Lithium battery SOC prediction method of bayes regularization LM-BP neural network

• Main Authors: ZHANG CHIJIAN, LI GUIJUAN, SHI ZHIGANG, LI LIANG
• Format: Patent
• Language: Chinese; English
• Published: 22.03.2019
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; MEASURING; MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES; PHYSICS; TESTING

The invention discloses a lithium battery SOC prediction method of a bayes regularization LM-BP neural network. The lithium battery SOC prediction method comprises the following steps: a, establishinga BP neural network model; b, establishing a bayes regularization LM-BP neural network algorithm; c, acquiring sample data and calculating sample SOC; and d, performing the normalization processing of data. The neural network has good nonlinear fitting capacity and does not need to consider a complicated chemical structure inside the battery, dynamic characteristics of the lithium battery can bewell fit, by combining the bayes regularization algorithm, the generalization capacity of the network can be improved, by combining the LM algorithm, the convergence rate of the network can be increased, and the approximation accuracy can be improved; and therefore, the lithium battery SOC prediction method of the bayes regularization LM-BP neural network has the characteristics of high predictionprecision, high convergenc