Research on Discharge Characteristics of Lithium Batteries in Low Temperature Environment

Abstract

Establish a lithium battery nonlinear equivalent circuit model, take 25Ah lithium iron phosphate battery performance parameters as model parameters, use Matlab experimental simulation to analyze the discharge curve of the lithium battery nonlinear equivalent circuit model, and pass the lithium battery static discharge capacity test experiment Verify reliability; Analyze the discharge characteristics of lithium iron phosphate batteries, polymer lithium batteries, and ternary lithium batteries at low temperatures of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{0},\ -\mathbf{5},\ -\mathbf{10},\ -\mathbf{15},\ -\mathbf{20},\ -\mathbf{25}{{}^{\circ}\mathsf{C}}$</tex> ; Taking the lithium iron phosphate battery that has the greatest impact on the low-temperature environment as the research object, in response to the problem that it is difficult to directly measure at different temperatures, a prediction simulation of indirect discharge capacity is proposed, and the prediction is realized indirectly; Fitting the nonlinear relationship between voltage and discharge capacity through Gaussian curve to realize the prediction of the discharge capacity of lithium battery by the characteristic parameter of voltage at a fixed temperature; On the basis of Gaussian fitting, the least squares polynomial is introduced to fit the relationship between Gaussian fitting and temperature, and then it is realized. The characteristic parameter is the temperature discharge prediction model. The results show that the constant current discharge time of lithium batteries is proportional to the discharge capacity in a low temperature environment, and the discharge capacity is affected by low temperature in order: lithium iron phosphate battery, ternary lithium battery, polymer lithium battery, and finally verify and evaluate the construction Based on the prediction model, it is concluded that when the temperature is -25 °C~0°C, the change trend of the self-discharge prediction value is the same as the actual value, there is a maximum average relative error within 6 % and the prediction accuracy is good.