Abstract

<div class="section abstract"><div class="htmlview paragraph">DC fast charging (DCFC) also referred to as L3 charging, is the fastest charging technology to replenish the drivable range of an electric vehicle. DCFC provides the convenience of faster charging time compared to L1 and L2 at the expense of potentially increased battery health degradation. It is known to accelerate battery capacity fade leading to reduced range and lifetime of the EV battery. While there are active efforts and several means to reduce the downsides of DCFC at cell chemistry level, this trade-off is still an important consideration for most battery cells in automotive propulsion applications. Since DCFC is a customer driven technology, informing drivers of the trade-off of each DCFC event can potentially result in better outcomes for the EV battery life. Traditionally, the driver is advised to limit DCFC events without providing quantifiable metrics to inform their decisions during EV charging. A recommendation system for DCFC based on battery health optimization is proposed in this work. The optimization framework uses historical driver behavior, both in charging and driving, which customizes the DCFC recommendation. It is further informed by a battery capacity fade model that is sensitive to different modes of charging. Dynamic programming is employed to compute the remaining fast charging budget for an end-of-life battery capacity target. Results of the optimization and the resulting fast charging recommendation scenario is presented. The fast-charging recommendation system is shown to be capable of meeting the end-of-life battery capacity target through appropriate sequencing and advising of charge events.</div></div>

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