*6.1. Main Findings*

This paper explains and shows the main mechanisms that influence the costs of electric buses when different routes and timetables are compared. The most significant results of this paper can be summarized as:


This paper has presented a TCO model which fills a gap between the very simple cost comparisons which present one TCO for each type of bus, and the very complex bus-planning tools which can calculate the exact TCO for one specific route with all its details and its exact timetable. The presented TCO model is aimed at describing the main mechanisms which make the TCO for different type of buses vary in different ways when route properties and timetables vary. It ignores some details on purpose to make it easier to understand, for example, the reasons why one type of bus can have the lowest cost of one timetable and at the same time be more expensive than other types of buses for another timetable.

By explaining these mechanisms, this TCO model can help build a general understanding of the cost structure of electric buses. Such knowledge is important to determine what type of buses to investigate with the more detailed bus-planning tools. The TCO model can also be used to find modifications to a charging strategy which can reduce costs, or to estimate how future cost reductions in different parts of the system will influence the determination of which type of bus will be most cost effective.

The results from the TCO analysis in Section 5 demonstrate how useful this type of model is, as it shows, for example, that it is not at all sufficient to analyse the cost effectiveness of charging off-peak by only looking at its influence on the number of buses required. Reducing the number of buses was the primary motivation for such a strategy, but other effects such as a bigger battery and less driver hours will also influence how the TCO changes using this strategy.

## *6.2. Critical Assessment and Comparisons with Other Studies*

The results in this paper are theoretical but based on experiences where the authors have been involved in or lead earlier projects with electric buses (e.g., [1,7,15,20,21]). Results from testing the proposed methodology for the TCO of electric buses is well in line with these previous experiences, as well as other recent studies with comparable economic prerequisites (e.g., the Nordic countries) [22]. There are, however, some differences in results regarding the TCO of other buses when compared to studies from countries other than those in northern Europe (e.g., [23,24]). As mentioned in Section 1, electric buses can become cost competitive in about 5 years in Texas [8] and 25 years in India [9], and have twice as long pay-back time (almost six years) than diesel buses in Turkey [10]. These differences are mainly related to incentives for fossil fuels, but also the cost of drivers and maintenance personnel, as well as regional fluctuations in prices for busses and batteries. As shown in this paper, such variations in input data can, in the end of a procurement period, make a difference in terms of revenue (or loss) for a bus operator. The authors of this paper therefore stress the importance of using the model with updated prices and other data for the routes(s) if the model is used in a study for the procurement of electric bus traffic.

As for all models, it is important to know this model's limitations, and its purpose. The model should be used for more strategic investigations, such as when making general comparisons between different charging strategies or analysing what bus routes are especially good to focus on when introducing electric buses. The final decision on how to operate a certain bus route should always be based on the results of tools that are created for that purpose.
