Nicolas Posso

Battery electric vehicles (BEVs) are a key technology for reducing CO₂ emissions from the transport sector, but their large-scale adoption may strain the current electricity grid. Smart charging (SC) can complement BEV uptake by optimizing charging according to grid constraints, renewable energy availability, and user preferences. Despite their potential, both technologies exhibit low adoption rates, making it important to understand consumers' preferences. I analyse preferences for BEVs and SC in France using two discrete choice experiments conducted in early 2024 with a sample of 2,380 individuals. Latent class models are used for the estimations. I identify three classes for BEV preferences and four classes for SC. Regarding BEVs, driving range is the most important attribute for the reluctant class, charging time for the keen class, and purchase price for the neutral class. For SC, charging speed is by far the most critical attribute across most groups.  Across both technologies, preferences are significantly aligned—with over 56% of individuals occupying corresponding sentiment classes across both choice experiments—and class membership is consistently predicted by demographic factors such as age, educational level, and urban residence.