Power Battery SOC Algorithms And Its Information Model Study

With the consumption of global primary energy and environment problems more serious,electric vehicle has been widely concerned for its zero emission, low noise advantages,relative to the fuel car. Countries regard electric vehicles as the development direction of theautomobile industry, with its distributed energy storage characteristic as the important part ofthe construction of smart grid.At present, hybrid cars received more and more attention, pure electric car start to enterthe market. As the important constituent of the electric vehicles(EV), power battery’sperformance directly affects the electric car on use and promotion. Battery SOC is animportant parameter for measure the actual available capacity of the power battery, carry onthe accurate estimation is the prerequisite to guarantee the power battery safety, continuous,the longest life supply the power.This paper takes the lead acid battery as the study object, and take estimating the batterystate of charge accurately as objective, studied and tested of lead-acid batteries work principleand characteristics, analysis the factors which influence of power battery SOC,comprehensive consideration the advantages and disadvantages of the methods of thecommon battery state of charge estimation, and combined with the construction of the smartgrids and the charging station to design an electric vehicle power battery SOC estimationmethod.The specific works in this paper are as follows:According to beneficial effect which natural information and factory testing parameterson power battery SOC estimation, the method of embedding battery chip in the battery packto achieve data preservation and can be read and write selectively is studied, at the same time,the method to use the embedded chip to identify the battery Authenticity, which prevent thefake and inferior products into the market is designed in paper.National Grid carry out the construction of electric vehicle charging facilities, this meanswe can achieve battery charge and discharge data sharing through the charging stations’process layer network and network between the charging stations. And use the sharingfunction to provide a large number of effective data for battery SOC estimation. At the sametime the battery manufacturer and the project team can also visit the management database toview the data shared network and can monitor the battery analysis and failure prediction,diagnosis. The paper studies the aging effect of power battery in the cycle, the relationship betweenthe rechargeable capacity and rated capacity is analyzed, and the relationship of the batterycurrent circulation use times and number of times of the manufacturers expected, presents thebattery life factor to measure battery current performance considering the electric output ofthe monomer battery in the actual working condition, and establishes a battery life factorexpression, and through experiments on the algorithm for solving verification.This paper designed life factor model of SOC estimate based on standard model, it usesBP neural network, GA-BP, GAAA-BP network to simulate the SOC estimation modelrespectively. Compared its estimates effect, we can realize the life factor model estimationaccuracy is higher than that of the standard model, and the estimation effect of GAAA-BPneural network for power battery SOC is superior to the other two network.The application of power battery as distributed energy in the intelligent power grid isstudied and SOC estimate information model is established in the paper. Analysis the IEC61850-7-420takes the power battery as source of energy which used in power grid, thendesigned the SOC information model, analysis the appliance of the battery SOC to access therole of power grid, and designed the corresponding data class and data attribute for the batterySOC model. At last, this paper use IEC61850Test Harness software constructed battery SOCmodel, and verified the usability of the model.