Policy insights and modelling challenges: The case of passenger car powertrain technology transition in the European Union

Eur. Transp. Res. Rev. (2017) 9: 37 DOI 10.1007/s12544-017-0252-x ORIGINAL PAPER Policy insights and modelling challenges: The case of passenger car powertrain technology transition in the European Union Gillian Harrison 1 & Christian Thiel 1 Received: 11 October 2016 / Accepted: 19 June 2017 / Published online: 5 July 2017 # The Author(s) 2017. This article is an open access publication Abstract Purpose We are interested in what policy insights can be transferred from EU countries that have been most successful in introducing EVs to those that are debating policy options. As we use a model to explore this, we are also interested in the application of modelling, seeking to understand if real world policies and results can be replicated in a model and, more generally, the challenges to the use of modelling in policy appraisal. Methods We use the EC-JRC Powertrain Technology Transition Market Agent Model (PTTMAM), a system dynamics model based around the interactions of conceptual market agent groups in the EU. We perform iterative scenario tests to replicate the policies carried out in the Netherlands and the UK in recent years in an attempt to achieve similar results in EV sales. We then transfer the policy scenarios to other EU member states and assess the transferability of the policies. Results Reasonable approximations of the Netherlands and UK EV policies and sales were achieved and implemented in other EU member states. Conclusion We find that the PTTMAM is fit-for-purpose and can replicate successful policies to a certain degree. Policy success is sensitive to country specific conditions, and a The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission * Gillian Harrison 1 European Commission, Joint Research Centre, Directorate for Energy, Transport and Climate, Via Enrico Fermi 2749, I-21027 Ispra, VA, Italy system dynamics model like the PTTMAM can help identify which conditions react to which policy stimulus. There are challenges to modelling in policy appraisal, such as the subjectivity of the modeller and flexibility to specific conditions, which must be kept transparent for the model to be a relevant tool for policy making. Keywords Electro-mobility . Policy Design . Transport . System Dynamics Modelling . EU 1 Introduction As part of the White Paper on Transport [1] there is the desire to significantly reduce emissions from road transport vehicles, and to eliminate all tailpipe emissions from urban areas. The European Union (EU) has introduced numerous regulations in support of this goal, including fleet emission targets [2–5] and the Alternative Fuel Infrastructure Directive [6]. The transition away from conventionally fuelled internal combustion engine vehicles towards electric vehicles (EV) forms a major part of this. Therefore a comprehensive system dynamics model of the EU light duty vehicle road transport sector was built, in order to satisfy a need to create a more sophisticated model for understanding relevant interactions and transitions than previously available. This model, the Powertrain Technology Transition Market Agent Model (PTTMAM) has been presented in previous publications [7–9]. In this paper, modelling case studies are tested against Breal-world^ passenger car Plug-in Electric Vehicle (PiEV) uptake. PiEV are a subcategory of EV that includes only Battery Electric Vehicle (BEV) and Plug-in Hybrid Electric Vehicle (PHEV). Due to the timescale of this paper Fuel Cell Vehicles are not directly considered. This exercise addresses three research questions: 1) Can the model replicate short term effects of real world 37 Page 2 of 14 policies in individual countries?; 2) What policy insights can be transferred from EU countries who have been successful in introducing EVs to others that are debating policy options?; and 3) What challenges are there to the use of modelling in policy appraisal? Question 1 relates to an extension in scope of a model that is primarily geared to analyse longer term effects of policies and market developments, and has to date only been used in studies at an EU-wide level. Question 2 is important for evidence-based policy advice that can inform future policy decisions by both the EU and individual member states. Question 3 addresses the need to qualify the model based conclusions within the context of the limitations of the chosen modelling approach. Eur. Transp. Res. Rev. (2017) 9: 37 case studies. As the EV market remains in infancy and extensive data and experience is simply not available, the model is calibrated to historical data for key parameters such as vehicle demand and component costs. At present it is difficult to capture some of the more detailed dynamics within the system or to fully replicate individual or focused (eg regional or user oriented) policies. As such, it is necessary to manually perform iterative testing of simplified policy representations to obtain model scenarios that reasonably match reality. This learning is then applied across the whole EU and discussion focuses in particular on those EU member states with less ambitious EV policies to understand if a similar success could be achieved if the case study policies were applied. The paper concludes with a summary of the policy insights and modelling challenges encountered in the study. 2 Background As discussed in previous literature [10, 11], the use of system dynamics modelling is widespread in transport studies, and in particular regarding the uptake of new and alternative fuel vehicle (AFV) technologies. Without wishing to repeat the review or discussion of previous papers, suffice to say that to date, many of these models and studies have been limited in their scope. Due to the nature of modelling a detailed focus on a specific area, with assumptions regarding aspects external to the study boundaries, is a necessity For example, system dynamics has been used to model specific regulations on automobile manufacturers in California [12], the concept of ‘willingness to consider’ a generic AFV [13], strategic niche management of AFVs [14], and the impact of infrastructure on potential hydrogen transitions in Germany [15]. However, in order to support the European Commission in their policy decisions a model that expanded on these studies was required, which can consider multiple countries, market agents and alternative technologies relevant to the complex market that exists within the EU. The EV market is still in its early stages in Europe [16]. EU member states are adopting various strategies to encourage the take up of new technologies, concerning both the vehicle and its supportive infrastructure. In this study the Powertrain Technology Transition Market Agent Model (PTTMAM), a system dynamics model implemented in Vensim™ software, is employed to generate policy insights that could support both EU-wide regulations and the (...truncated)