Examining the Application Possibilities and Economic Issues of an Alternative Drive Chain in Hungary: Scenario Analysis

Abstract

Background: A societal shift in attitudes is going to be required to reduce greenhouse gas emissions in the field of transportation, which is crucial to the level of mitigation that can be achieved. There is increasing pressure on policymakers to address climate change and, in turn, to promote sustainable transport. The sector’s decarbonization is essential to meet climate change targets, and alternative powertrains, particularly battery electric trucks, can play a key role. However, international research shows that the solutions and strategic plan proposals are primarily developed in isolation according to the country’s specific conditions. Methods: This study aims to compare battery electric trucks and conventional internal combustion engine trucks in Hungary, focusing on the total cost of ownership over ten years. Results: This study examines the cost parameters for operating electric and conventional trucks, based on current economic conditions. In addition, alternative studies have been carried out to see what additional savings can be expected by changing the parameters under consideration. This research examines four scenarios that model changes in state subsidies, tolls, and excise duties alongside current cost parameters. Conclusions: The results suggest that public policy interventions play a key role in developing sustainable transport systems, particularly to preserve the competitiveness of small and medium-sized enterprises.

1. Introduction

Reducing greenhouse gas (GHG) emissions from the transport sector is essential in the fight against climate change. Alternative powertrains, particularly electric vehicles, are gaining attention as a more sustainable alternative to conventional internal combustion engines. Transport accounts for almost 30% of GHG emissions in Europe; in contrast to other sectors, emissions have not decreased here over the past 35 years. The GHG emissions of the European transport sector exceeded 1 billion tonnes of carbon dioxide (CO₂) equivalent in 2022, with road transport contributing around 70%, of which the heavy-duty vehicles (HDVs) segment is responsible for 19% [1]. Hungary and the European Union (EU) Member States are faced with different infrastructure and economic issues related to alternative propulsion. In many cases, solutions and strategic plans are developed in isolation, according to the specific conditions of each country. This research examines the operating cost parameters of electric and conventional trucks in the next ten years, starting from today’s known parameters.

Several scenarios for alternative powertrains are expected to be realized in the next ten years. The uptake of electric trucks could continue, especially if battery costs can be reduced while increasing battery efficiency through technological improvements. In addition, the expansion of charging infrastructure and the integration of renewable energy sources will be key [2]. Alternative fuels (AF) such as hydrogen and biofuels can also significantly decarbonize the transport sector. However, economic and infrastructural challenges remain, which must be addressed if the transition is to be successful [3].

In order to correctly map the situation in Hungary, it is essential to be aware of the transport policy environment in which, among other things, freight transport companies have to operate. The EU has already set a primary target for a significant reduction in GHG emissions and is now helping its Member States to achieve the first milestone of reducing GHG emissions by at least 55% by 2030 compared to 1990 levels through several packages of measures, legislative proposals, and legislative amendments [4]. Even more urgently, starting in 2026, road transport will be covered by the Emissions Trading System (ETS), which will focus on upstream fuel distributors and make fuel producers responsible for compliance. Thus, the proposal will place a payment burden on polluters, encourage the use of cleaner fuels, and reinvest the proceeds in clean technologies. These efforts will substantially impact the competitiveness of SMEs, even in the short term, which lack the expertise to identify development opportunities and the capital to implement innovations [5,6].

This study endeavors to explore comparative aspects of the total cost of ownership (TCO) of battery electric trucks (BETs) and their conventional counterparts with internal combustion engine trucks (ICETs) counterparts. This analysis is designed to uncover the main challenges that BETs face in Hungary and to formulate policy recommendations that can help SMEs position themselves in the transport sector in the challenging period ahead. This study provides an analysis of HDVs that cover an average distance of 520 km per day. Four conditions have been assessed: firstly, by calculating the cost data known in December 2024; secondly, by examining the role of public intervention in subsidies and excise duty change margins; and last but not least, by examining the role of tolls. These areas and measures could catalyze the use of BETs, including in Hungary, where there is a large TCO gap between BETs and diesel trucks.

