Exploring Electric Vehicle Patent Trends through Technology Life Cycle and Social Network Analysis
Abstract
:1. Introduction
- At what stage of the technology life cycle are EV technologies globally and in South Korea?
- What is South Korea’s position in the global competition for EV technology?
- What are the prevailing technological trends and future directions in the EV sector?
- Can these future research directions address the sustainability challenges faced by EVs?
2. Materials and Methods
2.1. Data Collection and Organization
- Step 1: Initial search scope: The initial search yielded 899,426 patent documents based on the specified time frame and keywords.
- Step 2: Grouping by simple families [68]: To eliminate duplicate entries across different jurisdictions, patents were grouped into simple families, reducing the dataset to 659,975 unique patent families.
- Step 3: Document type filtering: The dataset was further refined by filtering for patent applications and granted patents, resulting in 450,054 documents.
- Step 4: Legal status filtering: Patents were then filtered based on their legal status (active, inactive, expired), reducing the dataset to 210,056 documents.
- Step 5: Manual review: A manual review was conducted to ensure the relevance of the remaining patents, culminating in a final dataset of 187,700 documents. IPC co-occurrence data were processed into a co-linearity matrix and saved as a CSV file for visualization using Gephi 0.10.1. Figure 1 illustrates the research framework of this study.
2.2. Research Methods
2.2.1. S-Curve Model
2.2.2. IP Strategies According to the Technology Life Cycle
2.2.3. IPC Code Co-Occurrence
2.2.4. Bubble Charts for Time Series and Core Applicant Layouts
3. Results
3.1. Electric Vehicles Technology Development Trend
3.1.1. Global Technology Application Trends
3.1.2. Technology Application Trends in Major Automobile-Producing Countries
3.2. Technology Life Cycle Analysis
Technology Life Cycle Using the Logistic Curve
3.3. Social Network Analysis
3.3.1. Social Network Analysis Using IPC Code Co-Occurrence
3.3.2. Trends in Core Technology Applications
3.3.3. Technology Layouts of Core Applicants
4. Discussion
4.1. Policy Initiatives Driving EV Adoption
4.2. Technological Life Cycle and Market Dynamics in the EV Industry
4.3. A Comparison with Previous Research
4.4. EV Charging Technology and Infrastructure
4.5. EV Charging Technology and Infrastructure and Sustainability Challenges
4.6. Battery Monitoring and Management and Sustainability Challenges
4.7. EV Intelligence and ICT Technologies
4.8. Environmental Challenges and Research Limitations in EV Adoption
5. Conclusions
- Fast-charging infrastructure technology: More efficient and quicker charging technologies and optimized layouts of charging facilities can effectively alleviate range anxiety. For the challenge of overloaded power grids, smart grid technology and V2G systems are also worth focusing on. Additionally, integrating renewable energy into the grid and using V2G technology to optimize the use of renewable energy should be prioritized.
- Battery monitoring and management technology development: The development of battery technology has shifted from a traditionally increasing range to a focus on battery monitoring and management. Moreover, battery monitoring and management technology can optimize battery lifespan, better addressing the challenge of battery capacity degradation faced by EVs.
- Application of communication technology to enhance vehicle intelligence: Further development and application of ICT can enhance the intelligence level of EVs and optimize the user experience. At the same time, optimizing battery management systems and improving the integration of EVs with smart grids (SG) will help us better address the sustainability challenges faced by EVs.
- The analysis is based on patent data, which may not fully capture all aspects of technological innovation, such as academic papers and news reports.
- The study focuses on global and South Korean markets, which may not fully represent technological trends in other significant regions.
- The use of IPC co-occurrence and betweenness centrality to identify core technologies in the current phase of EV development may be somewhat narrow.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Emadi, A. Handbook of Automotive Power Electronics and Motor Drives, 1st ed.; CRC Press: Boca Raton, FL, USA, 2005; pp. 55–96. [Google Scholar]
- World Energy Outlook 2015. Available online: https://www.iea.org/reports/world-energy-outlook-2015 (accessed on 29 April 2024).
- Inflation Reduction Act Guidebook. Available online: https://www.whitehouse.gov/cleanenergy/inflation-reduction-act-guidebook/ (accessed on 29 April 2024).
- Deng, R.; Shen, N.; Zhao, Y. Diffusion model to analyse the performance of electric vehicle policies: An evolutionary game simulation. Transp. Res. Part D Transp. Environ. 2024, 127, 104037. [Google Scholar] [CrossRef]
- Zero-Emission Vehicle Program. Available online: https://ww2.arb.ca.gov/our-work/programs/zero-emission-vehicle-program/about (accessed on 29 April 2024).
- CO2 Emissions Performance of New Passenger Cars in Europe. Available online: https://www.eea.europa.eu/en/analysis/indicators/co2-performance-of-new-passenger (accessed on 29 April 2024).
