Online Detection of Battery Residual Capacity in DC Power Supply System Based on LSSVM
In order to solve the problems of low detection accuracy and long detection time in existing battery residual capacity detection methods,an online detection method for battery residual capacity in DC power systems based on LSSVM is proposed.Analyze the factors affecting the remaining capacity of DC power system batteries,obtain operational data such as battery volt-age,internal resistance,temperature,etc.The data acquisition and signal complete isolation are achieved by the sampling and re-cording unit.After analyzing the factors affecting battery capacity through the intelligent detection unit,a battery remaining ca-pacity detection model based on LSSVM is constructed.Open circuit voltage,internal resistance,and temperature parameter are used as the input for the battery residual capacity detection model based on LSSVM.The grey wolf optimization algorithm is used to solve the optimal solution of penalty coefficient,error,and kernel coefficient,output the battery residual capacity detec-tion results,and achieve online detection of battery residual capacity.The experimental results show that the detection error of the method proposed in this paper is controlled within±0.01,and the detection time is kept below 2 seconds.It has high detec-tion accuracy and efficiency,and good performance in practical application.
LSSVMDC power supply systembatteryremaining capacitygrey wolf optimization algorithminformation inter-action
万方数据
维普