2. Literature Review

Reducing carbon emissions from trucks is critical to creating sustainable road freight transport systems worldwide, so mapping the current situation and long-term analysis are integral to the current research [7]. Based on an emissions analysis of conventional diesel trucks and potentially zero-emission trucks, including natural gas, battery electric vehicle (BEV), plug-in hybrid electric (PHEV), hydrogen fuel cell, and well-to-wheel, the GHG emissions of China’s total road freight transport were analyzed under four scenarios up to 2035. The four scenarios were based on the baseline: policy facilitation (PF), technology breakthrough (TB), and a combination. The results show that the TB and PF-TB scenarios could reach the carbon peak by 2030 with GHG emission reductions of 0.13% and 1.5% per year, respectively. In contrast, with the baseline and PF scenarios, the carbon emission reduction targets cannot be achieved as they focus only on the number of zero-emission trucks and do not limit energy GHG emission factors, ignoring energy efficiency improvements in trucks, resulting in total emissions increased by 29.76% and 16.69%, respectively, compared to 2020 [8].

In addition to road transport, China has also carried out a complex analysis of the potential for reducing carbon emissions across all transport modes. This was overtaken by analyzing historical data on freight transport activity between 2007 and 2019. The three drivers of carbon emissions from the freight transport system were examined, and it was concluded that the electrification of rail and freight transport will contribute to the downward trend in carbon emissions by 2024. As a first step, they assessed the current situation, identifying the three main internal drivers: the share of rail freight, the level of rail electrification, and the level of uptake of electric vehicles. The results show that in 2030 if the three main drivers defined as 23.96% of total freight transport, 83.7% of rail freight transport, and 11% of road freight transport account for the three main drivers, the Chinese freight transport system has the best and most optimal scenario in terms of carbon peak [9].

As in China, Uruguay has analyzed the possible outcomes for GHG reduction in the vehicle fleet. To this end, three future scenarios were set up in which different alternative powertrain technologies, such as BEVs and fuel cell electric vehicles (FCEVs), are implemented at different rates. Future scenarios indicate that significant reductions in greenhouse gas and ozone precursor emissions can only be realized through the implementation of targeted policies and regulatory frameworks [10]. In addition, it is essential to underline that today, the investment costs are much higher than conventional ones, and the development of changing infrastructure requires significant investment, so market conditions in different countries may be different depending on their level of development [11].

Regulating taxation and road user charging systems constitutes one of the most effective policy instruments to accelerate the transition toward zero-carbon road freight transport [12]. In a study involving European countries, the relative cost-competitiveness of five different alternative commercial vehicles was examined in terms of the total cost of ownership (TCO), looking for correlations between low and zero emissions [13]. The results show that in some application segments and European countries, the cost competitiveness of low or zero-emission drive technologies is already evident but may not be the most effective or the most appropriate policy instrument for the sector. At the same time, the optimal use of conventional leverage, even regarding route optimization, should not be overlooked, which will also support sustainability objectives [14].

In China, the environmental and economic performance of diesel, hybrid electric, and PHEVs with different hybridization factors and battery capacities was analyzed, comparing whole-life carbon emissions and total cost of ownership from 2020 to 2040. Scenario analysis was used to explore the impact of grid composition, diesel, charging prices, and battery energy density, and the sensitivity of driving distances from 100 km to 800 km was investigated [15]. The results show that hybrid electric trucks with high hybridization factors are the most promising currently on the Chinese grid when considering charging time and battery price. Decoupling economic growth from resource use (decoupling) should be achieved in line with climate goals so that individuals and regions are not the losers of the transformation and, where possible, the social perception of the transformation is positive [16]. The role of transport policy in the context of the EU and the schemes that support and promote environmental sustainability are presented below.

The future deployment of electric cars and trucks is likely to generate significant environmental and economic benefits. However, existing research and practical experience remain limited on the operational characteristics of 100% deployment of these vehicles, and therefore, manufacturers are investing many resources in R&D activities [17]. The European Union has set a target for newly registered HDVs to emit 30% less carbon dioxide by 2030 than in 2019 [18]. Taking the transport sector into account, a quarter of air pollution from this sector is related to freight transport. However, HDVs account for only 5% of all vehicles in transport [19]. The following EU ambitions are summarized in

Table 1. Summary of incentive measures relevant to the research.