- Kim, Y.G.; Lim, H.; Lee, J. Decarbonizing road transport in Korea: Role of electric vehicle transition policies. Transp. Res. Part D Transp. Environ. 2024, 128, 104084. [Google Scholar] [CrossRef]
- Singh, A.R.; Vishnuram, P.; Alagarsamy, S.; Bajaj, M.; Blazek, V.; Damaj, I.; Rathore, R.S.; Al-Wesabi, F.N.; Othman, K.M. Electric vehicle charging technologies, infrastructure expansion, grid integration strategies, and their role in promoting sustainable e-mobility. Alex. Eng. J. 2024, 105, 300–330. [Google Scholar] [CrossRef]
- Rehman, F.U.; Islam, M.M.; Miao, Q. Environmental sustainability via green transportation: A case of the top 10 energy transition nations. Transp. Policy 2023, 137, 32–44. [Google Scholar] [CrossRef]
- Pamidimukkala, A.; Kermanshachi, S.; Rosenberger, J.M.; Hladik, G. Evaluation of barriers to electric vehicle adoption: A study of technological, environmental, financial, and infrastructure factors. Transp. Res. Interdiscip. Perspect. 2023, 22, 100962. [Google Scholar] [CrossRef]
- Krishnan, V.V.; Koshy, B.I. Evaluating the factors influencing purchase intention of electric vehicles in households owning conventional vehicles. Case Stud. Transp. Policy 2021, 9, 1122–1129. [Google Scholar] [CrossRef]
- Pamidimukkala, A.; Kermanshachi, S.; Rosenberger, J.M.; Hladik, G. Barriers and motivators to the adoption of electric vehicles: A global review. Green Energy Intell. Transp. 2024, 3, 100153. [Google Scholar] [CrossRef]
- Alanazi, F. Electric vehicles: Benefits, challenges, and potential solutions for widespread adaptation. Appl. Sci. 2023, 13, 6016. [Google Scholar] [CrossRef]
- Krishna, G. Understanding and identifying barriers to electric vehicle adoption through thematic analysis. Transp. Res. Interdiscip. Perspect. 2021, 10, 100364. [Google Scholar] [CrossRef]
- Mohammed, A.; Saif, O.; Abo-Adma, M.; Fahmy, A.; Elazab, R. Strategies and sustainability in fast charging station deployment for electric vehicles. Sci. Rep. 2024, 14, 283. [Google Scholar] [CrossRef]
- Ruoso, A.C.; Ribeiro, J.L.D. An assessment of barriers and solutions for the deployment of electric vehicles in the Brazilian market. Transp. Policy 2022, 127, 218–229. [Google Scholar] [CrossRef]
- Ramesan, S.; Kumar, P.; Garg, S.K. Analyzing the enablers to overcome the challenges in the adoption of electric vehicles in Delhi NCR. Case Stud. Transp. Policy 2022, 10, 1640–1650. [Google Scholar] [CrossRef]
- Li, J.; Jiao, J.; Tang, Y. Analysis of the Impact of Policies Intervention on Electric Vehicles Adoption Considering Information Transmission—Based on Consumer Network Model. Energy Policy 2020, 144, 111560. [Google Scholar] [CrossRef]
- Hardman, S.; Shiu, E.; Steinberger-Wilckens, R. Comparing High-End and Low-End Early Adopters of Battery Electric Vehicles. Transp. Res. Part A Policy Pract. 2016, 88, 40–57. [Google Scholar] [CrossRef]
- Philipsen, R.; Brell, T.; Brost, W.; Eickels, T.; Ziefle, M. Running on Empty—Users’ Charging Behavior of Electric Vehicles versus Traditional Refueling. Transp. Res. Part F Traffic Psychol. Behav. 2018, 59, 475–492. [Google Scholar] [CrossRef]
- Patel, R.K.; Etminani-Ghasrodashti, R.; Kermanshachi, S.; Rosenberger, J.M.; Weinreich, D. Exploring Preferences Towards Integrating Autonomous Vehicles with Current Microtransit Services: A Disability Focus Group Study. In International Conference on Transportation and Development 2021, Proceedings of the International Conference on Transportation and Development 2021: Transportation Operations, Technologies, and Safety, Virtual, 8–10 June 2021; ASCE Library: Reston, VA, USA; pp. 355–366.
- Gnanavendan, S.; Selvaraj, S.K.; Dev, S.J.; Mahato, K.K.; Swathish, R.S.; Sundaramali, G.; Azab, M. Challenges, Solutions and Future Trends in EV-Technology: A Review. IEEE Access 2024, 12, 17242–17260. [Google Scholar] [CrossRef]
- Liu, D.; Song, Y.; Li, L.; Liao, H.; Peng, Y. On-Line Life Cycle Health Assessment for Lithium-Ion Battery in Electric Vehicles. J. Clean. Prod. 2018, 199, 1050–1065. [Google Scholar] [CrossRef]
- The State of EVs: 2023 Smart Mobility Survey. Available online: https://www.verramobility.com/ev-2023-smart-mobility-survey/ (accessed on 29 April 2024).
- Strezoski, L.; Stefani, I. Enabling Mass Integration of Electric Vehicles through Distributed Energy Resource Management Systems. Int. J. Electr. Power Energy Syst. 2024, 157, 109798. [Google Scholar] [CrossRef]
- Khalid, M.R.; Alam, M.S.; Sarwar, A.; Asghar, M.J. A Comprehensive Review on Electric Vehicles Charging Infrastructures and Their Impacts on Power Quality of the Utility Grid. ETransportation 2019, 1, 100006. [Google Scholar] [CrossRef]
- Thiel, C.; Perujo, A.; Mercier, A. Cost and CO2 Aspects of Future Vehicle Options in Europe under New Energy Policy Scenarios. Energy Policy 2010, 38, 7142–7151. [Google Scholar] [CrossRef]
- Qiao, Q.; Zhao, F.; Liu, Z.; He, X.; Hao, H. Life Cycle Greenhouse Gas Emissions of Electric Vehicles in China: Combining the Vehicle Cycle and Fuel Cycle. Energy 2019, 177, 222–233. [Google Scholar] [CrossRef]
- Lombardi, L.; Tribioli, L.; Cozzolino, R.; Bella, G. Comparative Environmental Assessment of Conventional, Electric, Hybrid, and Fuel Cell Powertrains Based on LCA. Int. J. Life Cycle Assess. 2017, 22, 1989–2006. [Google Scholar] [CrossRef]
