Abstract
A real time Neural Network (NN) technique is presented for estimating the electrochemical properties of Li-ion batteries. The Single Particle Model is retained to train the NN model. The resulting NN model is then used to estimate the diffusion coefficients (Ds,n & Ds,p) and the intercalation/deintercalation reaction-rate constants (Kn & Kp) of the electrodes, the electrolyte resistance of the battery (Rcell) and its discharge curve. The results show that the proposed NN model is computationally performant, accurate and befitting on-line parameter estimations. The NN model is also adaptable to a multitude of input variables and output parameters. As a result, it is expected that the present NN model will find applications in Battery Management Systems.
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