Incentive Measures	Established	Scope	Main Goals	Main Points Affecting Transport
Paris Agreement [20]	2016	2050	Action plan to limit global warming.	Develop comprehensive and transparent transport policy objectives for the long term.
Sustainable Development Goals [21]	2015	2030	The world’s countries have jointly committed to eradicating poverty, finding sustainable and inclusive development solutions, ensuring human rights for all, and, in general, catching up with the countries lagging by 2030.	Three action points that affect transport: Affordable and clean energy; Clean energy, clean energy, and renewable energy; Sustainable cities and communities.
White Paper: Roadmap to a Single European Transport Area [22]	2011	2020	Preparing the European transport area for the future, developing a competitive and sustainable transport system, and defining strategic actions.	Creating a well-functioning Single European Transport Area, connecting Europe through modern, multimodal, and safe transport infrastructure networks, moving towards sustainable mobility, including reducing other negative externalities of transport. It includes ten specific objectives to make the transport system more competitive and resource-efficient.
A clean planet for all [23]	2018	2050	A long-term strategic vision for a prosperous, modern, competitive, and climate-neutral economy, similar to the White Paper.	Consider legislation to improve the CO2 efficiency of cars, vans, and HDVs.
EU Mobility Strategy 2020 [24]	2020	2050	Reducing emissions; creating and operating a smart, competitive, safe, accessible, affordable transport system.	Various milestones for 2030, 2035, and 2050, such as almost all cars, vans, buses, and new HDVs becoming zero-emission, doubling rail freight, or even using maritime and large aircraft for transport becoming zero-emission.
Fitt for 55 [25]	2022	2050	Reduce CO2 emissions by 55% by 2030 and reach zero by 2050.	Three main areas for action: AFI; FuelEU Maritime; ReFuelEU Aviation.

, which could significantly impact the transport sector, including freight transport, in the future.

The table clearly shows that the various regulations and package measures all set the unanimous goal of creating sustainable transport systems to reduce CO₂ emissions to zero or even below zero by the middle of the 21st century. The use of alternative powertrain technologies constitutes a viable and potentially impactful alternative [26].

However, to ensure that, among other considerations, SMEs can assess the viability of undertaking such a substantial investment and technological transition in the future, it can prove to be beneficial to explore the TCO parameters associated with each option. A 2021 study sought to explore how the components of total cost of ownership (TCO) might evolve with the adoption of battery electric trucks (BETs) and internal combustion engine trucks (ICETs), considering both current technological advancements and projected future developments. This analysis focuses on changes in diesel and electricity prices and how specific cost parameters (taxes, servicing costs, etc.) might change over time in seven European countries [27]. The analysis of scenarios concluded that BETs could achieve total cost of ownership (TCO) parity with diesel trucks in Europe within the current decade, even without additional policy support. However, significant differences can be observed between countries in the timing of this achievement, mainly due to differences in electricity and diesel prices, road pricing, and current policy measures.

Similarly to the previous one, a study in 2024 also looks at how AF could help reduce GHG emissions in the EU in the future and how this could be achieved, analyzing several scenarios. The study concludes that BEVs offer the most promising solution for decarbonizing EU road transport. However, looking at another alternative, the so-called electric road system (ERS), could significantly accelerate the transition by reducing battery capacity requirements and facilitating vehicle retrofitting. Nevertheless, the EU road transport sector is likely to exceed its fair share of global GHG emissions unless further interventions are made [28].

However, their mass deployment still raises many questions for the future, both for passenger and freight transport. With this in mind, several scenarios have been sketched out below, using an econometric tool, to illustrate the main operating parameters and values under which heavy goods vehicles in freight transport can operate economically based on current knowledge.

3. Research Method

Following a review of the international literature, a proprietary calculation method based on economics was developed to compare different scenarios over a 10-year time horizon. The tool used is discounting, whereby different scenarios have been constructed to discount the present value of the future impacts to the present value, thus making it possible to compare the costs at different points in time. It provides a practical answer to whether a project is worth pursuing [29], see Equation (1).

$$\mathrm{NPV}={\sum }_{i=1}^N{\displaystyle \frac{CF}{{(1+r)}^i}}$$

(1)

where

• NPV discounted present value of the cumulative discounted present value of future costs;
• CF the total costs incurred in a given period;
• C₀ the amount of money invested at date 0;
• r the interest rate, which expresses the cost of the capital investment and takes account of the risk of non-payment;
• N the number of years taken into account for discounting;
• i current year taken into account;
• used discount rate: 3%.