- Li, F.; Ou, R.; Xiao, X.; Zhou, K.; Xie, W.; Ma, D.; Song, Z. Regional Comparison of Electric Vehicle Adoption and Emission Reduction Effects in China. Resour. Conserv. Recycl. 2019, 149, 714–726. [Google Scholar] [CrossRef]
- Niri, A.J.; Poelzer, G.A.; Zhang, S.E.; Rosenkranz, J.; Pettersson, M.; Ghorbani, Y. Sustainability Challenges Throughout the Electric Vehicle Battery Value Chain. Renew. Sustain. Energy Rev. 2024, 191, 191–114176. [Google Scholar]
- Rupp, M.; Handschuh, N.; Rieke, C.; Kuperjans, I. Contribution of Country-Specific Electricity Mix and Charging Time to Environmental Impact of Battery Electric Vehicles: A Case Study of Electric Buses in Germany. Appl. Energy 2019, 237, 618–634. [Google Scholar] [CrossRef]
- Onat, N.C.; Kucukvar, M.; Afshar, S. Eco-Efficiency of Electric Vehicles in the United States: A Life Cycle Assessment Based Principal Component Analysis. J. Clean. Prod. 2019, 212, 515–526. [Google Scholar] [CrossRef]
- Yu, A.; Wei, Y.; Chen, W.; Peng, N.; Peng, L. Life Cycle Environmental Impacts and Carbon Emissions: A Case Study of Electric and Gasoline Vehicles in China. Transp. Res. Part D Transp. Environ. 2018, 65, 409–420. [Google Scholar] [CrossRef]
- Poullikkas, A. Sustainable Options for Electric Vehicle Technologies. Renew. Sustain. Energy Rev. 2015, 41, 1277–1287. [Google Scholar] [CrossRef]
- Gan, Y.; Lu, Z.; Wu, Q.; He, X.; Dai, Q.; Kelly, J.C.; Ankathi, S.K.; Wang, M. Cradle-to-Grave Mercury Emissions of Light-Duty Gasoline and Electric Vehicles in China. Resour. Conserv. Recycl. 2023, 190, 106736. [Google Scholar] [CrossRef]
- Yu, X.; Li, W.; Gupta, V.; Gao, H.; Tran, D.; Sarwar, S.; Chen, Z. Current Challenges in Efficient Lithium-Ion Batteries’ Recycling: A Perspective. Glob. Chall. 2022, 6, 2200099. [Google Scholar] [CrossRef]
- Arat, H.T. Recycling and Reusing Batteries: A Significant Way for Effective Sustainability of FCEVs and EVs. Int. J. Hydrogen Energy 2023, 48, 23272–23278. [Google Scholar] [CrossRef]
- Obrador Rey, S.; Canals Casals, L.; Gevorkov, L.; Cremades Oliver, L.; Trilla, L. Critical Review on the Sustainability of Electric Vehicles: Addressing Challenges without Interfering in Market Trends. Electronics 2024, 13, 860. [Google Scholar] [CrossRef]
- Omri, A. Technological Innovation and Sustainable Development: Does the Stage of Development Matter? Environ. Impact Assess. Rev. 2020, 83, 106398. [Google Scholar] [CrossRef]
- Chatterjee, P.; Greenland, S.; Low, D.; Watson, C.; Nguyen, N. Barriers to Sustainable Innovation Adoption: A Qualitative Investigation of Metal Additive Printing from Supply and Demand Perspectives. Clean Logist. Suppl. Chain 2023, 9, 100128. [Google Scholar] [CrossRef]
- Huang, Y. Technology Innovation and Sustainability: Challenges and Research Needs. Clean Technol. Environ. Policy 2021, 23, 1663–1664. [Google Scholar] [CrossRef] [PubMed]
- Alraja, M.N.; Imran, R.; Khashab, B.M.; Shah, M. Technological Innovation, Sustainable Green Practices, and SMEs’ Sustainable Performance in Times of Crisis (COVID-19 Pandemic). Inform. Syst. Front. 2022, 24, 1081–1105. [Google Scholar] [CrossRef]
- Anadon, L.D.; Chan, G.; Harley, A.G.; Matus, K.; Moon, S.; Murthy, S.L.; Clark, W.C. Making Technological Innovation Work for Sustainable Development. Proc. Natl. Acad. Sci. USA 2016, 113, 9682–9690. [Google Scholar] [CrossRef]
- Pilkington, A.; Dyerson, R. Innovation in disruptive regulatory environments: A patent study of electric vehicle technology development. Eur. J. Innov. Manag. 2006, 9, 79–91. [Google Scholar] [CrossRef]
- Liu, J.S.; Kuan, C.H.; Cha, S.C.; Chuang, W.L.; Gau, G.J.; Jeng, J.Y. Photovoltaic technology development: A perspective from patent growth analysis. Sol. Energy Mater. Sol. Cells 2011, 95, 3130–3136. [Google Scholar] [CrossRef]
- Adamuthe, A.C.; Thampi, G.T. Technology forecasting: A case study of computational technologies. Technol. Forecast. Soc. Chang. 2019, 143, 181–189. [Google Scholar] [CrossRef]
- Li, M.; Fang, J.; Wu, Y. Based on the patent index method and S curve method prediction analysis of pure electric vehicle life cycle. J. Phys. Conf. Ser. 2020, 1533, 22105. [Google Scholar] [CrossRef]
- Madavar, M.D.; Nezhad, M.H.G.; Aslani, A.; Naaranoja, M. Analysis of generations of wind power technologies based on technology life cycle approach. Distrib. Gener. Altern. Energy J. 2017, 32, 52–79. [Google Scholar]
- Gao, L.; Porter, A.L.; Wang, J.; Fang, S.; Zhang, X.; Ma, T.; Wang, W.; Huang, L. Technology life cycle analysis method based on patent documents. Technol. Forecast. Soc. Chang. 2013, 80, 398–407. [Google Scholar] [CrossRef]
- Garg, M.; Koundal, D. Emotional AI and Human-AI Interactions in Social Networking; Elsevier: Amsterdam, The Netherlands, 2023; pp. 213–235. [Google Scholar]
- Hanneman, R.; Mark, R. Introduction to Social Network Methods; University of California, Riverside: Riverside, CA, USA, 2005. [Google Scholar]
- Lee, H.; Kim, C.; Cho, H.; Park, Y. An ANP-based technology network for identification of core technologies: A case of telecommunication technologies. Expert Syst. Appl. 2009, 36, 894–908. [Google Scholar] [CrossRef]
- Constant, E.W., II. Why evolution is a theory about stability: Constraint, causation, and ecology in technological change. Res. Policy 2002, 31, 1241–1256. [Google Scholar] [CrossRef]
- Devezas, T.C. Evolutionary theory of technological change: State-of-the-art and new approaches. Technol. Forecast. Soc. Chang. 2005, 72, 1137–1152. [Google Scholar] [CrossRef]
