Development Path and Model Design of a New Energy Vehicle in China
Abstract
:1. Introduction
2. Current Development Status of New Energy Vehicles
2.1. Analysis of the Development Path
2.2. Development Status of the Industry
2.2.1. Energy Consumption in the Field of Transportation
2.2.2. Current Status of Production of New Energy Vehicles
2.3. Development Status of the Subindustry
3. Obstacles to and Advantages of the Development of New Energy Vehicles
3.1. Obstacles to Development
3.1.1. Policy Issues
3.1.2. Basic Issues
- (1).
- The standard of construction infrastructure is not uniform
- (2).
- High cost of battery construction
3.1.3. Market Issues
3.1.4. Technical Issues
3.2. Advantages of Development
3.2.1. Policy Advantage
3.2.2. Market Advantage
4. Design of New Energy Vehicle Development Model
4.1. Design of Policy Framework
4.1.1. New Energy Vehicle Manufacturers
4.1.2. Charging Facility Market
- (1).
- Expanding the Size of the Charging Facility Market
4.1.3. Design of the Zero-Emission Vehicle Integrated Mechanism
- (1).
- Pay a fine.
- (2).
- Purchase ZEVs with the surplus of the enterprises (the buyers and sellers negotiate to buy; the price will be lower than the government fines).
- (1).
- The surplus integral can be sold.
- (2).
- The integral can also be stored for future compliance (as the policy is strict, the price of the integral is rising). The government announces the integral and integral stock for the year.
4.2. Business Model Design
4.2.1. New Energy Vehicle Profit model
- (1).
- Short term: low cost plus service fees
- (2).
- Mid-term: wholesale, retail electricity plus charging service fees
- (3).
- Long term: wholesale, retail electricity plus charging service plus adding value
4.2.2. Construction of Management Platform
- (1).
- Government New Energy Vehicle Platform
- (2).
- Intelligent new energy vehicle rental platform
- (3).
- New energy vehicle cloud platform
4.2.3. Equipment Manufacturing Mode
4.2.4. Sales Model of Vehicle Power Battery
- (1).
- Sales model of full vehicle battery
- (2).
- Naked vehicle sales plus battery replacement
4.2.5. Management Model of Vehicle Power Battery Recycling
- (1).
- Producer recovery system model
- (2).
- Battery rental recovery system model
4.3. Technical Support
4.3.1. System Intelligentization
4.3.2. Utility of the Charging Network
- (1).
- Family conventional charging points used as an energy supply system
- (2).
- Improve the construction of charging networks
5. Conclusions
- (1).
- Power battery monomers, modules, and management systems should be established, forming battery material technology research alliances with colleges and universities, and building a common technology platform to conduct joint research on the dynamic energy density, cell cycle life, and other common problems.
- (2).
- Technology alliances should be relied on to conduct research on the materials, system, and technology of power batteries and grasp the frontier technology of power batteries. The R&D of power batteries can improve the production efficiency and ensure the consistency of the products. Enterprises should be guided to increase investment in the research and development of key materials, such as power battery separators and electrolytes.
- (3).