To prepare the scenarios, the aspects in Figure 1 were considered for ICETs and BETs from purchase through operation and carbon emissions.

Accordingly, four scenarios were constructed, as detailed in the following sections. The current situation was mapped as a starting point, with the cost elements available today. The source of each parameter can be found in Appendix A.

This research has limitations and can be interpreted in several ways, primarily because this study is based on a scenario analysis based on future economic and technological assumptions. The price, lifetime, and efficiency of BET batteries can significantly affect TCO, and the model does not consider future technological breakthroughs. Moreover, the adoption of battery electric trucks (BETs) is heavily contingent upon the availability of charging infrastructure, which remains underdeveloped in Hungary. The model does not consider the costs and time needed to develop the infrastructure, as the vehicles used were explicitly analyzed from the perspective of SMEs and business operations, thus limiting the scope of the research.

The initial parameters were drawn from the literature or publicly available databases as of 1 December 2024. After the baseline was examined, three possible scenarios were investigated based on the data projected in the literature review. Accordingly, the following three aspects were changed for each scenario:

• State aid rates for BETs;
• Changes in road tolls;
• Changes in excise duties.

The parameters used in the calculation are shown in

Table 2. Parameters used to build the scenarios.

Examined Parameters	Scenario Zero	Scenario 1	Scenario 2	Scenario 3
Purchase a diesel truck	95,000 EUR	95,000 EUR	95,000 EUR	95,000 EUR
Purchase an electric truck	200,000 EUR	200,000 EUR	200,000 EUR	200,000 EUR
Maintenance for a diesel truck	10,000 EUR/year	10,000 EUR/year	10,000 EUR/year	10,000 EUR/year
Maintenance for electric truck	6600 EUR/year	6600 EUR/year	6600 EUR/year	6600 EUR/year
Number of working days	250 days/year	250 days/year	250 days/year	250 days/year
Average distance traveled per day	520 km/day	520 km/day	520 km/day	520 km/day
Price elasticity for diesel	2%	2%	2%	2%
Price elasticity for electricity	2%	2%	2%	2%
Fuel consumption	32 L/100 km	32 L/100 km	32 L/100 km	32 L/100 km
Electricity consumption	1440 Wh/km	1440 Wh/km	1440 Wh/km	1440 Wh/km
Fuel price	1.7 EUR/L	1.7 EUR/L	1.7 EUR/L	2.5 EUR/L
Electricity price	0.26 EUR/kWh	0.26 EUR/kWh	0.26 EUR/kWh	0.3 EUR/kWh
Toll diesel truck	0.5 EUR/km	0.5 EUR/km	1 EUR/km	0.5 EUR/km
Toll electric truck	0.3 EUR/km	0.3 EUR/km	0 EUR/km	0.3 EUR/km
Toll elasticity of diesel	10%	10%	10%	10 %
Toll elasticity of electricity	3%	3%	- %	3%
The government supports electric trucks	0 EUR	105 000 EUR	0 EUR	0 EUR
CO2 emission diesel truck	900 CO2 g/km	900 CO2 g/km	900 CO2 g/km	900 CO2 g/km
CO2 emission of electric truck	204 CO2 g/kWh	204 CO2 g/kWh	204 CO2 g/kWh	204 CO2 g/kWh
CO2 external price	80 EUR/tons	80 EUR/tons	80 EUR/tons	80 EUR/tons
CO2 external price elasticity	3%	3%	3%	3%

.

In the first scenario, a single variable was modified: the state aid rate applicable to electric trucks. The calculation with this parameter was considered necessary because the literature review showed that using different types of state subsidies is one of the best motivating factors for the uptake of alternative propulsion systems. In the second scenario, the assumption that electric vehicles would be exempt from tolls for the next decade—while tolls for diesel vehicles would rise substantially—was nearly doubled. This parameter is also a critical transport policy tool for policymakers. The third scenario shows the parameters used, where two changes have been made, one for diesel and one for electricity. In this case, the assumption is that the State, by changing the excise duty value, influences consumer prices and, thus, demand in an attempt to favor alternative propulsion. After outlining the parameters, the concrete results are presented below.

