SYSTEMS AND METHODS FOR ENERGY STORAGE SYSTEM STATE ESTIMATION AND MANAGEMENT

原文（中国語）

Systems and methods for energy storage system (ESS) real-time state estimation and management. A system can include a deep learning (DL) module, which receives real-time measurement of time series data for current, voltage, and temperature of an ESS under test. The DL module can reshape the received time series data with a preprocessing component and then process the reshaped data with a DL component. The DL component can include various DL models such as DFFN, DCNN, LSTM, and ConLSTM, and utilize one or more of these DL models in estimating the SOH and/or remaining capacity for an ESS based on, for example, information about the ESS so as to generate more accurate estimations. The DL module can provide the estimations for the ESS under a variety of charging protocols. Such estimations can be utilized to control aspects of the ESS, such as optimizing its performance and extending its lifespan.