| Popis: |
Batteries are critical components of battery electric vehicles (BEVs) and yet their expected lifetime is hard to estimate. Various determinants play a significant role, among which cell temperatures and usage profile are notably the most predominant, but their impact is complex to estimate. The variability of the vehicle usage patterns makes it difficult to estimate typical stresses on the battery, and cell temperatures are often unknown conversely to the ambient temperature, that is usually used in degradation models. For these reasons, in this study we present a methodology for estimating the expected battery lifetime in electric vehicles (EVs) through a comprehensive powertrain, electrical and thermal model of the vehicle and its battery, including a battery degradation model. Supported by experimental measures, the whole model, including the battery cooling system, is calibrated with data obtained from the onboard Controller Area Network (CAN) of a BEV with average error below 1°C. The case study to represent typical traffic conditions on Italian routes highlights that the approach is robust, expected battery lifetimes are suitable for typical vehicle usage, and that appropriate battery thermal modelling can reduce errors in the lifetime assessment of beyond 40-50%. The study emphasizes the importance of active thermal management in preserving battery health, and the methodology provides a foundation for further multi-disciplinary modeling of EV battery aging. |