4. Analysis of Electric and Conventional Propulsion Operation over Ten Years

4.1. Scenario Zero: Current Situation

The zero scenario includes the cost parameters available and current in Hungary on 1 December 2024, which were used as the basis for the discounting. Figure 2 visualizes the summary of the 10-year discounted values by cost parameter.

Fuel and tolls are the most oversized items for diesel trucks, while the purchase cost dominates for electric vehicles. The graph shows that the overall cost of electric vehicles is lower, but the initial investment is significant. The evolution of the total costs is shown in Figure 3.

This line graph shows the evolution of costs over time. The costs of diesel vehicles are consistently higher, while electric vehicles follow a flatter curve, reflecting lower running costs in the longer term.

4.2. Scenario 1: Evolution of Procurement Costs with State Aid

In the case of the first parameter, the level of state aid has been increased, so the investment cost of ICETs and BETs is the same. Figure 4 shows the resulting aggregated cost parameters.

Figure 5 shows the projected values over ten years for the first scenario.

State aid is expected to equalize the acquisition costs of electric and diesel vehicles. The figures show that this leads to a significant cost reduction for electric vehicles, especially in the early years. The cumulative costs are thus even more favorable than in the base case.

4.3. Scenario 2: Changes in Tolls

The next step was to change the level of tolls from the baseline for the future, as literature research and incentive schemes in some European countries have shown that one of the potential cost parameters to encourage early switchover is to reduce or eliminate them. Figure 6 shows the aggregated cost parameters for the second scenario.

Figure 6 shows that if the toll for BETs is entirely waived from 2024 onwards, and the toll for ICETs is also increased, this will have a positive effect on the incentives for BETs in the long run, costing more than EUR1,600,000 less than conventional trucks over the ten years. Figure 7 shows the projected values over the years as in previous scenarios.

Based on the evolution of costs over time, electric vehicles are clearly on a more favorable trajectory, particularly due to the absence of tolls. Following the change in the toll, excise duty was examined.

4.4. Scenario 3: Changes in Excise Duties

The fluctuation in fuel prices led to an increase in the value of diesel, which in turn facilitated a transition toward greener technologies. Additionally, this shift resulted in a marginal rise in the value of electricity. The main reason is that if the uptake of electrified vehicles increases, there will be less demand for conventional fuels, thus reducing government revenues. Taxes may change not only to encourage the switchover but also to reduce the resulting revenue loss. As shown in Figure 8, the more than eightfold increase in the price of diesel and electricity over the next ten years makes it much more affordable to run a BET.

Increases in the price of diesel and electricity have less impact on the cost differential. Figure 9 shows the evolution of total costs over the ten years.

The line graph shows that the evolution of the costs is almost parallel, so the change in excise duties alone is insufficient to ensure an economic advantage for BETs.

4.5. Sensitivity Analysis

In addition to calculating the NPV, it is a standard corporate practice to include sensitivity analyses measuring the sensitivity to changes in specific parameters of the investment project as an integral part of corporate economic analyses and reports. In the sensitivity analysis, the parameters examined were not changed separately; only the additional parameters were used for each scenario. In each case, one unit was adjusted positively to perform the sensitivity analysis. The absolute value of the data was then used to determine which parameter caused the most significant deviation from the baseline in each case. This is shown in Figure 10, Figure 11, Figure 12 and Figure 13.

From the sensitivity analysis of the scenarios, it can be seen that the ‘Fuel consumption’ causes the most significant deviation. This suggests that the economics of vehicle operation are most influenced by fuel efficiency and that technological advances may be a key factor in the future. A further important factor is the economic environment, which is reflected in the values of price elasticities. A comparative synthesis of the scenario results is provided in the following section.

5. Summary

The results show that electric trucks have a more favorable long-term cost trajectory, especially if the State subsidizes their purchase or abolishes tolls. The findings indicate that electric trucks exhibit a more advantageous long-term cost trajectory, particularly in scenarios where government subsidies support their acquisition or tolls are eliminated. The most significant savings can be achieved through changes in tolls, while changes in excise duties alone cannot stimulate technological change. This research answers the question of which economic policy instruments could effectively promote the uptake of zero-emission vehicles.

The relevance of the parameters studied lies in the fact that they are the most important cost factors influencing business decisions. The model may benefit the SME sector, for whom cost efficiency is a key issue. The research results can inform transport policy decisions and accelerate the uptake of sustainable transport solutions.