- Lee, W.S.; Han, E.J.; Sohn, S.Y. Predicting the pattern of technology convergence using big-data technology on large-scale triadic patents. Technol. Forecast. Soc. Chang. 2015, 100, 317–329. [Google Scholar] [CrossRef]
- Chang, S.H.; Fan, C.Y. Using patent technology networks to observe neurocomputing technology hotspots and development trends. Sustainability 2020, 12, 7696. [Google Scholar] [CrossRef]
- Almeida, P.; Phene, A.; Grant, R. Innovation and knowledge management: Scanning, sourcing, and integration. In Handbook of Organizational Learning and Knowledge Management; Blackwell Publishing: Oxford, UK, 2003; pp. 356–371. [Google Scholar]
- Chen, Y.H.; Chen, C.Y.; Lee, S.C. Technology forecasting and patent strategy of hydrogen energy and fuel cell technologies. Int. J. Hydrogen Energy 2011, 36, 6957–6969. [Google Scholar] [CrossRef]
- Yuan, X.; Cai, Y. Forecasting the development trend of low emission vehicle technologies: Based on patent data. Technol. Forecast. Soc. Chang. 2021, 166, 120651. [Google Scholar] [CrossRef]
- Fang, J.; Shao, F.; Li, M. Predictive analysis of new energy vehicle life cycle based on logistic model. J. Phys. Conf. Ser. 2020, 1533, 042059. [Google Scholar] [CrossRef]
- Sinigaglia, T.; Martins, M.E.S.; Siluk, J.C.M. Technological forecasting for fuel cell electric vehicle: A comparison with electric vehicles and internal combustion engine vehicles. World Pat. Inf. 2022, 71, 102152. [Google Scholar] [CrossRef]
- Wu, C.C.; Leu, H.J. Examining the trends of technological development in hydrogen energy using patent co-word map analysis. Int. J. Hydrogen Energy 2014, 39, 19262–19269. [Google Scholar] [CrossRef]
- Koo, M.; Hwang, H.; Jeon, J. Analysis of patent trends of electric vehicle in Korea using network analysis. J. Korea Acad. Ind. Coop. Soc. 2023, 24, 13–23. [Google Scholar]
- Ma, S.C.; Xu, J.H.; Fan, Y. Characteristics and Key Trends of Global Electric Vehicle Technology Development: A Multi-Method Patent Analysis. J. Clean. Prod. 2022, 338, 130502. [Google Scholar] [CrossRef]
- Hsu, C.W.; Lin, C.Y. Using Social Network Analysis to Examine the Technological Evolution of Fermentative Hydrogen Production from Biomass. Int. J. Hydrogen Energy 2016, 41, 21573–21582. [Google Scholar] [CrossRef]
- The Lens. Available online: https://en.wikipedia.org/wiki/The_Lens (accessed on 29 April 2024).
- Patent Families. Available online: https://www.epo.org/en/searching-for-patents/helpful-resources/first-time-here/patent-families (accessed on 29 April 2024).
- Technology Life Cycle. Available online: https://en.wikipedia.org/wiki/Technology_life_cycle (accessed on 29 April 2024).
- Butler, J.E. Theories of technological innovation as useful tools for corporate strategy. Strat. Manag. J. 1988, 9, 15–29. [Google Scholar] [CrossRef]
- He, J.; Wang, Z.; King, M.; Hang, W.; Zhao, C. Research on prediction methods for motor vehicle driver training demand based on an S-curve. Transp. Res. Part F Traffic Psychol. Behav. 2018, 58, 831–842. [Google Scholar] [CrossRef]
- Bengisu, M.; Nekhili, R. Forecasting emerging technologies with the aid of science and technology databases. Technol. Forecast. Soc. Chang. 2006, 73, 835–844. [Google Scholar] [CrossRef]
- Basberg, B.L. Patents and the measurement of technological change: A survey of the literature. Res. Policy 1987, 16, 131–141. [Google Scholar] [CrossRef]
- Meyer, P.S.; Yung, J.W.; Ausubel, J.H. A primer on logistic growth and substitution: The mathematics of the Loglet Lab software. Technol. Forecast. Soc. Chang. 1999, 61, 247–271. [Google Scholar] [CrossRef]
- Efron, B. Bootstrap Methods: Another Look at the Jackknife; Kotz, S., Johnson, N.L., Eds.; Springer Series in Statistics; Springer: New York, NY, USA, 1992; pp. 569–593. [Google Scholar]
- Yang, D. Study on Intellectual Property Strategy: Based on Strategic Situation of Companies Considering TLC. Master’s Thesis, Seoul National University, Seoul, Republic of Korea, 2014. [Google Scholar]
- Cho, T.S.; Shih, H.Y. Patent citation network analysis of core and emerging technologies in Taiwan: 1997–2008. Scientometrics 2011, 89, 795–811. [Google Scholar] [CrossRef]
- Liu, J.H.; Meng, Z.; Jiang, Z.H. Analysis on core technologies and cutting-edge technologies of new energy based on input-output method. Procedia Eng. 2017, 174, 1036–1045. [Google Scholar] [CrossRef]
- Wang, X.; Duan, Y. Identifying core technology structure of electric vehicle industry through patent co-citation information. Energy Procedia 2011, 5, 2581–2585. [Google Scholar] [CrossRef]
- Maleki, A.; Rosiello, A. Does knowledge base complexity affect spatial patterns of innovation? An empirical analysis in the upstream petroleum industry. Technol. Forecast. Soc. Chang. 2019, 143, 273–288. [Google Scholar] [CrossRef]
- Lizin, S.; Leroy, J.; Delvenne, C.; Dijk, M.; De Schepper, E.; Van Passel, S. A patent landscape analysis for organic photovoltaic solar cells: Identifying the technology’s development phase. Renew. Energy 2013, 57, 5–11. [Google Scholar] [CrossRef]
- Archibugi, D.; Planta, M. Measuring technological change through patents and innovation surveys. Technovation 1996, 16, 451–519. [Google Scholar] [CrossRef]
- Curran, C.-S.; Leker, J. Patent indicators for monitoring convergence—Examples from NFF and ICT. Technol. Forecast. Soc. Chang. 2011, 78, 256–273. [Google Scholar] [CrossRef]
