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 40.4%India: 20.5%United States: 12.7%Germany: 5.9%6 others listed: 20.5%40%largest
China4,311 · 40.4%India2,184 · 20.5%United States1,354 · 12.7%Germany626 · 5.9%6 others listed2,184 · 20.5%

Shares of the rows listed above, not of the whole node.

Which institutions lead Electric Vehicles and Infrastructure research?

By volume in 2022–2025, North China Electric Power University publishes the most Electric Vehicles and Infrastructure research, followed by Tsinghua University and Beijing Institute of Technology.

Who are the leading researchers in Electric Vehicles and Infrastructure?

The most-cited researchers publishing on Electric Vehicles and Infrastructure include Frede Blaabjerg, H. Vincent Poor and İbrahim Dinçer.

  1. 1 Frede Blaabjerg Denmark 12k citations
  2. 2 H. Vincent Poor United States 9.5k citations
  3. 3 İbrahim Dinçer Canada 5.9k citations
  4. 4 Josep M. Guerrero Denmark 5.6k citations
  5. 5 Xuemin Shen Canada 5.1k citations
  6. 6 Dusit Niyato Singapore 4.5k citations
  7. 7 Remus Teodorescu Denmark 4.2k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Electric Vehicles and Infrastructure research done?

The largest centres of Electric Vehicles and Infrastructure research in 2022–2025 are Beijing (China), Shanghai (China), Nanjing (China) and Guangzhou (China). Among places with at least 20 works in it, it is an unusually large share of all research in Oshawa and Yangpu.

Largest cities, 2022–2025

  1. 1 Beijing China 883 works
  2. 2 Shanghai China 395 works
  3. 3 Nanjing China 291 works
  4. 4 Guangzhou China 194 works
  5. 5 Wuhan China 188 works
  6. 6 Chennai India 177 works
  7. 7 Tianjin China 176 works
  8. 8 Xi'an China 175 works
  9. 9 Chongqing China 147 works
  10. 10 New Delhi India 135 works

Where it is the local speciality

  1. OshawaCA · 20.1 works12×
  2. YangpuCN · 30.6 works11×
← less than its size predictsmore →

Location quotient: how much more of its research is in Electric Vehicles and Infrastructure than the world average.

See Electric Vehicles and Infrastructure on the map

Where is the best place to study Electric Vehicles and Infrastructure?

Among universities, judged by research, North China Electric Power University, Chalmers University of Technology and Beijing Institute of Technology score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 25.8%fractional works in this node (log) →share in the world top 10% →North China Electric Power University: 142, 19.5%Chalmers University of Technology: 41, 28.8%Beijing Institute of Technology: 111, 33.6%Politecnico di Milano: 76, 20.7%Hong Kong Polytechnic University: 53, 34.3%Chang'an University: 46, 20.0%Aalborg University: 45, 38.9%Universiti Tenaga Nasional: 11, 25.6%Politecnico di Torino: 48, 19.0%Ontario Tech University: 20, 17.6%Beijing Institute of…Chalmers University …Politecnico di MilanoNorth China Electric…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 North China Electric Power UniversityChina 64.219.5%13.9×142 +73.9%
2 Chalmers University of TechnologySweden 63.228.8%10.6×41 +33.8%
3 Beijing Institute of TechnologyChina 62.233.6%6.1×111 +92.8%
4 Politecnico di MilanoItaly 60.220.7%7.1×76 +152.5%
5 Hong Kong Polytechnic UniversityHong Kong 59.934.3%4.0×53 +111.3%
6 Chang'an UniversityChina 59.820.0%8.0×46 +265.7%
7 Aalborg UniversityDenmark 59.838.9%5.7×45 +67.4%
8 Universiti Tenaga NasionalMalaysia 59.825.6%9.0×11 +264.0%
9 Politecnico di TorinoItaly 58.819.0%7.0×48 +291.2%
10 Ontario Tech UniversityCanada 58.417.6%13.1×20 +181.0%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Electric Vehicles and Infrastructure research growing?

Output in 2018–2022 was 106% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Electric Vehicles and Infrastructure.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.