Electromobility Research Group
Research keywords:
· electromobility
· charging infrastructure
· electric bus
· hybrid railcars
· smart grid
· charging management
· life-cycle analysis
· V2G
· total cost of ownership (TCO)
· decision support
· energy management
Horizon Europe keywords:
· Batteries
· Cities and communities
· Clean, sustainable, secure and competitive energy supply
· Hydrogen
· Renewable energy
· Smart and sustainable transport and mobility
· European Green Deal
Faculty of Transportation Engineering and Vehicle Engineering Department of Transport Technology and Economics
Introduction of the Research Group
We investigate factors affecting the spread and use of electric vehicles and develop planning and operational methods to support electromobility. We integrate expertise in transportation engineering, electrical engineering, energetics, and social sciences with a holistic view. We conduct interdisciplinary quantitative and qualitative research studies. Our research group has competence in multi-criteria evaluation, system development, mathematical modeling, and multi-objective optimization.In our research projects, we investigate the social acceptance of electric cars, develop information system to support electric car use, elaborated a decision supporting tool based on the total cost of ownership model of new vehicles, a charging station locating method and a charging management method . Our aim is to reduce the negative impact of charging on the power grid using local power generation and energy storage systems. Therefore, we modeled the charging demand and supply of the power network and elaborated centralized and decentralized charging management solutions. We investigated the life-cycle environmental impact of e-cars and calculated the total cost of ownership. We elaborated a method to optimize the public electric bus service in urban areas.Accordingly, we modeled the service and identified the factors affecting the energy consumption. Stochastic factors were considered with probability functions. The optimal service was determined with a confidence level. Furthermore, we investigate the shared services and micromobility using electric vehicles. we modeled the charging demand and supply of the power network and elaborated centralized and decentralized charging management solutions. We investigated the life-cycle environmental impact of e-cars and calculated the total cost of ownership. We elaborated a method to optimize the public electric bus service in urban areas. Accordingly, we modeled the service and identified the factors affecting the energy consumption.Stochastic factors were considered with probability functions. The optimal service was determined with a confidence level. Furthermore, we investigate the shared services and micromobility using electric vehicles. we modeled the charging demand and supply of the power network and elaborated centralized and decentralized charging management solutions. We investigated the life-cycle environmental impact of e-cars and calculated the total cost of ownership. We elaborated a method to optimize the public electric bus service in urban areas. Accordingly, we modeled the service and identified the factors affecting the energy consumption. Stochastic factors were considered with probability functions.The optimal service was determined with a confidence level. Furthermore, we investigate the shared services and micromobility using electric vehicles. We investigated the life-cycle environmental impact of e-cars and calculated the total cost of ownership. We elaborated a method to optimize the public electric bus service in urban areas. Accordingly, we modeled the service and identified the factors affecting the energy consumption. Stochastic factors were considered with probability functions. The optimal service was determined with a confidence level. Furthermore, we investigate the shared services and micromobility using electric vehicles. We investigated the life-cycle environmental impact of e-cars and calculated the total cost of ownership. We elaborated a method to optimize the public electric bus service in urban areas. Accordingly, we modeled the service and identified the factors affecting the energy consumption. Stochastic factors were considered with probability functions. The optimal service was determined with a confidence level. Furthermore, we investigate the shared services and micromobility using electric vehicles.
Watch our 3-minute introductory video:
Achievements
- Electric passenger car's emission and total cost calculation method and information system
- Charging station locating method based on land use and traffic volume in urban areas and along national roads
- Charging management method and dynamic tariff system
- Optimization method for electric bus service planning and operation in urban areas including charging infrastructure, vehicle fleet composition, and service characteristics
- Local power generation and energy storage capacity optimization method
Publications
Csonka, B. 2021. Optimization of Static and Dynamic Charging Infrastructure for Electric Buses. Energies, 14(12), 3516. DOI: 10.3390/en14123516Csiszár, Cs., Csonka, B., Földes, D., Lovas, T., Wirth, E. 2020. Location optimization method for fast-charging stations along national roads. Journal of Transport Geography, 88. DOI: 10.1016/j.jtrangeo.2020.102833
Csonka, B. 2020. Centralized charging power distribution method for electric vehicles. 2020 Smart City Symposium Prague (SCSP), pp. 1-6. DOI: 10.1109/SCSP49987.2020.9134002
Csiszár, Cs., Csonka, B., Földes, D., Lovas, T., Wirth, E. 2019. Urban Public Charging Station Locating Method for Electric Vehicles Based on Land Use Approach. Journal of Transport Geography, 74, pp. 173-180. DOI: 10.1016/j.jtrangeo.2018.11.016
Csonka, B., Csiszár, Cs. 2019. Integrated Information Service for Plug-In Electric Vehicle Users Including Smart Grid Functions. Transport Journal, 34(1), pp. 135-145. DOI: 10.3846/transport.2019.8548
Awards
2020 Hungarian Scientific Association for Transport – Literature prize; 2020 UNI BME Startup Program – 1st prize, BolleyJournals
Energies, Journal of Transport Geography, Periodica Polytechnica Transportation Engineering, TransportProjects
- H2020: Electric Mobility Europe (EME), Electric travelling, 2018-2020, EU
- Green Finance Research Project: E-mobility and smart city, 2020-, National Bank of Hungary (MNB)
- 2019-2.1.11-TÉT Funding for bilateral science and technology (S&T) cooperation, Chinese relation "Development of Energy Management Services to Optimize Energy Use of Electric Road Vehicles", 2022-2023, National Research, Development and Innovation Office (NKFIH)
- Higher Education Institutional Excellence Program, Artificial Intelligence, Future Mobility (BME FIKP MI/FM) Electromobility research group, 2018-2021, NKFIH
- Concept of national charging station deployment and database – study, 2017, e-Mobi Kft.
Industry relations
Center for Budapest Transport (BKK), e-Mobi Nonprofit Kft., GriffSoft Zrt., JAK Hungarian E-Mobility Cluster, Meter Solutions Kft., MOL Nyrt., Wattmanager Kft.Conferences
Conference of Transport Sciences Győr, presenter and chairman since 2016 Smart Cities Symposium, Prague presenter and scientific committee member since 2018 Member of the International Council for Priority Research Area Smart Cities and Future Mobility, Silesian University of Technology, Katowice 2020- 17th Scientific and technical conference Transport Systems Theory and Practice, Katowice, scientific committee member 2021 ZIRP 2021 International Scientific Conference, The Science and Development of Transport, 30th September – 1st October 2021, Šibenik, Croatia program committee member 19th European Transport Congress, European Green Deal, Challenges and Solutions for Mobility and Logistics in Cities, Maribor October 7-8, 2021 scientific committee member 6th International Conference on Road and Rail Infrastructure 20-21 May 2021, Online, presenter