The barriers preventing the widespread introduction of electric vehicles are often not just technological ones, but can be due to regulations, user or potential user attitudes.

There are also potential barriers due to the new relationships along the value chain that these new technologies bring with them. These include the transition needed within the existing automotive supply chain. The future of existing suppliers less secure (e.g. valves, pistons, camshafts), while new suppliers are not necessarily used to working with automotive clients (batteries, traction motors, ICT). But they also go beyond the conventional automotive supply chain where links with energy suppliers are now increasingly valued, while the move towards connected and autonomous vehicles also creates the need for new relationships and partnerships.

All three participating Schools have a track record in various aspects of the EV value chain, including areas such as smart grids, energy demand scenarios for EVs, regulatory options and incentives, consumer barriers and incentives.

All three Schools are among the top ranking in their disciplines in the UK, the Schools of Psychology and Business in the top ten, while in global rankings, the Business School was recently ranked within the top 100 and the School of Psychology in the top 40.

Selected publications

• Xydas, E. , Marmaras, C. and Cipcigan, L. M. 2016. A multi-agent based scheduling algorithm for adaptive electric vehicles charging. Applied Energy 177 , pp.354-365. (10.1016/j.apenergy.2016.05.034)
• Al Essa, M. and Cipcigan, L. M. 2016. Reallocating charging loads of electric vehicles in distribution networks. Applied Sciences 6 (2) 53. (10.3390/app6020053)
• Xydas, E. et al. 2016. A data-driven approach for characterising the charging demand of electric vehicles: A UK case study. Applied Energy 162 , pp.763-771. (10.1016/j.apenergy.2015.10.151)
• Luè, A. et al., 2016. Future priorities for a climate-friendly transport: a European strategic research agenda towards 2030. International Journal of Sustainable Transportation 10 (3), pp.236-246. (10.1080/15568318.2014.893043)
• Xenias, D. 2016. Summative Evaluation Report: Learning from seven European electric fleets. Project Report.[Online].eBridgeAvailable athttp://ebridge-project.eu/images/ebridge/docs/d4-3-summative-report-final-summary-96294.pdf.
• Whitmarsh, L. and Xenias, D. 2015. Understanding people and cars. In: Nieuwenhuis, P. A. H. F. and Wells, P. E. eds. The Global Automotive Industry. Automotive Series Wiley. , pp.29-40.
• Wells, P. E. and Xenias, D. 2015. From 'freedom of the open road' to 'cocooning': Understanding resistance to change in personal private automobility. Environmental Innovation and Societal Transitions 16 , pp.106-119. (10.1016/j.eist.2015.02.001)
• Xenias, D. et al. 2015. UK smart grid development: an expert assessment of the benefits, pitfalls and functions. Renewable Energy 81 , pp.89-102. (10.1016/j.renene.2015.03.016)
• Abdulah, A. et al., 2015. eBRIDGE Toolkit - Successful operation and promotion of electric fleets in Europe: an insider’s guide. Project Report.[Online].eBRIDGEAvailable athttp://www.ebridge-project.eu/images/ebridge/docs/ebridge-toolkit-rev3-low-82490.pdf.
• Wells, P. E. and Nieuwenhuis, P. A. H. F. 2015. EV business models in a wider context: balancing change and continuity in the automotive industry. In: Beeton, D. and Meyer, G. eds. Electric Vehicle Business Models; Global Perspectives. Lecture Notes in Mobility Springer. , pp.3-16.
• Connor, P. M. et al., 2014. Policy and regulation for smart grids in the United Kingdom. Renewable and Sustainable Energy Reviews 40 , pp.269-286. (10.1016/j.rser.2014.07.065)
• Özel, F. M. et al., 2014. How to strategically position European SMEs as part of an electric vehicle technology value chain. International Journal of Electric and Hybrid Vehicles 6 (3), pp.227-254. (10.1504/IJEHV.2014.065728)
• Newman, D. et al. 2014. Learning from electric cars as socio-technical mobility experiments: where next?. Transfers 4 (2), pp.23-41. (10.3167/TRANS.2014.040203)
• Grau, I. et al. 2014. Management of electric vehicle battery charging in distribution networks with multi-agent systems. Electric Power Systems Research 110 , pp.172-179. (10.1016/j.epsr.2014.01.014)
• Newman, D. et al. 2014. Urban, sub-urban or rural: where is the best place for electric vehicles?. International Journal of Automotive Technology and Management, 14 (3/4), pp.306-323. (10.1504/IJATM.2014.065295)
• Skarvelis-Kazakos, S. et al., 2013. Implementing agent-based emissions trading for controlling Virtual Power Plant emissions. Electric Power Systems Research 102 , pp.1-7. (10.1016/j.epsr.2013.04.004)
• Xenias, D. and Whitmarsh, L. E. 2013. Dimensions and determinants of expert and public attitudes to sustainable transport policies and technologies. Transportation Research Part A: Policy and Practice 48 , pp.75-85. (10.1016/j.tra.2012.10.007)
• Papadopoulos, P. et al. 2013. Coordination of the charging of electric vehicles using a multi-agent system. IEEE Transactions on Smart Grid 4 (4), pp.1802-1809. (10.1109/TSG.2013.2274391)
• Budde Christensen, T. , Wells, P. E. and Cipcigan, L. M. 2012. Can innovative business models overcome resistance to electric vehicles? Better Place and battery electric cars in Denmark. Energy Policy 48 , pp.498-505. (10.1016/j.enpol.2012.05.054)
• Papadopoulos, P. et al. 2012. Electric vehicles' impact on British distribution networks. IET Electrical Systems in Transportation 2 (3), pp.91-102. (10.1049/iet-est.2011.0023)
• Papadopoulos, P. et al. 2011. Electricity demand with electric cars in 2030: comparing Great Britain and Spain. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 225 (5), pp.551-566. (10.1177/0957650911406343)

