Abstract:In this paper, we build an electric vehicle adoption model using heterogeneity in first-time PEV buyer household characteristics in California between 2012-2020. Utilizing a multi-year survey of 18,921 respondents, adopters are segmented using sociodemographic, vehicle fleet, and land use characteristics through latent class analysis into eight clusters. Single-vehicle households are split between Lower-Income Old Families, Lower-Income Young Renters, High-Income Families, and Mid/High-Income Young Renters. Multi-vehicle households include High-Income SUV Families, Middle-Income Young Renter, Mid/HighIncome Old Families, and Mid/High-Income Rural Truck Families. After classifying the population into these segments, we fit Bass diffusion models to create a PEV adoption forecast meeting the 100% ZEV new car sales goal by 2035. We find Rural Truck Families, Lower-Income Old Families, and Lower-Income Young Renters, which together represent almost half of the population, are adopting PEVs much slower than other clusters. Policymakers should consider the specific infrastructure and incentives needed to electrify these segments.