The article aims to develop, based on experimental data, a comprehensive aging model for a battery used in vehicular applications. This model utilizes a Rainflow algorithm to adequately account for all major factors contributing to capacity degradation: cycling, calendar life, temperature, and battery current.

In conjunction with this approach, a physical/electrothermal model of the electric vehicle has been developed in Modelica language, accurately simulating both thermal and electrical behavior of the battery under various driving profiles that include different charging modes reflecting user driving habits.

These modes encompass slow charging, fast charging, and Vehicle-to-Grid (V2G) applications supporting the electrical grid. The proposed case study demonstrates that the expected lifespan of electric vehicles is comparable to traditional cars (10-20 years) and that modeling the battery’s operational temperature reduces estimation errors by up to 27%.

A sensitivity analysis was conducted across different climatic regions in Italy, suggesting that in colder climates, the expected lifespan could increase by up to 30% compared to warmer areas.