Investigator(s)	Funder	Title	Date	Amount
Mourshed, Rezgui, Cipcigan, Rana	European Commission (FP7)	Multi-Agent Systems and secured coupling of Telecom and Energy grids for next generation smart grid services (MAS2TERING)	2014-2017	£396,378 and £25,284
Cipcigan, Jenkins, Rana, Burnap	EPSRC (with TSB)	Ebbs and flows of energy systems	2014-2017	£345,145
Cipcigan	Royal Academy of Engineering (RAEng)	Future balancing services for high level of embedded electricity generation	2015-2016	£30,000
Burnap, Rana, Cipcigan	EADS UK	SCADA Cyber Security Lifecycle	2014-2016	£277,660
Jenkins, Wu, Cipcigan	EPSRC via Imperial College London	Economics and grid planning for smart electromobility	2013-2016	£325,170
Whitmarsh, Xenias, Cipcigan	European Commission	Empowering e-fleets for business and private purposes in cities (Ebridge)	2013-2016	£146,628
Davies, Nieuwenhuis, Cipcigan	ERDF INTERREG IVb	ENEVATE2	2014-2015	n/a
Cipcigan	National Grid	Energy strategy and policy	2015	£10,000
Cipcigan, Rana	Innovate UK	Ebb and flow energy systems	2013	£10,665
Cipcigan	Innovate UK	Agent-based controllers for electric vehicles and microgenerators	2012-2013	£4,560
Cipcigan	EPSRC	Smart management of electric vehicles	2011-2013	£93,402
Whitmarsh, Xenias, Cipcigan	UKERC via University of Westminster	Scenarios for the development of smart grids in the UK	2011-2013	£140,270
Davies, Nieuwenhuis, Cipcigan	ERDF INTERREG IVb	European network on electric vehicles and transferring expertise (ENEVATE)	2010-2013	£355,408
Cipcigan, Holford, Davies	EPSRC	Pathways Electric Vehicle Value Chain - Bridging the Gaps	2011-2012	£39,164
Ekanayake, Jenkins, Cipcigan, Wu	European Commission (FP7)	Mobile Energy Resources in Grids of Electricity (MERGE)	2010-2011	£238,55

Academic staff

Associated staff