<div class="section abstract"><div class="htmlview paragraph">As compared with other batteries, lithium-ion batteries are featured by high power density, long service life, high energy density, environmental friendliness and thus have found wide application in the area of consumer electronics. However, lithium-ion batteries for electric and hybrid electric vehicles (EVs and HEVs) have high capacity and large serial-parallel numbers, which, coupled with such problems as safety, durability, cost and uniformity, imposes limitations on the wide application of lithium-ion batteries in the EVs and HEVs. The narrow area in which lithium-ion batteries operate with safety and reliability necessitates the effective control and through the use of management of battery management system. Battery state of health (SOH) monitoring has become a crucial challenge in EVs and HEVs research, as SOH significantly affects the overall vehicle performance and life cycle. This paper presents both cycling and calendar aging at high and low temperatures. In the proposed model the calendar aging is represented as a function of time, storage temperature and state-of-charge (SOC). On the other hand, cycle aging is represented as a function of energy throughput, cell temperature and C-rate. The cycling and calendar aging models are later combined to formulate an empirical cell-level aging model. The performance of the cell-level empirical aging model is validated by comparing it with the aging test data for different driving scenarios. The aging prediction from the empirical aging model shows very good agreement with the test data with a maximum normalized root mean squared error (RMSE) of 0.85%</div></div>
Electrified vehicle (EV) batteries that have reached the automotive end of life are providing a low-cost energy storage solution for grid-connected systems, such as DC fast charge stations (DCFCs). There are several challenges associated with the integration of second life batteries (SLBs) in power systems, such as the definition of a systematic approach for the concurrent optimization of performance and lifetime with the aim of minimizing the investment and operating costs. This paper proposes the application of automotive SLBs to DCFC stations where high-power grid connection is not available or feasible. The SLBs are charged using a low-power grid connection and then provide DCFC power to the EVs. An optimal control problem has been formulated to identify the energy management control (EMC) strategy that allows minimizing the replacement rate of the SLBs, while ensuring the EV load request is match.
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