Better mental model, fewer watt-hours? Effects of ecodriving tips on knowledge, action regulation, and driving performance in battery electric vehicles

Abstract

Supporting users in avoiding waste of valuable resources like energy is a key objective in optimising system design. Particularly in battery electric vehicle (BEV) operation, energy efficiency depends on driver behaviour, i.e., on adequate understanding of energy dynamics. Building on the theoretical relevance of know-how and know-why knowledge (e.g., in the form of mental models) for successful action regulation, this study examines how ecodriving tips can be communicated efficiently and what depth of information is required. Specifically, we investigate whether compact, generic tips suffice, or whether psychologically structured information–linking action instructions with system rationale–more effectively support ecodriving. In a field experiment, participants (N = 50) drove an 11 km urban route comprising multiple energy-relevant driving situations in a Nissan LEAF BEV. Participants were randomly assigned to receive either (G1) no tips, (G2) compact generic tips, or (G3) psychologically comprehensive tips integrating action guidance with explanatory rationale (know-how-and-why). Contrast analyses revealed a consistent linear trend across groups, indicating gradual improvements from G1 to G3. Participants in G3 demonstrated the lowest energy consumption (–11.3% vs. G1), more moderate and stable throttle use, and the most consistent velocity. They reported the highest perceived support for action regulation and the mental model, along with the largest gain in perceived ecodriving knowledge. These findings highlight the importance of aligning information structure with cognitive needs. Implications concern cognitively aligned in-vehicle support systems and scalable interventions for driver education and sustainable transport.