- Geum, Y.; Kim, C.; Lee, S.; Kim, M.S. Technological convergence of IT and BT: Evidence from patent analysis. ETRI J. 2012, 34, 439–449. [Google Scholar] [CrossRef]
- Caviggioli, F. Technology fusion: Identification and analysis of the drivers of technology convergence using patent data. Technovation 2016, 55–56, 22–32. [Google Scholar] [CrossRef]
- Curran, C.-S.; Bröring, S.; Leker, J. Anticipating converging industries using publicly available data. Technol. Forecast. Soc. Chang. 2010, 77, 385–395. [Google Scholar] [CrossRef]
- Freeman, L.C. A set of measures of centrality based on betweenness. Sociometry 1977, 40, 35–41. [Google Scholar] [CrossRef]
- Chang, S.H. International technology market hotspots and development trends from the perspective of inventor mobility. J. Knowl. Econ. 2024, 15, 2361–2382. [Google Scholar] [CrossRef]
- Gilsing, V.; Nooteboom, B.; Vanhaverbeke, W.; Duysters, G.; Van Den Oord, A. Network embeddedness and the exploration of novel technologies: Technological distance, betweenness centrality and density. Res. Policy 2008, 37, 1717–1731. [Google Scholar] [CrossRef]
- Park, J.; Lee, H.; Park, Y. Disembodied knowledge flows among industrial clusters: A patent analysis of the Korean manufacturing sector. Technol. Soc. 2009, 31, 73–84. [Google Scholar] [CrossRef]
- Yoon, J.; Choi, S.; Kim, K. Invention property-function network analysis of patents: A case of silicon-based thin film solar cells. Scientometrics 2011, 86, 687–703. [Google Scholar] [CrossRef]
- Wasserman, S.; Faust, K. Social Network Analysis: Methods and Applications; Cambridge University Press: New York, NY, USA, 1994; pp. 177–192. [Google Scholar]
- Zhang, J.; Luo, Y. Degree centrality, betweenness centrality, and closeness centrality in social network. In Proceedings of the 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017), Bangkok, Thailand, 26 March 2017. [Google Scholar]
- Breschi, S.; Lissoni, F.; Malerba, F. Knowledge-relatedness in firm technological diversification. Res. Policy 2003, 32, 69–87. [Google Scholar] [CrossRef]
- Zhou, H.; Dai, J.; Chen, X.; Hu, B.; Wei, H.; Cai, H.H. Understanding innovation of new energy industry: Observing development trend and evolution of hydrogen fuel cell based on patent mining. Int. J. Hydrogen Energy 2024, 52, 548–560. [Google Scholar] [CrossRef]
- International Patent Classification; IPC. Available online: https://www.wipo.int/classifications/ipc/en/ (accessed on 29 April 2024).
- Global, E.V. Outlook. 2024. Available online: https://www.iea.org/reports/global-ev-outlook-2024 (accessed on 29 April 2024).
- Six Major Automakers Agree to End Gas Car Sales Globally by 2040. Available online: https://www.caranddriver.com/news/a38213848/automakers-pledge-end-gas-sales-2040 (accessed on 29 April 2024).
- Gillingham, K.T.; van Benthem, A.A.; Weber, S.; Saafi, M.A.; He, X. Has consumer acceptance of electric vehicles been increasing? Evidence from microdata on every new vehicle sale in the United States. In AEA Papers and Proceedings; American Economic Association: Nashville, TN, USA, 2023; Volume 113, pp. 329–335. [Google Scholar]
- Kennedy, S. China’s Risky Drive into New-Energy Vehicles; Center for Strategic & International Studies (CSIS): Washinton; DC, USA, 2018. [Google Scholar]
- Funke, S.Á.; Sprei, F.; Gnann, T.; Plötz, P. How much charging infrastructure do electric vehicles need? A review of the evidence and international comparison. Transp. Res. Part D Transp. Environ. 2019, 77, 224–242. [Google Scholar] [CrossRef]
- Egbue, O.; Long, S. Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions. Energy Policy 2012, 48, 717–729. [Google Scholar] [CrossRef]
- Noel, L.; Zarazua de Rubens, G.Z.; Sovacool, B.K.; Kester, J. Fear and loathing of electric vehicles: The reactionary rhetoric of range anxiety. Energy Res. Soc. Sci. 2019, 48, 96–107. [Google Scholar] [CrossRef]
- Chevy Silverado EV Charges Faster than Most EV Trucks. Available online: https://www.nyechevrolet.com/chevy-silverado-ev-charges-faster-than-most-ev-trucks/ (accessed on 29 April 2024).
- Impact of Climate on the Range of Electric Vehicles. Available online: https://www.power.com/community/green-room/blog/impact-climate-range-electric-vehicles?langcode=en (accessed on 29 April 2024).
- Guo, D.; Liu, R.; Li, M.; Tan, X.; Ma, P.; Zhang, H. An Approach to Optimizing the Layout of Charging Stations Considering Differences in User Range Anxiety. Sustain. Energy Grids Netw. 2024, 38, 101292. [Google Scholar] [CrossRef]
- Tao, Y.; Huang, M.H.; Chen, Y.P.; Yang, L. Review of Optimized Layout of Electric Vehicle Charging Infrastructures. J. Cent. South Univ. 2021, 28, 3268–3278. [Google Scholar] [CrossRef]
- Li, W.; Yang, L.; Wen, Z.; Chen, J.; Wu, X. On the Optimization Strategy of EV Charging Station Localization and Charging Piles Density. Wirel. Commun. Mob. Comput. 2021, 2021, 6675841. [Google Scholar] [CrossRef]
- White, L.V.; Carrel, A.L.; Shi, W.; Sintov, N.D. Why Are Charging Stations Associated with Electric Vehicle Adoption? Untangling Effects in Three United States Metropolitan Areas. Energies 2022, 89, 102663. [Google Scholar] [CrossRef]
- Gas Stations Vs. EV Charging Stations: Why Density Matters. Available online: https://www.novacharge.net/blog/gas-stations-vs.-ev-charging-stations-density-matters (accessed on 29 April 2024).
