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- W2406836328 abstract "Abstract Battery electric vehicles (EVs) have a more limited range and longer refueling, i. e. charging times accompanied by battery aging as conventional vehicles. Initial field studies about the behavior of EV users also have identified the presence of range anxiety, which is expressed by frequent recharging. Battery aging is a non-linear process with numerous interactions, but generally pronounced around higher state of charge (SoC) levels. Therefore, range anxiety potentially provokes elevated battery degradation due to the resulting operating conditions. Based on 2966 empirical driving profiles, I analyze different user groups as well as the effect of different charging strategies in a simulation-based analysis. In comparison to charging strategies, for instance as fast as possible (AFAP) charging or critical SoC charging (such that the next trip is feasible), I calculate the degradation optimal charging pattern based on a realistic battery cell aging model. The model is derived from accelerated aging tests of Li-NMC 18650 cells, but can be adjusted to individual degradation parameters, in order to account for different battery chemistries. Preliminary results show that degradation can be reduced by up to 46% by the optimized charging strategy as compared to AFAP or critical SoC charging." @default.
- W2406836328 created "2016-06-24" @default.
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- W2406836328 date "2016-01-01" @default.
- W2406836328 modified "2023-09-27" @default.
- W2406836328 title "Modeling of battery life optimal charging strategies based on empirical mobility data" @default.
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- W2406836328 doi "https://doi.org/10.1515/itit-2015-0043" @default.
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