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Evaluating Sustainable Transport Options: E-Buses in Wilder Keiser Tourism region

Evaluating Sustainable Transport Options: E-Buses in Wilder Keiser Tourism region banner
Evaluating Sustainable Transport Options: E-Buses in Wilder Keiser Tourism region
Published at 24 January 2025 | Austria

General details

EDIHs involved

Customer

EDIH logo
Customer type: SME
Customer size: Micro (1-9)

Services provided
Test before invest
Technologies
Mobility
Sectors
Travel and tourism

Challenges

An image of one of the buses in the region.© Mathäus GartnerThe Wilder Kaiser tourism region is planning to adopt sustainable and electric mobility solutions to improve tourist access to key destinations, such as mountain railways and alpine areas, throughout both winter and summer seasons. To support this initiative, Kufstein mobil, a regional competence centre that aims to support mobility transition, required of a comprehensive scenario analyses of the region to evaluate the feasibility and potential of using electric buses for ski and hiking transport.

The feasibility analysis will focus on several key aspects:

  • Vehicle Selection: Developing recommendations for selecting electric buses that meet the specific demands of the Wilder Kaiser region.

  • Route Optimisation: Identifying the most efficient and accessible routes for electric bus operation.

  • Charging Infrastructure: Assessing requirements for charging infrastructure, including potential station locations, opportunities to leverage existing facilities, and synergies with local energy communities.

  • Economic and Operational Analysis: Evaluating energy solutions, performing life cycle cost analyses for both vehicles and charging infrastructure, and assessing overall economic viability.

The insights gained from this study will enable the region to implement effective and sustainable mobility solutions, catering to the growing demand for eco-friendly tourism experiences. Moreover, these findings will serve as a foundation for launching a tender to procure e-buses for the Wilder Kaiser region.

Solutions

Salzburg Research, coordinator of EDIH Crowd in Motion, developed a scientific consumption model to estimate the maximum energy usage of e-buses on proposed routes in the Wilder Kaiser region. To achieve this, buses in the region were equipped with specialized loggers to record GNSS data. Real driving data collected in March and April 2024 underwent quality verification and was aligned with a road graph (GIP). Collaborating with Kufstein mobil, Salzburg Research established necessary assumptions to refine the consumption model, enabling scenario-based evaluations for e-bus deployment in the region.

Economic Feasibility Analysis

For assessing economic feasibility, a dynamic present value calculation tool—developed by e7, a project subcontractor—was used. This tool adheres to the ÖNORM M 7140 standards for comparative energy system analysis and integrates detailed cost parameters for both e-buses and the required charging infrastructure. Key cost considerations included:

  • Investments: Bus and hardware purchases, subsidies.

  • Operational Costs: Charging and fuel expenses.

  • Maintenance Costs: Insurance and network fees.

To enhance the accuracy of these cost assumptions, data was collected through direct interviews with key local stakeholders such as the bus operator Ledermair, municipal services in Steyr, Kufstein municipal utilities, and TINetz. Additionally, direct discussions with e-bus providers refined the cost and performance assumptions for the vehicles.

Alignment with Sustainability Goals

This structured approach provided a reliable foundation for data-driven decision-making in e-bus adoption, aligning with the region's environmental and tourism goals. Public investments supported initial infrastructure, while private funding focused on operational costs under a financial sustainability model. This initiative marks a significant step toward the Wilder Kaiser region’s sustainability objectives.

Results and Benefits

Maximum daily energy consumption per vehicle for the lines eligible for electrification (summer and winter lines) in the Wilder Kaiser region for the “charging outside the Wilder Kaiser region” scenario © Salzburg ResearchSalzburg Research assisted Kufstein mobil by conducting a potential analysis to evaluate the maximum daily mileage and energy consumption of e-buses across 31 routes, segmented into winter and summer paths. Two scenarios were considered: a "maximum variant," reflecting peak energy consumption due to high-demand components like air conditioning, and a "normal variant," representing average operational conditions. The analysis also assessed charging scenarios, comparing options for charging within the Wilder Kaiser region or at depots outside the region (e.g., in Kufstein), and evaluated different battery capacities.

The findings identified which routes could be covered with a single battery charge and which would require interim charging under each scenario, providing a clear framework for efficient route planning. A comprehensive market overview of current e-bus models was also developed to aid bus companies in streamlining their procurement processes.

Winter and summer bus routes analyzed. © Salzburg Research

Charging strategies, including depot charging and opportunity charging, were analysed, resulting in recommendations for optimal charging infrastructure locations and power requirements. Initial profitability calculations compared the costs of diesel and electric buses, projecting an economic advantage for e-buses within 7 to 17 years, depending on cost variables.

This analysis significantly enhanced the digital capabilities of both Salzburg Research and its customer, Kufstein Mobil, enabling precise energy and financial forecasting while optimising sustainable transport planning. With this framework, the customer can plan routes based on concrete data for energy consumption and charging requirements, facilitating informed decisions about infrastructure investments and operational efficiency. Bus companies benefit from data-driven procurement guidance, accelerating the transition to e-mobility with clear economic projections and a streamlined decision-making process.