Table 3. Comparison of scenarios (EUR).

	Comparison
Current situation
	Diesel	Electric	Difference	% difference
Fuel	848,170	583,740	264,429	145%
Purchase	127,672	268,783	−141,111	48%
Service	117,778	77,733	40,045	152%
Toll	835,612	471,944	363,668	177%
CO2	113,267	36,970	76,296	306%
Total	2,042,499	1,439,171	603,327	142%
Evolution of procurement costs with State aid
	Diesel	Electric	Difference	% difference
Fuel	848,170	583,740	264,429	145%
Purchase	127,672	127,672	-	100%
Service	117,778	77,733	40,045	152%
Toll	835,612	471,944	363,668	177%
CO2	113,267	36,970	76,296	306%
Total	2,042,499	1,298,060	744,439	157%
Changes in tolls
	Diesel	Electric	Difference	% difference
Fuel	848,170	583,740	264,429	145%
Purchase	127,672	268,783	−141,111	48%
Service	117,778	77,733	40,045	152%
Toll	1,671,225	-	1,671,225	-
CO2	113,267	36,970	76,296	306%
Total	2,878,111	967,227	1,910,884	298%
Changes in excise duties
	Diesel	Electric	Difference	% difference
Fuel	1,247,309	673,547	573,762	185%
Purchase	127,672	268,783	−141,111	48%
Service	117,778	77,733	40,045	152%
Toll	835,612	471,944	363,668	177%
CO2	113,267	36,970	76,296	306%
Total	2,441,638	1,528,978	912,660	160%

shows the aggregated costs of the four states over ten years.

The data show that electric vehicles have a lower total cost in all cases, especially in the abolition of tolls, where the savings are close to EUR1.9 million. State aid also makes a significant difference of more than EUR740,000, although this shows the most minor difference. The table demonstrates that direct financial incentives and regulatory interventions play a key role in increasing the economic competitiveness of electric drives and that their effects are most pronounced during operation and in the longer term. Figure 14 shows a visual comparison of each scenario of the total costs.

We can conclude in several areas if we look at the research findings from the policy-making perspective. The model suggests that the most effective incentive is toll reimbursement or exemption for BETs. Toll increases for diesel vehicles and toll exemptions for electric vehicles could lead to a rapid payback. High-capacity charging stations along logistics centers, industrial parks, and motorways are essential to achieve this.

6. Discussion

In the transport planning process, decision-makers need reliable and informative assessments to help them compare different options and determine whether a proposal is worth bringing to society or policymakers. They must recognize the financial constraints essential for making a rational decision. The literature review shows that using different drive chains will be a priority for developers, policymakers, economists, and users in the period ahead. The study analyses four scenarios: the current situation, the cost of acquisition reduced by state aid, changes in tolls, and changes in excise duties. The model also considers the purchase price, maintenance costs, fuel or electricity consumption, tolls, and the external costs of CO₂ emissions of vehicles. The most significant cost savings can be achieved by abolishing tolls and state subsidies. A switch to electric vehicles may be justified by the fact that, with the expected revision of the tolling system in 2027, the operation of conventional vehicles is likely to represent a significant additional cost compared to the 2024 introduction, in line with the motivation and urgency represented by the climate targets. However, in addition to the operating costs, the underdeveloped charging infrastructure and limited range in Hungary are, in practice, a significant obstacle to everyday operational use and may also be an indirect cost factor, which has further research potential.

Overall, the study answers important questions from economic and environmental perspectives and fits well with the EU’s climate objectives. The research methodology and results can be applied in other countries, especially where decarbonization of the transport sector is on the agenda. Developing synchromodal networks is aimed at increasing resilience in addition to the efficiency and sustainability of supply chains. This can allow a small business to fulfill first and last-mile transport tasks as part of a well-organized transport data community. In this respect, the limited range of electric vehicles will become less and less of an obstacle and limiting factor for the effective operation of a business, as the proportion of long-distance transport tasks is expected to decrease and be replaced by collection and distribution services, carried out with high efficiency, careful and accurate planning. Competitive advantage for operators could be gained by being at the forefront of such initiatives with appropriately sized fleets, which could provide further perspectives as a continuation of this research.