http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112098845-A

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filingDate 2020-08-17-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_9aff3020a443d13c314d32a0a8daa66f
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publicationDate 2020-12-18-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-112098845-A
titleOfInvention A Lithium Battery State Estimation Method for Distributed Energy Storage System
abstract The invention discloses a lithium battery state estimation method for a distributed energy storage system, and belongs to the application field of lithium ion batteries. The method includes using a gated cyclic unit cyclic neural network to establish a deep learning-based lithium battery state of health estimation model; using a second-order equivalent circuit model of the lithium battery combined with an extended Kalman filter algorithm to estimate the real-time distribution of the distributed energy storage unit management system. Lithium battery state of charge; update the battery capacity and lithium battery state of health estimation model in the process of estimating lithium battery state of charge synchronously through information exchange. On the premise of not increasing the cost of system hardware, the invention provides accurate lithium battery capacity for SOC estimation through information exchange, and provides training samples for the big data SOH estimation model at the same time; and further improves the relationship between the SOC and SOH of the lithium battery in the system. The estimation accuracy is convenient for subsequent effective energy management and scheduling of the system.
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Total number of triples: 39.