Climate urgency, bad air quality and energy dependency are all concerns that highlight the current road transportation system limits. These concerns originate from the dominance of the internal combustion engine vehicle (ICEV) technology and its detrimental side effects on the society. Moving from the ICEV technology is necessary if we want to achieve a more sustainable system. With this in mind, the European Union formulated the ‘Fit for 55’ plan, which includes a 100% reduction of greenhouse gas emission target by 2035 for cars and vans. The best candidate technology to replace ICEVs by 2035 is the battery electric vehicle (BEV) technology, since these vehicles emit zero emissions while being driven and are widely available to the general public. However, there still exist barriers that hinder the majority of the Belgian consumers to adopt this technology, namely the high vehicle purchase price and the lack of public charging infrastructure. Therefore, this thesis aims at providing an overview of the Belgian vehicle preferences andhow or when these remaining barriers can be alleviated.
Firstly, chapter 2 discusses a latent class analysis that is performed on survey data concerning the vehicle preferences of Belgian consumers in 2016 and 2020. This enables the identification of four distinct consumer classes and to discern how the preferences changed between 2016 and 2020. The results show that three classes are present both in 2016 and 2020, namely, the price-focused driver that considers the
purchase price as being the most important attribute during the choice of a new vehicle, the cost balancer that considers all costs as important and the undisturbed driver that puts the emphasis on driving range and infrastructure availability. The last class shifted from a more brand and image focused consumer to an eco-friendly driver. This shift demonstrates the growing interest of the Belgian consumer towards more sustainable alternatives than ICEVs.
Secondly, chapter 3 focuses on the lack of public charging infrastructure in the Brussels-Capital Regionby proposing two complementary approaches that suggest suitable locations for additional charging infrastructure. The first approach targets opportunity charging by suggesting to locate new infrastructure at regional points of interest to increase the networks overall accessibility. The second approach is a maximal covering location problem that aims at maximizing the coverage of building blocks that are deemed suitable given future predictions of electric vehicle uptake and by considering the layout of the electric grid. The combination of both methods result in a focus on neighbourhoods where the EV adoption of residents is expected to be higher and the increase in availability of the charging infrastructure network in the Brussels-Capital Region.
Thirdly, chapter 4 investigates the cost difference between the different vehicle technologies. The aimis to compare different vehicle technologies’ costs on an ownership base, rather than only accounting the purchase price, by using the Total Cost of Ownership (TCO) methodology. The TCO is extended in the third chapter with the Total External Cost (TEC) methodology to form a value called the Total Cost for Society (TCS). Different driving profiles were defined based on a persona representation that enabled the observation of the sensitivity between the various assumptions. The TCS results indicate that most vehicle technologies have comparable TCS values in their respective car segment for the same persona. The main parameters affecting the result between the personas are the urbanization degree (impacting the TEC) and the annual vehicle kilometers traveled (impacting both TCO and TEC).
Lastly, chapter 5 provides an overview of the change in TCO between 2015 and 2020 based on 4 TCO analyses. Furthermore, the future TCO for 2030 is predicted using a Monte Carlo simulation. The longitudinal study concludes that the fluctuations in the TCO of ICEVs were mainly determined by the fuel price, while the TCO of BEVs remained quite stable even though their battery size doubled. This last observation indicates that car manufacturers first tackled the range anxiety related to driving range adoption barrier before reducing the high purchase price. Notwithstanding the increase in driving range, the battery cost is expected to continue to decrease and will impact the future BEV purchase price and TCO. The results of the Monte Carlo simulation for 2030 indicates that BEVs will have a lower TCO compared to ICEVs with a probability of 98,64% in the medium car segment. However, the prediction is less positive for smaller city cars with a 23,53% chance of having the lowest TCO compared to petrol vehicles.
Recommendations for going further with the results presented in this thesis are discussed in the concluding chapter. This discussion includes policy recommendations on charging infrastructure and vehicle cost, as well as how to stimulate more research in the domain by providing access to some type of data. Additionally, research recommendations are also provided both concerning methodological and topical aspects.