- Investment funds in R&D should be set up to support technological innovation and transformation. The Chinese government must prioritize support for the power battery industry and key material industry alliances in the form of funding, and guide enterprises to increase investments in technology, engineering, standard setting, and market applications. Through the formulation and implementation of various preferential policies of talent, the Chinese government will increase the cultivation and introduction of a technological innovation team.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Song, J.; Cha, J. Development of Prediction Methodology for CO2 Emissions and Fuel Economy of Light Duty Vehicle. Energy 2022, 244, 123166. [Google Scholar] [CrossRef]
- Wei, H. Impacts of China’s National Vehicle Fuel Standards and Subway Development on Air Pollution. J. Clean. Prod. 2019, 241, 118399. [Google Scholar] [CrossRef]
- Chandra, M. Investigating the Impact of Policies, Socio-Demography and National Commitments on Electric-Vehicle Demand: Cross-Country Study. J. Transp. Geogr. 2022, 103, 103410. [Google Scholar] [CrossRef]
- Lv, Z.; Shang, W. Impacts of Intelligent Transportation Systems on Energy Conservation and Emission Reduction of Transport Systems: A Comprehensive Review. Green Technol. Sustain. 2023, 1, 100002. [Google Scholar] [CrossRef]
- Liu, L.; Liu, S.; Wu, L.; Zhu, J.; Shang, G. Forecasting the Development Trend of New Energy Vehicles in China by an Optimized Fractional Discrete Grey Power Model. J. Clean. Prod. 2022, 372, 133708. [Google Scholar] [CrossRef]
- Metwly, M.Y.; Ahmed, M.; Hamad, M.S.; Abdel-Khalik, A.S.; Hamdan, E.; Elmalhy, N.A. Power Management Optimization of Electric Vehicles for Grid Frequency Regulation: Comparative Study. Alex. Eng. J. 2022, in press. [Google Scholar] [CrossRef]
- Huang, P.; Tu, R.; Zhang, X.; Han, M.; Sun, Y.; Hussain, S.A.; Zhang, L. Investigation of Electric Vehicle Smart Charging Characteristics on the Power Regulation Performance in Solar Powered Building Communities and Battery Degradation in Sweden. J. Energy Storage 2022, 56, 105907. [Google Scholar] [CrossRef]
- Fan, W.; Huang, L.; Tan, Z.; Xue, F.; De, G.; Song, X.; Cong, B. Multi-Objective Optimal Model of Rural Multi-Energy Complementary System with Biogas Cogeneration and Electric Vehicle Considering Carbon Emission and Satisfaction. Sustain. Cities Soc. 2021, 74, 103225. [Google Scholar] [CrossRef]
- Liu, H.; Huang, K.; Wang, N.; Qi, J.; Wu, Q.; Ma, S.; Li, C. Optimal Dispatch for Participation of Electric Vehicles in Frequency Regulation Based on Area Control Error and Area Regulation Requirement. Appl. Energy 2019, 240, 46–55. [Google Scholar] [CrossRef]
- Fan, W.; Tan, Z.; Li, F.; Zhang, A.; Ju, L.; Wang, Y.; De, G. A Two-Stage Optimal Scheduling Model of Integrated Energy System Based on CVaR Theory Implementing Integrated Demand Response. Energy 2023, 263, 125783. [Google Scholar] [CrossRef]
- Tan, Z.; Yang, P.; Nehorai, A. An optimal and distributed demand response strategy with electric vehicles in the smart grid. IEEE Trans. Smart Grid 2014, 5, 861–869. [Google Scholar] [CrossRef]
- Pan, Z.; Liu, S. Research on charging and discharging dispatch of electric vehicles based on demand side discharge bidding. Power Syst. Technol. 2016, 40, 1140–1146. [Google Scholar]
- Xiaodong, Y.; Youbing, Z.; Bo, Z. Automated demand response method for electric vehicles charging and discharging to achieve supply-demand coordinated optimization. Proc. CSEE 2017, 37, 120–129. [Google Scholar]
- Huanqiang, L. Analysis of Charging Service Mode for Electric Vehicle. Distrib. Energy 2017, 2, 31. [Google Scholar]
- Qi, L.; Wu, X.; Zeng, X.; Feng, Y.; Pan, H.; Zhang, Z.; Yuan, Y. An electro-mechanical braking energy recovery system based on coil springs for energy saving applications in electric vehicles. Energy 2020, 200, 117472. [Google Scholar] [CrossRef]
