一种基于统计分析的动态SOC校准方法及系统
Through offline experiments and data analysis, characteristic cells of the battery are dynamically identified and calibrated, which solves the shortcomings of static calibration strategies, realizes dynamic SOC calibration of the battery system, and improves battery capacity utilization and flexibility.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- XIAN SINGULARITY ENERGY TECH CO LTD
- Filing Date
- 2026-04-07
- Publication Date
- 2026-07-17
AI Technical Summary
In existing battery management systems, the SOC calibration strategy for battery cells is mainly static calibration, which has strict triggering conditions and is difficult to meet actual needs, resulting in inconsistent cell capacity and low overall system capacity.
Offline experiments were conducted to collect data on the state of charge (SOC) and voltage curves of the battery cells. The Monte Carlo sampling theorem and the isolated forest algorithm were used to determine the baseline SOC value. Featured cells were dynamically identified and calibrated to dynamically correct the battery SOC value.
It enables dynamic correction of the battery's state of charge during battery operation, adapting to actual operating requirements and improving the overall capacity utilization and flexibility of the battery system.
Smart Images
Figure CN121978548B_ABST