Single-flow Zinc-Nickel Battery SOC Estimation And Charging Energy Efficiency Optimization Analysis

Single-Flow Zinc-Nickel battery is a new type of liquid flow energy storage device,which has the advantages of low cost,long life cycle and large energy storage capacity,and has a broad development prospect in the field of energy storage.The State Of Charge（SOC）Of the battery is an important parameter to characterize the current remaining Charge Of the battery.Aiming at the problems Of low precision Of SOC estimation and low energy efficiency Of the current single-flow Zinc-Ni battery,this article takes the single-flow Zinc-Nickel battery as the research object.Adaptive Square-Root Cubature Kalman Filtering（ASRCKF）was used to estimate the battery SOC,and an improved coyote optimization algorithm was proposed to optimize the charging current to improve the battery charging energy efficiency.Firstly,the characteristics and advantages of various battery modeling methods were analyzed,and the 2-RC equivalent circuit model of single-flow zinc-nickel battery was established.The pulse charge-discharge current and terminal voltage data of single-flow zinc-nickel battery were obtained by Xinwei BTS-5V200A battery testing system.The model parameters were identified by the improved coyote optimization algorithm proposed in stages.Then,there are many problems in the iteration of the Cubature Kalman Filtering（CKF）algorithm,such as the algorithm is stopped due to many sensitive operations that can destroy the symmetry and positive nature of covariance,and the SOC estimation accuracy is insufficient due to the covariance of fixed measurement noise.ASRCKF was used to estimate the SOC of a single-flow zinc-nickel.In order to improve the estimation accuracy and robustness of ASRCKF algorithm,some parameters such as noise covariance Q,initial value of measurement noise covariance R（0）and initial value of state error covariance P₀were proposed by improving the coyote optimization algorithm.Experiments under different operating conditions show that the optimized ASRCKF estimation of battery SOC has higher estimation accuracy and stronger robustness.Finally,aiming at the problem of low energy efficiency of single-flow zinc-nickel battery,this paper analyzes the effect of charging current on the charging energy efficiency of single-flow zinc-nickel battery,and proposes that the charging energy efficiency of the battery can be effectively improved by charging the battery in stages.The battery was charged in stages by the SOC with an interval of 5%,and the simulation and optimization model of battery charging energy efficiency was established.The improved coyote optimization algorithm was used to optimize the charging current in each stage.The simulation results show that the optimized charging current of each stage is used to simulate the battery charging,and the optimized charging energy efficiency is 67.90%,which is 0.44%higher than the traditional constant current charging method with a rate of 1C.In addition,in order to further verify the applicability of ASRCKF,the SOC estimation platform of single-flow zinc-nickel battery was designed,and the battery charge and discharge measurement and control system with STM32F107VCT6 microcontroller as the core was built.The relevant charge and discharge data were collected in real time by the slave computer and then transferred to the masterr computer to realize the SOC estimation.