- Hao, Y.; Dong, L.; Liang, J.; Liao, X.; Wang, L.; Shi, L. Power forecasting-based coordination dispatch of PV power generation and electric vehicles charging in microgrid. Renew. Energy 2020, 155, 1191–1210. [Google Scholar] [CrossRef]
- Yao, W.; Zhao, J.; Wen, F.; Xue, Y.; Ledwich, G. A hierarchical decomposition approach for coordinated dispatch of plug-in electric vehicles. IEEE Trans. Power Syst. 2013, 28, 2768–2778. [Google Scholar] [CrossRef]
- Kley, F.; Lerch, C.; Dallinuer, D. New business models for electric cars-a holistic approach. Energy Policy 2011, 39, 3392–3403. [Google Scholar] [CrossRef] [Green Version]
- Bohnsack, R.; Pinkse, J.; Kolk, A. Business models for sustainable technologies: Exploring business model evolution in the case of electric vehicles. Res. Policy 2014, 43, 284–300. [Google Scholar] [CrossRef] [Green Version]
- Zhai, H.; Frey, H.C.; Rouphail, N.M. Development of a modal emissions model for a hybrid electric vehicle. Transp. Res. Part D 2011, 16, 444–450. [Google Scholar] [CrossRef]
- Shi, X.; Li, L.; Yang, J. The carbon emission reduction potential of low carbon traffic electric vehicle and its influencing factors analysis. Environ. Sci. 2014, 34, 385–394. [Google Scholar]
- Dai, Z.; Liu, H.; Rodgers, M.O.; Guensler, R. Electric Vehicle Market Potential and Associated Energy and Emissions Reduction Benefits. Appl. Energy 2022, 322, 119295. [Google Scholar] [CrossRef]
- Bai, S.; Liu, C. Overview of Energy Harvesting and Emission Reduction Technologies in Hybrid Electric Vehicles. Renew. Sustain. Energy Rev. 2021, 147, 111188. [Google Scholar] [CrossRef]
- Tan, Z.; Wang, S.; Yang, H.; Xing, T.; Liu, L.; Tian, W. Potential Calculation Model of Energy-saving and Emission Reduction of Electric Vehicles. Mod. Electr. Power 2013, 30, 79–81. [Google Scholar]
- Brady, J.; O’Mahony, M. The potential impacts of electric vehicles on climate change and urban air quality. Transp. Res. Part D 2011, 17, 188–193. [Google Scholar] [CrossRef]
- Reed, T.; Doucette, M.; McCulloch, D. Modeling the prospects of plug-in plug hybrid electric vehicle to reduce CO2 emissions. Appl. Energy 2011, 88, 2315–2323. [Google Scholar]
- Ojeda-Esteybar, D.M.; Rubio-Barros, R.U.; Varuas, A. Integrated operational planning of hydrothermal power and natural gas systems with large scale storages. J. Mod. Power Syst. Clean Energy 2017, 5, 299–313. [Google Scholar] [CrossRef] [Green Version]
- Ramadhani, U.H.; Shepero, M.; Munkhammar, J.; Widén, J.; Etherden, N. Review of probabilistic load flow approaches for power distribution systems with photovoltaic generation and electric vehicle charging. Int. J. Electr. Power Energy Syst. 2020, 120, 106003. [Google Scholar] [CrossRef]
- Secinaro, S.; Brescia, V.; Calandra, D.; Biancone, P. Employing bibliometric analysis to identify suitable business models for electric cars. J. Clean. Prod. 2020, 264, 121503. [Google Scholar] [CrossRef]
- Yang, J.; Wu, F.; Yan, J.; Lin, Y.; Zhan, X.; Chen, L.; Liao, S.; Xu, J.; Sun, Y. Charging demand analysis framework for electric vehicles considering the bounded rationality behavior of users. Int. J. Electr. Power Energy Syst. 2020, 119, 105952. [Google Scholar] [CrossRef]
- Lefeng, S.; Chunxiu, L.; Jingrong, D.; Cipcigan, L. External benefits calculation of sharing electric vehicles in case of Chongqing China. Util. Policy 2020, 64, 101021. [Google Scholar] [CrossRef]
- Akinlabi, A.H.; Solyali, D. Configuration, design, and optimization of air-cooled battery thermal management system for electric vehicles: A review. Renew. Sustain. Energy Rev. 2020, 125, 109815. [Google Scholar] [CrossRef]
- He, H.; Sun, F.; Wang, Z.; Lin, C.; Zhang, C.; Xiong, R.; Deng, J.; Zhu, X.; Xie, P.; Zhang, S.; et al. China’s Battery Electric Vehicles Lead the World: Achievements in Technology System Architecture and Technological Breakthroughs. Green Energy Intell. Transp. 2022, 1, 100020. [Google Scholar] [CrossRef]
- National Bureau of Statistics of the People’s Republic of China. China Statistical Yearbook; China Statistics Press: Beijing, China, 2021. Available online: http://www.stats.gov.cn/ (accessed on 1 December 2022).
