A novel endurance prediction method of series connected lithium-ion batteries based on the voltage change rate and iterative calculation

Abstract

A novel endurance prediction method of series connected lithium-ion batteries based on the voltage change rate and iterative calculation.

Offline and Online Blended Machine Learning for Lithium-Ion Battery Health State Estimation

“…The offline SBC-RBFNN model structure is obtained by combining ( 9)- (11), denoted by y = h(x). To obtain the parameters for one individual model, including the weights W [1] , W [2] , and W [3] , the biases b [1] , b [2] , and b [3] , as well as the center vector [z c1 , z c2 , • • • , z cn ], the datasets are randomly split into the base model group, training group, and testing group, and they are used for base model generation, SBC-RBFNN model training, and model verification, respectively. The RMSE between the model and the expected output, calculated by (8), is used as the loss function in the training process.…”

“…However, the energy storage capacity and power capability of Li-ion batteries can gradually reduce caused by various aging mechanisms, leading to limited service life and degraded system performance over time [2]. To ensure the safe, reliable, and efficient use of Liion batteries, the indicator of battery health, namely the state of health (SOH), must be precisely monitored and predicted, which forms a fundamental functionality of Li-ion battery management systems (BMSs) [3].…”

A simulation-driven prediction model for state of charge estimation of electric vehicle lithium battery

“…However, it is important to note that a battery is a complex system of chemical reactions. Its structure comprises various components, including positive and negative electrodes [ 8 ], model [ 9 ], and internal medium [ 10 ]. The electrolyte's positive and negative ions move between the electrodes due to the electric current, leading to chemical reactions.…”

Adaptive iterative working state prediction based on the double unscented transformation and dynamic functioning for unmanned aerial vehicle lithium-ion batteries

“…18 In addition, a new method for predicting the life of LiBs based on the voltage change rate and iterative calculation is proposed. 19 The online dynamic equilibrium adjustment of high-power LiB packs based on the equilibrium state estimation is designed. 20 The method of data model fusion is applied to the estimation of online charging state and health state of LiB.…”