Modern automobiles are composed of more than 2000 different compounds comprising 76 different elements. Identifying supply risks across this palette of materials is important to ensure a smooth transition to more sustainable transportation technologies. This paper provides insight into how electrification is changing vehicle composition and how that change drives supply risk vulnerability by providing the first comprehensive, high-resolution (elemental and compound level) snapshot of material use in both conventional and hybrid electric vehicles (HEVs) using a consistent methodology. To make these contributions, we analyze part-level data of material use for seven current year models, ranging from internal combustion engine vehicles (ICEV) to plug-in hybrid vehicles (PHEVs). With this data set, we apply a novel machine learning algorithm to estimate missing or unreported composition data. We propose and apply a metric of vulnerability, referred to as exposure, which captures economic importance and susceptibility to price changes. We find that exposure increases from $874 per vehicle for ICEV passenger vehicles to $2344 per vehicle for SUV PHEVs. The shift to a PHEV fleet would double automaker exposure adding approximately $1 billion per year of supply risk to a hypothetical fleet of a million vehicles. The increase in exposure is largely not only due to the increased use of battery elements like cobalt, graphite, and nickel but also some more commonly used materials, most notably copper.
Keywords: automobile; critical materials; electric vehicle; machine learning; vulnerability.