Abstract for: Model-based Decision Support for Future OEM Power-train Portfolios: Academic Solutions for Practical Requirements

Meeting 21st century’s challenges of climate change and scarcity of crude oil requires the transition to alternatively powered vehicles, such as electric vehicles. As a consequence, car manufacturers have to integrate these vehicles into their product portfolios. Decisions have to be made about, for instance, the power-train to be offered in specific vehicle models and their times of introduction. This is a complex decision making task, especially due to high uncertainties about the future development of the market demand for alternatively powered vehicles. We here discuss how the application of system dynamics and agent-based simulation can contribute to manage the transition to alternatively powered vehicles from a manufacturer’s perspective. To this end, we present practical requirements on a model-based decision support and a scientifically novel simulation approach to fulfill these requirements. The simulation approach was developed in cooperation between university and industry. It integrates a system dynamics model with an agent-based discrete choice model to simulate aggregated system behavior and individual consumer choices based on industrially proved data. We show that our novel approach meets users’ requirements and can offer multiple benefits for decision making in industry. We discuss how these benefits can be exploited in future.