A Lithium-ion Battery SOC Estimation Method Involving Battery Internal Temperature

Liu, Yuntong; Chen, Haosen; Song, Wei‐Li; Lu, Jihua; Hou, Shujuan; Sun, Lei; Wang, Shaoqi

doi:10.1109/cvci56766.2022.9964684

Cited by 2 publications

(2 citation statements)

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“…The network structure in this work can be schematically represented as in Figure 3. The network contains 2 inputs and 1 output, and to obtain the number of neurons in the hidden layer, we use Equation (12), where n is the number of inputs to the network (in this case, 2 inputs), giving us 5 neurons in the hidden layer.…”

Section: Data Collection For the State Of Charge Of A Nickel Metal Hy...mentioning

confidence: 99%

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Electric Vehicle NiMH Battery State of Charge Estimation Using Artificial Neural Networks of Backpropagation and Radial Basis

Hernández,

Fernández,

Torres

2023

WEVJ

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The state of charge of a battery depends on many magnitudes, but only voltage and intensity are included in mathematical equations because other variables are complex to integrate into. The contribution of this work was to obtain a model to determine the state of charge with these complex variables. This method was developed considering four models, the multilayer feed-forward backpropagation models of two and three input variables used supervised training, with the variable-learning-rate backpropagation training function, five and seven neurons in the hidden layer, respectively, achieving an optimal training. Meanwhile, the radial basis neural network models of two and three input variables were trained with the hybrid method, the propagation constant with a value of 1 and 80 neurons in the hidden layer. As a result, the radial basis neural network with the variable-learning-rate training function, considering the discharge temperature, was the one with the best performance, with a correlation coefficient of 0.99182 and a confidence interval of 95% (0.98849; 0.99516). It is then concluded that artificial neural networks have high performance when modeling nonlinear systems, whose parameters are difficult to measure with time variation, so estimating them in formulas where they are omitted is no longer necessary, which means an accurate SOC.

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Section: Data Collection For the State Of Charge Of A Nickel Metal Hy...mentioning

confidence: 99%

“…Therefore, the kinetics of the charge transfer reaction are highly affected by temperature [12]. Higher C rates result in higher temperatures on the primary surface of the battery, since the current being discharged from the battery increases when the value of C is very high.…”

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confidence: 99%