Moreover, the solution is scalable and adaptable for other regions, as the developed consumption model can be used to evaluate e-bus implementation elsewhere. This flexibility positions the model as a valuable tool for advancing sustainable transit solutions on a broader scale.

In addition to allocating staff resources (time), the customer invested approximately €6,000 for an economic calculation subcontract to support this service. This investment underscores their commitment to a future-oriented approach, fostering the shift toward sustainable and economically viable transport systems.

Perceived social/economic impact

The implementation of the scientific consumption model for e-bus energy usage in the Wilder Kaiser region offers substantial social and economic benefits. By enabling precise forecasting of energy consumption and operational costs, the model supports the transition to electric mobility, significantly reducing greenhouse gas emissions and improving air quality. This shift aligns with environmental sustainability goals, enhancing regional livability and creating a cleaner, quieter environment for residents and visitors.

Economically, the model empowers authorities and transport operators to make informed decisions about infrastructure investments. The dynamic present value calculation tool allows stakeholders to compare long-term costs of electric versus diesel buses, projecting economic advantages for electric buses within 7 to 17 years. Savings in fuel and maintenance costs can improve operational budgets and profitability for local bus companies. Additionally, precise data on energy consumption and charging needs facilitates route optimization, reducing delays and improving service reliability, which encourages public transport use.

Stakeholder collaboration has been essential to the project’s success. By working with local authorities, operators, and residents, the model reflects real-world conditions and fosters community support. As the benefits of cleaner, more efficient transport become evident, public acceptance of e-mobility is expected to grow.

While the model provides critical insights, challenges remain. Seasonal data constraints during late winter complicate peak-season projections, and future adaptability is needed to address evolving driving patterns. Nonetheless, the project lays a strong foundation for sustainable transportation in the Wilder Kaiser region.

Measurable data

Maximum daily energy consumption per vehicle for the lines eligible for electrification (summer and winter lines) in the Wilder Kaiser region for the “charging outside the Wilder Kaiser region” scenario (i.e. charging outside the region would be possible, for example, in a bus depot in Kufstein). Comparison of “normal variant” (= dark bars) vs. “maximum variant” (= light bars). The vertical lines show the battery capacities of three different e-bus types.  Maximum daily energy consumption per vehicle for the lines eligible for electrification (summer and winter lines) in the Wilder Kaiser region for the “charging within the Wilder Kaiser region” scenario. Comparison of “normal variant” (= dark bars) vs. “maximum variant” (= light bars). The vertical lines show the battery capacities of three different e-bus types. 

DMA score and results - Stage 0

The organisation has already achieved an average level of digital maturity, however there are still improvements to be made. Precisely, additional investments in digital technologies and skills to improve operations and products. A number of mainstream technologies are used already, however adopting Information Management Systems, e-commerce, social networks, or AI is worth considering. The personnel obtain an average level of digital skills, however in order to advance in digital transformation, a well-planned training and IT professionals are crucial. Although a lot of business information is already in a digital form, the company would benefit a lot from a comprehensive data strategy, including data security, providing Kufstein Mobil with increased data analytics capacities and would support high-level decision making. ICT technologies could also be adopted to help become more sustainable in the company`s operations. Such changes would lead to increased competitiveness and bring the company closer to more digital mature competitors in their respective market. 

Lessons learned

The development of a scientific consumption model to estimate e-bus energy usage in the Wilder Kaiser region yielded critical insights for Salzburg Research and Kufstein mobil:

  1. Effective use of real driving data
    The integration of GNSS-based real driving data for quality verification ensured the consumption model's accuracy and reliability.

  2. Stakeholder collaboration and agreement on assumptions
    Close collaboration with Kufstein Mobil and other regional stakeholders was instrumental. The mutual agreement on foundational assumptions strengthened the model’s validity and aligned it with local operational realities.

  3. Economic feasibility
    A robust economic feasibility analysis was developed by combining stakeholder insights with data from e-bus providers. The dynamic present value calculation tool, developed by e7, enabled the evaluation of operational and infrastructure costs, ensuring alignment with the project’s sustainability objectives.

Despite these successes, several challenges were identified:

  1. Model adaptability
    The model may face limitations in adapting to future changes in driving patterns or energy consumption requirements. Assumptions regarding energy usage during peak conditions need to be revisited as more operational data becomes available.

  2. Charging infrastructure
    While the analysis of various charging strategies was beneficial, it revealed the need for a more thorough exploration of infrastructure requirements, including the identification of optimal charging locations and power needs.

  3. Seasonal and operational data constraints
    Data collection occurred during March and April 2024, at the end of the winter season, when timetables were thinned or journeys were not conducted as scheduled. This introduced challenges in extrapolating data for peak season operations.

  4. Data quality and route assembly complexity
    Ensuring the quality of the collected data and assembling it into coherent bus routes proved to be a complex and resource-intensive process.

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