Lithium-ion cells are currently the dominant technology in the market for battery-powered electric vehicles. Their biggest downside is their degradation over lifetime and usage, limiting the main vehicle functions such as the driving power and range. Moreover, the battery aging state has a big influence on the expected residual value of electric vehicles. The speed of the degradation depends on specific operating conditions such as temperature, SOC level and current. These stress factors are influenced by the usage behaviour of the vehicle driver as well as possible tuning measures. The aim of this study is to investigate the impact of typical driver behaviour combined with tuning measures on battery aging and the resulting residual value. A fully configurable, longitudinal simulation model is presented for the analysis that covers the main components of an electric drivetrain and takes battery aging into account. The model allows us to simulate various possible driver characteristics and tuning measures. Furthermore, the affiliated regression model allows the establishment of a link between the battery aging induced by driver behaviour and the residual value. First results show that our approach is promising and indicate that driver behaviour has a big influence on battery aging and thus the residual value, this being further reinforced by tuning measures. In addition, there is no linear correlation between the aging induced by driver behaviour and the residual value.
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Lithium-ion cells are currently the dominant technology in the market for battery-powered electric vehicles. Their biggest downside is their degradation over lifetime and usage, limiting the main vehicle functions such as the driving power and range. Moreover, the battery aging state has a big influence on the expected residual value of electric vehicles. The speed of the degradation depends on specific operating conditions such as temperature, SOC level and current. These stress factors are inf...
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