- Hoogland, K.; Kurani, K.S.; Hardman, S.; Chakraborty, D. If You Build It, Will They Notice? Public Charging Density, Charging Infrastructure Awareness, and Consideration to Purchase an Electric Vehicle. Energies 2024, 23, 101007. [Google Scholar] [CrossRef]
- Mateen, S.; Amir, M.; Haque, A.; Bakhsh, F.I. Ultra-Fast Charging of Electric Vehicles: A Review of Power Electronics Converter, Grid Stability, and Optimal Battery Consideration in Multi-Energy Systems. Sustain. Energy Grids Netw. 2023, 35, 101112. [Google Scholar] [CrossRef]
- Franzese, P.; Di Pasquale, A.; Iannuzzi, D.; Pagano, M. Electric Ultra-Fast Charging Stations: A Real Case Study. In Proceedings of the 2021 AEIT International Annual Conference (AEIT), Milan, Italy, 4–8 October 2021; IEEE: New York, NY, USA; pp. 1–6. [Google Scholar]
- Amjad, M.; Farooq-i-Azam, M.; Ni, Q.; Dong, M.; Ansari, E.A. Wireless Charging Systems for Electric Vehicles. Renew. Sustain. Energy Rev. 2022, 167, 112730. [Google Scholar] [CrossRef]
- Manivannan, B.; Kathirvelu, P.; Balasubramanian, R. A Review on Wireless Charging Methods–The Prospects for Future Charging of EV. Renew. Energy Focus 2023, 46, 68–87. [Google Scholar] [CrossRef]
- Jain, S.; Ahmad, Z.; Alam, M.S.; Rafat, Y. Battery Swapping Technology. In Proceedings of the 2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE), Jaipur, India, 1–3 December 2020; IEEE: New York, NY, USA; pp. 1–4. [Google Scholar]
- Vallera, A.M.; Nunes, P.M.; Brito, M.C. Why We Need Battery Swapping Technology. Energy Policy 2021, 157, 112481. [Google Scholar] [CrossRef]
- Li, Y.; Zhu, F.; Li, L.; Ouyang, M. Electrifying Heavy-Duty Truck Through Battery Swapping. Joule 2024, 8, 1556–1561. [Google Scholar] [CrossRef]
- Smart Grids. Available online: https://www.iea.org/energy-system/electricity/smart-grids (accessed on 29 April 2024).
- Barman, P.; Dutta, L.; Bordoloi, S.; Kalita, A.; Buragohain, P.; Bharali, S.; Azzopardi, B. Renewable Energy Integration with Electric Vehicle Technology: A Review of the Existing Smart Charging Approaches. Renew. Sust. Energ. Rev. 2023, 183, 113518. [Google Scholar] [CrossRef]
- Brinkel, N.; van Wijk, T.; Buijze, A. Enhancing Smart Charging in Electric Vehicles by Addressing Paused and Delayed Charging Problems. Nat. Commun. 2024, 15, 5089. [Google Scholar] [CrossRef] [PubMed]
- Bibak, B.; Tekiner-Mogulkoc, H. Influences of Vehicle to Grid (V2G) on Power Grid: An Analysis by Considering Associated Stochastic Parameters Explicitly. Sustain. Energy Grids Netw. 2021, 26, 100429. [Google Scholar] [CrossRef]
- Mastoi, M.S.; Zhuang, S.; Munir, H.M.; Haris, M.; Hassan, M.; Alqarni, M.; Alamri, B. A Study of Charging-Dispatch Strategies and Vehicle-to-Grid Technologies for Electric Vehicles in Distribution Networks. Energy Rep. 2023, 9, 1777–1806. [Google Scholar] [CrossRef]
- Sahoo, M.; Kaushik, S.; Gupta, M.; Islam, M.K. EVs and Renewables: Navigating Future Sustainability with Symmetry and Asymmetry. Transp. Res. Part D Transp. Environ. 2024, 132, 104233. [Google Scholar] [CrossRef]
- Chen, L.; Ma, R. Clean Energy Synergy with Electric Vehicles: Insights into Carbon Footprint. Energy Strateg. Rev. 2024, 53, 101394. [Google Scholar] [CrossRef]
- Seo-yeon, P.; Sung-hoon, C. Integrating Vehicle-to-Grid Technologies in Autonomous Electric Vehicle Systems. Appl. Res. Artif. Intell. Cloud Comput. 2022, 5, 105–120. [Google Scholar]
- Taibi, E.; del Valle, C.F.; Howells, M. Strategies for Solar and Wind Integration by Leveraging Flexibility from Electric Vehicles: The Barbados Case Study. Energy 2018, 164, 65–78. [Google Scholar] [CrossRef]
- Wellik, T.K.; Griffin, J.R.; Kockelman, K.M.; Mohamed, M. Utility-Transit Nexus: Leveraging Intelligently Charged Electrified Transit to Support a Renewable Energy Grid. Renew. Sustain. Energy Rev. 2021, 139, 110657. [Google Scholar] [CrossRef]
- Saw, L.H.; Ye, Y.; Tay, A.A. Integration Issues of Lithium-Ion Battery into Electric Vehicles Battery Pack. J. Clean. Prod. 2016, 113, 1032–1045. [Google Scholar] [CrossRef]
- Lee, Y.L.; Lin, C.H.; Farooqui, S.A.; Liu, H.D.; Ahmad, J. Validation of a Balancing Model Based on Master-Slave Battery Management System Architecture. Electr. Power Syst. Res. 2023, 214, 108835. [Google Scholar] [CrossRef]
- Waseem, M.; Ahmad, M.; Parveen, A.; Suhaib, M. Battery Technologies and Functionality of Battery Management System for EVs: Current Status, Key Challenges, and Future Prospectives. J. Power Sources 2023, 580, 233349. [Google Scholar] [CrossRef]
- Ullah, A.; Zhang, Q.; Ahmed, M. The impact of smart connectivity features on customer engagement in electric vehicles. Sustain. Prod. Consum. 2021, 26, 203–212. [Google Scholar] [CrossRef]
- Daziano, R.A.; Sarrias, M.; Leard, B. Are consumers willing to pay to let cars drive for them? Analyzing response to autonomous vehicles. Transp. Res. Part C Emerg. Technol. 2017, 78, 150–164. [Google Scholar] [CrossRef]
- Alahmad, A.; Al Juheshi, F.; Sharif, H.; Alahmad, M.; Shuaib, K.; Abdul-Hafez, M.; Aljuhaishi, N. Overview of ICT in the advancement of electric vehicle penetration: Overview of vehicle grid communication systems and charging infrastructure, and a case study of the economic and environmental benefits of electric vehicles in Nebraska. In Proceedings of the 12th International Conference on Innovations in Information Technology (IIT), Al-Ain, United Arab Emirates, 28–30 November 2016; Volume 28. [Google Scholar]
