Research On Multi-parameter Monitoring System For Battery Health Status

In order to ensure the safety of communication systems,power systems and defense military systems,more and more attention is paid to the use of emergency power supplies and uninterruptible power supplies.Lead-acid batteries are considered to be a cost-effective energy storage device and were used in more and more places now.While ensuring the safety of various power supply sites,the safety of lead-acid batteries also needs to be concerned.In this paper,according to the relationship between the parameters related to the battery and the health status of the battery,an online prediction method for health status of leadacid batteries is realized.Different methods are used to predict the state of charge(SOC)and state of health(SOH)of batteries under different working conditions.Under the condition of constant current charging and discharging of batter,considering the influence of temperature and charge-discharge rate on the residual capacity.The residual capacity of lead-acid batteries can be calculated by improved ampere-time method,and the SOC of battery can be obtained.When the battery is operating at a non-constant current,the voltage difference,time and temperature during the non-constant current discharge are taken as the input,and the SOC is taken as the output.The particle swarm optimization least squares support vector machine(PSO-LSSVM)method is used to estimate the SOC during non-constant current discharge of the battery.During the floating charge,according to the internal resistance and temperature of the battery,the SOH can be judged by referring to the relationship between the internal resistance and the residual capacity of the battery during charging.In addition,this paper also designed a related parameter detection device for lead-acid batteries.With STM32 as the core,the detection circuit of battery voltage,current,temperature and internal resistance is designed.The software part of battery health monitoring system is designed for real-time observation of battery health.Finally,the verification test of the lead-acid battery health monitoring system designed in this paper is carried out.The experimental results show that the system can accurately detect the related parameters of the battery,and the health status of lead-acid batteries can be accurately predicted by combining PS0-LSSVM method with improved ampere-time method.