RheinMobil - RheinMobil - Cross-border french-german e-mobility with an economic perspective
Overview
Background & policy context:
In a 3-year cross-border fleet trial with commuters from Michelin in Karlsruhe and employees of SIEMENS in Karlsruhe, the attempt is made to prove that economic operation of the vehicles can be achieved with the right combination of electric vehicle and application profile.
Objectives:
The RheinMobil project aims to prove within three years that electric vehicles can be operated economically under cross-border conditions in specific application profiles. Downtimes will be minimised and the kilometres driven maximised by successively optimising operation, and the economic efficiency will be presented over three years. The aim of the physical-technical accompanying research is to analyse the switching potential of conventional engines to electric ones and the subsequent optimization of the energy consumption of electric vehicles in operation. In the social science part, the user expectations and experiences are condensed into insights into possible market entry barriers from which measures to increase acceptance can be derived.
Methodology:
Demonstration of commuter traffic / cross-border works' traffic:
• Developing a work shift model of different usage variants for optimal capacity utilization of the vehicles Social-science accompanying research: three-phase approach to the analysis of acceptance:
1. Eliciting expectations by in-depth interviews with future users about their requirements and expectations and short interviews with non-users (random sample) about obstacles
2. Developing and evaluating questionnaires regarding users' experiences (after about 6 months)
3. Transfer of daily routines (shortly before the project finishes) in workshops with selected user groups Physical-technical accompanying research:
• Survey and evaluation of driving profiles in conventional vehicles and energy balance of e-vehicles
• Economic analysis and impact assessment of selected technical parameters
• Analysis of deviations between calculated energy consumption and measured energy consumption to identify operating situations or styles of driving with high, above-average energy consumption and of ways to avoid these
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