State of charge(SOC)estimation is a key process for ensuring the reliable operation of lithium battery.Since the operation of lithium battery is affected by many complex factors of itself and the outside,the traditional SOC estimation methods are ineffective.Therefore,there is a need to explore the SOC estimation method of lithium battery based on adaptive neuro-fuzzy inference system(ANFIS).The method establishes a three-input ANFIS model using measured voltage,discharge multiplier,and discharge capacity data.The ANFIS model establishes a nonlinear fuzzy system on its own according to the data characteristics,and optimizes the model's concluding parameters using the least squares estimation(LSE),and optimizes the model's premise parameters through the back-propagation(BP)algorithm.Comparing the ANFIS model with the commonly used BP model,the results show that the ANFIS model has better estimation accuracy and stability relative to the BP model,the root mean square error(7.09×10-5)and mean absolute error(3.63×10-5)of the ANFIS model improve the accuracy relative to the BP model by respectively 1.1%and 10.62%.
维普
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