Assessing planning-reference electrification envelopes against a calibrated EV-diffusion trajectory in Puerto Rico

Transportation–electrification pathways are increasingly used as inputs for long-term infrastructure and energy-planning decisions. In Puerto Rico, legislative, regulatory, and planning instruments provide context for transportation electrification and decarbonization through mid-century; however, they do not prescribe a unique temporal pathway for electrification of the reference vehicle fleet. This paper develops a consistency-assessment framework that compares planning-reference electrification envelopes, informed by Puerto Rico’s policy and decarbonization context, with a generalized-logistic trajectory calibrated from historical registered EV-stock observations. Historical registered EV-stock data from $$2014$$ through $$2023$$ are used to calibrate the generalized-logistic model, while front-loaded, linear, and delayed electrification envelopes are constructed around a common reference planning endpoint. The resulting pathways are compared using an adoption-level discrepancy metric, Δ P(t) , and a transition-time discrepancy metric, Δ Tₓ , which quantify differences in electrification levels and milestone-attainment timing, respectively. The calibrated model reproduces the observed series with R²=0.996 on cumulative stock and R²=0.959 on annual increments, and parameter uncertainty is propagated to both metrics by profile likelihood and residual bootstrap. Under the $$100%$$ reference endpoint, the calibrated trajectory remains below the three primary planning-reference envelopes at the representative planning years evaluated. Relative to the common $$2050$$ planning benchmark, the benchmark-to-model adoption-level discrepancy reaches approximately $$25$$ percentage points ( $$95%$$ interval $$22$$ to $$30$$ ). Representative electrification milestones are attained approximately $$2$$ to $$19$$ years later than under the corresponding envelopes, with delays of approximately $$11$$ to $$16$$ years at the $$90%$$ electrification milestone; under the $$100%$$ reference endpoint, the base-case discrepancies for the three primary envelopes remain positive across the bootstrap replicates evaluated. These results illustrate how differences between planning assumptions and a calibrated diffusion trajectory may affect charging-demand projections, infrastructure-deployment schedules, and long-term power-system planning; they are not deterministic forecasts or assessments of policy compliance. Sensitivity analyses across the reference endpoint, the saturation reference, the power-law envelope shape, and a sigmoid-family robustness check show that the reported discrepancy is governed primarily by endpoint and temporal-shape assumptions, with a break-even endpoint near $$75%$$ , whereas the saturation reference has a comparatively small effect on normalized adoption-level and transition-time metrics but materially affects absolute plug-in-equivalent charging-energy estimates. The framework supports periodic reassessment as adoption evidence evolves.