- Renold, A.P.; Kathayat, N.S. Comprehensive Review of Machine Learning, Deep Learning, and Digital Twin Data-Driven Approaches in Battery Health Prediction of Electric Vehicles. IEEE Access 2024, 12, 43984–43999. [Google Scholar] [CrossRef]
- Omakor, J.; Miah, M.S.; Chaoui, H. Battery Reliability Assessment in Electric Vehicles: A State-of-the-Art. IEEE Access 2024, 12, 77903–77931. [Google Scholar] [CrossRef]
- Esenogho, E.; Djouani, K.; Kurien, A.M. Integrating Artificial Intelligence, Internet of Things, and 5G for Next-Generation Smart Grids: A Survey of Trends, Challenges, and Prospects. IEEE Access 2022, 10, 4794–4831. [Google Scholar] [CrossRef]
- Pielecha, J.; Skobiej, K.; Kurtyka, K. Exhaust Emissions and Energy Consumption Analysis of Conventional, Hybrid, and Electric Vehicles in Real Driving Cycles. Energies 2020, 13, 6423. [Google Scholar] [CrossRef]
- A global Comparison of the Life-Cycle Greenhouse Gas Emissions of Combustion Engine and Electric Passenger Cars. Available online: https://theicct.org/publication/a-global-comparison-of-the-life-cycle-greenhouse-gas-emissions-of-combustion-engine-and-electric-passenger-cars/ (accessed on 29 April 2024).
- Degen, F.; Winter, M.; Bendig, D.; Tübke, J. Energy Consumption of Current and Future Production of Lithium-Ion and Post Lithium-Ion Battery Cells. Nat. Energy 2023, 8, 1284–1295. [Google Scholar] [CrossRef]
- Sharma, S.S.; Manthiram, A. Towards More Environmentally and Socially Responsible Batteries. Energy Environ. Sci. 2020, 13, 4087–4097. [Google Scholar] [CrossRef]
- Xia, X.; Li, P. A review of the life cycle assessment of electric vehicles: Considering the influence of batteries. Sci. Total Environ. 2022, 814, 152870. [Google Scholar] [CrossRef] [PubMed]
Type | Potential Challenges |
---|---|
Technological | Limited driving range |
Inadequate charging infrastructure | |
long charging times | |
Battery capacity fading | |
Overloaded power grids | |
Environmental | Greenhouse gas emissions |
Environmental impact of mining raw materials for batteries | |
Battery recycling issues |
Study | Findings | Limitations |
---|---|---|
Koo et al. (2023) [64] | Identified H01M (processes for converting chemical energy to electrical energy), B60L (vehicles in general), and G06Q (related to real-time and sensing keywords) as future research directions. | The study is limited to South Korea, and the analysis only extends to the subclass level of IPC codes. |
Ma et al. (2022) [65] | Highlighted battery-related technologies, fast charging, and charging infrastructure as key development areas. | Study data only extend through 2016. |
Fang and Li (2020) [48,61] | China’s pure electric vehicle technology reached a saturation point in 2023, and electric vehicle technology is expected to reach saturation in 2026. | |
Tiago et al. (2022) [62] | Fuel cell electric vehicles (FCEVs) in Europe reached technological saturation in 2012, while those in the United States reached technological saturation in 2016. |
Scope of inquiry: Title, Abstract, or Claims | |
Step 1. Scope of investigation Filing Date = (1 January 2004 – 31 December 2023) (Resulted in 899,426 documents) | |
Step 2. Grouped by Simple Families (Resulted in 659,975 documents) | |
Step 3. Document Type = (Patent_application, Granted_patent) (Resulted in 450,054 documents) | |
Step 4. Legal Status = (Active, Inactive, Expired) (Resulted in 210,056 documents) | |
Step 5. Manually reviewing (Resulted in 187,700 documents) | |
Search strategy | title:(‘Electric vehicle*’) OR abstract:(‘Electric vehicle*’) OR claim:(‘Electric vehicle*’) OR title:(‘Electric automobile*’) OR abstract:(‘Electric automobile*’) OR claim:(‘Electric automobile*’) OR title:(‘new energy car* ‘) OR abstract:(‘new energy car*’) OR claim:(‘new energy car* ‘) OR title:(‘new energy automobile* ‘) OR abstract:(‘new energy automobile* ‘) OR claim:(‘new energy automobile* ‘) OR title:(‘new energy vehicle* ‘) OR abstract:(‘new energy vehicle* ‘) OR claim:(‘new energy vehicle* ‘) OR title:(‘alternative fuel vehicle* ‘) OR abstract:(‘alternative fuel vehicle* ‘) OR claim:(‘alternative fuel vehicle* ‘) OR title:(‘alternative fuel automobile* ‘) OR abstract:(‘alternative fuel automobile* ‘) OR claim:(‘alternative fuel automobile* ‘) OR title:(‘alternative fuel car* ‘) OR abstract:(‘alternative fuel car* ‘) OR claim:(‘alternative fuel car* ‘) OR title:(‘Eco-Friendly car* ‘) OR abstract:(‘Eco-Friendly car* ‘) OR claim:(‘Eco-Friendly car* ‘) OR title:(‘Eco-Friendly automobile* ‘) OR abstract:(‘Eco-Friendly automobile* ‘) OR claim:(‘Eco-Friendly automobile* ‘) OR title:(‘Eco-Friendly vehicle* ‘) OR abstract:(‘Eco-Friendly vehicle* ‘) OR claim:(‘Eco-Friendly vehicle* ‘) OR title:(‘Green vehicle* ‘) OR abstract:(‘Green vehicle* ‘) OR claim:(‘Green vehicle* ‘) OR title:(‘Green automobile* ‘) OR abstract:(‘Green automobile* ‘) OR claim:(‘Green automobile* ‘) OR title:(‘Green vehicle* ‘) OR abstract:(‘Green vehicle* ‘) OR claim:(‘Green vehicle* ‘) OR title:(‘fuel cell vehicle* ‘) OR abstract:(‘fuel cell