- Zhou, S.; Wang, J.; Xu, B. Innovative Coupling and Coordination: Automobile and Digital Industries. Technol. Forecast. Soc. Change 2022, 176, 121497. [Google Scholar] [CrossRef]
- Zhang, H.; Cai, G. Subsidy strategyS on new-energy vehicle based on incomplete information: A Case in China. Phys. A Stat. Mech. Its Appl. 2020, 541, 123370. [Google Scholar] [CrossRef]
- Ji, S.F.; Zhao, D.; Luo, R.J. Evolutionary game analysis on local governments and manufacturers’ behavioral strategies: Impact of phasing out subsidies for new energy vehicles. Energy 2019, 189, 116064. [Google Scholar] [CrossRef]
- Guo, H.; Wang, X.; Li, L. State-of-charge-constraint-based energy management strategy of plug-in hybrid electric vehicle with bus route. Energy Convers. Manag. 2019, 199, 111972. [Google Scholar] [CrossRef]
No. | Subindustry | Trade Barriers | Industrial Transfer Space | Demand Elasticity |
---|---|---|---|---|
1 | Electrolyte | High | Higher | High |
2 | Diaphragm | High | Higher | High |
3 | Whole vehicle | Higher | High | Lower |
4 | Electrical control system | Higher | High | High |
5 | Lithium ore resources | Lower | High | Lower |
6 | Charging stations | Low | Higher | High |
Current Type | Charging Time | Advantages | Shortcomings | Scope of Application | |
---|---|---|---|---|---|
Slow charging | Constant voltage or constant current mode of small current | 5–8 h | Low cost of charger installation and charging | Difficult to meet the requirements of vehicle emergency operation | A family, a parking lot, a public charging station |
Fast charging | High current | 20 min–2 h | Short charging time | High installation cost, high requirements for the safety of charging technology | Special charging station |
Enterprises | Cooperation Model | Cooperative Partner |
---|---|---|
Toyota | Joint R&D + independent R&D | Panasonic |
Volkswagen | Joint R&D | SANYO motor, BYD, Toshiba |
Suzuki | Procurement + joint R&D | Sanyo |
General Motors | Procurement + independent R&D | LG CHEMICAL LTD |
Ford | Procurement + independent R&D | LG CHEMICAL LTD |
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. |
© 2022 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
Tan, Q.; Wang, Z.; Fan, W.; Li, X.; Li, X.; Li, F.; Zhao, Z. Development Path and Model Design of a New Energy Vehicle in China. Energies 2023, 16, 220. https://doi.org/10.3390/en16010220
Tan Q, Wang Z, Fan W, Li X, Li X, Li F, Zhao Z. Development Path and Model Design of a New Energy Vehicle in China. Energies. 2023; 16(1):220. https://doi.org/10.3390/en16010220
Chicago/Turabian StyleTan, Qingbo, Zhuning Wang, Wei Fan, Xudong Li, Xiangguang Li, Fanqi Li, and Zihao Zhao. 2023. "Development Path and Model Design of a New Energy Vehicle in China" Energies 16, no. 1: 220. https://doi.org/10.3390/en16010220
APA StyleTan, Q., Wang, Z., Fan, W., Li, X., Li, X., Li, F., & Zhao, Z. (2023). Development Path and Model Design of a New Energy Vehicle in China. Energies, 16(1), 220. https://doi.org/10.3390/en16010220