Jiahuan Lu

TL;DR: Investigating the external short circuit (ESC) fault characteristics of lithium-ion battery experimentally shows that the ESC fault can be diagnosed within 5s, the error between the model and measured data is less than 0.36V and the effectiveness of the fault diagnosis algorithm is not sensitive to the precision of battery SOC.

TL;DR: A deep neural network (DNN) based method is proposed to estimate SOC with only 10-min charging voltage and current data as the input, which enables fast and accurate SOC estimation with an error of less than 2.03% over the entire battery SOC range.

TL;DR: This work extends conventional capacity degradation estimation to the estimation of entire constant-current charging curves using a deep neural network developed to estimate complete charging curves by featuring small portions of the charging curves to form the input.

TL;DR: Li et al. as discussed by the authors investigated the ESC-caused temperature rise characteristics of LiB, and proposed an online prediction approach of the maximum temperature rise, which can be used for LiB safety management in all-climate electric vehicles application.

TL;DR: In this paper , the authors proposed a flexible method using only short pieces of charging data to estimate both maximum and remaining capacities to simultaneously address the state of health and state of charge estimation problems.