vehicle* ‘) OR claim:(‘fuel cell vehicle* ‘) OR title:(‘fuel cell automobile* ‘) OR abstract:(‘fuel cell automobile* ‘) OR claim:(‘fuel cell automobile* ‘) OR title:(‘fuel cell car* ‘) OR abstract:(‘fuel cell car* ‘) OR claim:(‘fuel cell car* ‘) OR title:(‘hybrid car* ‘) OR abstract:(‘hybrid car* ‘) OR claim:(‘hybrid car* ‘) OR title:(‘hybrid automobile* ‘) OR abstract:(‘hybrid automobile* ‘) OR claim:(‘hybrid automobile* ‘) OR title:(‘hybrid vehicle* ‘) OR abstract:(‘hybrid vehicle* ‘) OR claim:(‘hybrid vehicle* ‘) OR title:(‘battery vehicle* ‘) OR abstract:(‘battery vehicle* ‘) OR claim:(‘battery vehicle* ‘) OR title:(‘battery car* ‘) OR abstract:(‘battery car* ‘) OR claim:(‘battery car* ‘) OR title:(‘battery automobile* ‘) OR abstract:(‘battery automobile* ‘) OR claim:(‘battery automobile* ‘) |
Stage of the S-Curve | Characteristics | Patent Strategy |
---|---|---|
Emerging | Slow technological progress despite heavy R and D investments | Focus on creating and securing foundational patents, monitoring competitors, and acquiring core technologies |
Growth | High ratio of technological progress compared to R and D spending | Secure improvement and application patents to strengthen market position, differentiate with design and trademarks |
Maturity | R and D spending increases while technological progress slows | Actively protect existing patents, consider strategic alliances, and license out patents to generate revenue |
Saturation | Further improvements require substantial R and D for minimal gains | Actively explore future promising technologies as market demand for current technologies decreases |
Scope | Emerging (Years) | Growth (Years) | Maturity (Years) | Saturation (Years) | Saturation (Numbers) |
---|---|---|---|---|---|
Global | 2001 | 2007 | 2014 | 2021 | 22,805 |
Korea | 1999 | 2006 | 2012 | 2019 | 2080 |
Scope | Logistic Fits | Congruence Analysis | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
- | Midpoint (t50) (Years) | Growth Time (t10 − t90) (Years) | Saturation (k) (Numbers) | R2 | p Value 4 | |||||||||
- | Value 1 | Min 2 | Max 2 | Error 3 | Value 1 | Min 2 | Max 2 | Error 3 | Value 1 | Min 2 | Max 2 | Error 3 | - | - |
Global | 2014 | 2014 | 2015 | 0.002 | 13 | 11 | 16 | 0.19 | 22,805 | 20,653 | 26,793 | 0.13 | 0.961 | 0.00 |
Korea | 2012 | 2011 | 2013 | 0.005 | 12.5 | 11 | 14 | 0.12 | 2080 | 1951 | 2200 | 0.06 | 0.983 | 0.00 |
IPC Main-Group | The Technical Content [96] | Standardized Betweenness Centrality |
---|---|---|
B60W10 | Conjoint control of vehicle sub-units of different types or different functions | 0.133101 |
H02J7 | Circuit arrangements for charging or depolarizing batteries or for supplying loads from batteries | 0.116794 |
B60R16 | Electric or fluid circuits specially adapted for vehicles and not otherwise provided for | 0.10219 |
B60L50 | Electric propulsion with power supplied within the vehicle | 0.096273 |
B60L53 | Methods of charging batteries, specially adapted for EVs; charging stations or on-board charging equipment; exchange of energy storage elements in EVs | 0.095048 |
B60K6 | Arrangement or mounting of plural diverse prime movers for mutual or common propulsion | 0.061831 |
B60W20 | Control systems specially adapted for hybrid vehicles | 0.04334 |
B60L11 | Electric propulsion with power supplied within the vehicle | 0.043142 |
B60L58 | Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for EVs | 0.040302 |
B60K1 | Arrangement or mounting of electrical propulsion units | 0.034509 |
B60L15 | Methods, circuits, or devices for controlling the propulsion of electrically propelled vehicles | 0.030198 |
G01R31 | Purposes of road vehicle drive control systems not related to the control of a particular sub-unit | 0.027657 |
B60T13 | Transmitting braking action from initiating means to ultimate brake actuator with power assistance or drive; brake systems incorporating such transmitting means | 0.027589 |
B60L7 | Electrodynamic brake systems for vehicles in general | 0.021699 |
B60W30 | Purposes of road vehicle drive control systems not related to the control of a particular sub-unit | 0.02151 |
G06Q50 | Information and communication technology [ICT] specially adapted for the implementation of business processes in specific business sectors | 0.017998 |
B60L3 | Electric devices on electrically propelled vehicles for safety purposes; monitoring operating variables | 0.017412 |
H01M10 | Secondary cells; manufacture thereof | 0.016875 |
G06Q10 | Administration; management | 0.014035 |
B60K17 | Arrangement or mounting of transmissions in vehicles | 0.013854 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Chen, Y.; Cho, S.S. Exploring Electric Vehicle Patent Trends through Technology Life Cycle and Social Network Analysis. Sustainability 2024, 16, 7797. https://doi.org/10.3390/su16177797
Chen Y, Cho SS. Exploring Electric Vehicle Patent Trends through Technology Life Cycle and Social Network Analysis. Sustainability. 2024; 16(17):7797. https://doi.org/10.3390/su16177797
Chicago/Turabian StyleChen, Yuan, and Seok Swoo Cho. 2024. "Exploring Electric Vehicle Patent Trends through Technology Life Cycle and Social Network Analysis" Sustainability 16, no. 17: 7797. https://doi.org/10.3390/su16177797