Prediction Status Of Peak Power Of Battery On HEV

Power battery, as the core of electrical vehicle, should meet the requirementof dynamic factor and maintain its battery life at the same time. Then, the generaldesign of the body and the power management system of the electrical vehiclemay take real-time peak power of different conditions into consideration. Basedon checking many reference on testing standard and method of battery power inand aboard, predicting the future trend and analyzing the advantages and disadvantages respectively, this paper has proposed several battery dischargingmethods to test the output peak power of Li-ion battery for10seconds with two-pulse discharge, multi-pulse and constant power discharge and a method ofpredicting the output power through BP neural network is given in the paper. Themain contents are as follows:1． Two-pulse discharge, multi-pulse discharge and constant powerdischarge are applied respectively to measure the peak power of Li-ion battery,then the analysis results on the advantages of the methods is shown to find outthe more accurate, easy-operating, and easy-applied one.2．Conduct analysis on the experimental data obtained from the methodsabove, and get three types of prediction function: linear, exponential andpolynomial by fitting the experimental data. A conclusion can be drawn from theanalysis on the accuracy of the prediction value that exponential function can beapplied to predict the peak power of the battery with the minimal error.3． The peak power and real-time output power of power battery aresignificant factors to keep the balance between power and economy and longerbattery life. So the BP neural network model is proposed to predict the real-timeoutput power, make a comparison with realistic value and test on the feasibilityof the model.