A novel non-experiment-based reconstruction method for the relationship between open-circuit-voltage and state-of-charge/state-of-energy of lithium-ion battery

To date, model-based state-of-charge (SOC)/state-of-energy (SOE) estimation algorithm of lithium-ion battery has been widely used in real application due to its rational tradeoff between estimation accuracy and complexity. Nevertheless, as the bridge between estimated state and observation information in this class of method, the relationship between open-circuit-voltage (OCV) and SOC/SOE inevitably changes with battery degradation. Therefore, this relationship must be timely updated to assure precise SOC/SOE estimation. Considering the disadvantages existing in traditional OCV tests, including time-consuming and poor flexibility, a novel non-experiment-based reconstruction method for the relationship between OCV and SOC/SOE is proposed in this paper, where no additional battery tests are needed and the relationship between OCV and SOC/SOE can be partially reconstructed during battery's daily operating process. To verify the feasibility of the presented non-experiment-based reconstruction method, a sophisticated driving simulation namely Federal Urban Driving Schedule test is performed in this work. The validation results show that the relationship between OCV and SOC/SOE reconstructed by the proposed non-experiment-based method can well reflect the different battery aging status. On the basis of the reconstructed relationship, both mean absolute error and root mean square error of SOC/SOE estimation results by using extended Kalman filter can be roughly limited below 1%. In addition, a publicly available dataset namely “Panasonic 18650PF Li-ion Battery Data” is further adopted to evaluate the universality of the developed method, whose verification results demonstrate that the designed non-experiment-based method can still construct the relationship between OCV and SOC/SOE precisely of different type of lithium-ion batteries without any sophisticated preliminary tests.