Research On SOC Estimation Method Of LIFEPO4Battery

Lithium iron phosphate battery emerged in recent years has been widely used and gradually become the preferred electro car power battery due to its advantages of high rate charge-discharge capability, long cycling life, high safety and environmental protec-tion. The estimation precision of State of Charge (SOC) determines the life and working efficiency of energy storage system. This paper pertinently studies SOC estimation of nonlinear parameter in lithium-iron-phosphate battery, and online measurement of bat-tery capacity and open-circuit voltage in related models.For battery equivalent circuit model, this paper analyzes the influence of model pa-rameters on SOC estimation accuracy using experimental data, and proposes a simplified estimation model, which has removed state variable SOC in state equation, estimated on-ly battery polarization voltage, thus calculated Open Circuit Voltage (OCV) and further estimates the battery SOC. In different conditions, the estimation model was validated through extending Kalman Filter, Unscented Kalman Filter and Particle Filter SOC esti-mation methods.In practical applications, the battery capacity changes with temperature drift and an increase in cycle index, which produces greater error in SOC estimation. Typically, the exact value of battery capacity can be obtained only by a complete discharge test, while it is impossible to achieve the online correction of errors. Considering this issue, it estimated SOC parameters and calculated SOC difference at equal time interval through nonlinear extension of Kalman Filter and linear Ampere-hour method in the service course of the cells. By SOC definition, it obtains the corresponding relation between SOC differences of the two methods, gives the validity criterion of extended Kalman Filter estimation results, and thus proposes the calculation formula of battery capacity. It corrects online simulation value of battery capacity so as to further improve the SOC estimation accuracy.Normally, the battery OCV parameters can be only obtained by no-load prolonged standing. However, the inconsistency of batteries will inevitably end up indifference be-tween the acquired OCV measurement results and the actually OCV parameters, thus a ecting the actual SOC estimation accuracy. To solve this problem, the author uses electrochemistry theory to analyze the influence of polarization potential on OCV param-eter measurement. In addition, the paper substitutes battery terminal voltage di erence with adjacent intervals and load current into Terminal voltage loop equation of battery equivalent circuit model, with the purpose of solving the sum of ohmic polarization, elec-trochemical polarization and concentration polarization over potential. The difference between terminal voltage and over potential was taken and smoothing filtering was used to eliminate the impact of polarization over potential variation in battery capacity so as to acquire the open-circuit voltage of the battery rather than separate estimation of polar-ization over potential. This method achieves the online estimation of open-circuit voltage without under the standing state.Battery research inevitably entails plenty of experiments, and a homemade experi-mental system is more conducive to update and optimize the experiment. Considering the difference of verification, experiments and application scenarios, the paper builds a few battery test system platforms with the accuracy from high to low. Highly accurate veri-fication, experiment platforms built with external outpouring equipment and homemade application system were applied to verify practical application. Different platforms were used to carry out a large number of experiments in order to obtain the battery character-istic data for analysis. The platforms have laid the foundation for theoretical analysis and promoted the practical application of the algorithm. It develops a multi-function acqui-sition board and identifies the voltage and current measurement programs that meet the accuracy requirements; at the same time, in order to examine the application effect of algorithms in a low-accuracy acquisition system, this paper transplants EKF for SOC es-timation method to DSP development plate and makes comparisons with SOC estimation results, which has veri ed the portability and practicality of the SOC algorithm.