State of Charge Estimation of Storage Battery in Data Center Based on Traceless Kalman Algorithm

In the context of the rapid development of data centers, this article proposes a kind of UPS battery monitoring scheme, which divides the monitoring system into the following parts: data acquisition module, data transmission module, and management coordination. According to the circuit model of battery, particle swarm optimization algorithm is used to identify the battery parameters. In order to improve accuracy of the battery state of charge estimation, an unscented Kalman filter algorithm is applied to estimate the battery SOC and proof the precision of the algorithm.