A Fault Tolerant SoC Estimation method for Series-Parallel Connected Li-ion Battery Pack

2021 ◽  
pp. 1-1
Author(s):  
Shiyao Zhou ◽  
Ziqiang Chen ◽  
Deyang Huang ◽  
Tiantian Lin
Keyword(s):  
Fault Tolerant ◽  
Estimation Method ◽  
Battery Pack ◽  
Li Ion Battery ◽  
Soc Estimation ◽  
Li Ion

scholarly journals Li-ion battery SOC estimation method using a Neural Network trained with data generated by a P2D model

2021 ◽  
Vol 54 (10) ◽  
pp. 336-343
Author(s):  
Jean Kuchly ◽  
Alain Goussian ◽  
Mathieu Merveillaut ◽  
Issam Baghdadi ◽  
Sylvain Franger ◽  
...  
Keyword(s):  
Neural Network ◽  
Estimation Method ◽  
Li Ion Battery ◽  
Soc Estimation ◽  
Li Ion

Online State-of-Charge Estimation of Li-Ion Battery Based on the Second-Order RC Model

2013 ◽  
Vol 805-806 ◽  
pp. 1659-1663 ◽  
Author(s):  
Ze Cheng ◽  
Qiu Yan Zhang ◽  
Yu Hui Zhang
Keyword(s):  
Estimation Method ◽  
Equivalent Circuit Model ◽  
Second Order ◽  
State Of Charge ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Battery ◽  
Soc Estimation ◽  
Counting Approach ◽  
Li Ion

The real-timely estimation of the SOC (state of charge) is the key technology in Li-ion battery management system. In this paper, to overcome the error of the SOC estimation of Extended Kalman filter (EKF), a new estimation method based on modified-strong tracking filter (MSTF) is applied to SOC estimation of Li-ion battery, based on the second-order RC equivalent circuit model. Experiments are made to compare the new filter with the EKF and Coulomb counting approach (Ah). The simulation results demonstrate that the new filter algorithm MSTF used in this paper has higher filtering accuracy under the same conditions.

scholarly journals Li-Ion Battery Pack SoC Estimation for Electric Vehicles

2018 ◽  
Author(s):  
Kodjo Senou Rodolphe Mawonou ◽  
Akram Eddahech ◽  
Didier Dumur ◽  
Emmanuel Godoy ◽  
Dominique Beauvois ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Battery Pack ◽  
Li Ion Battery ◽  
Soc Estimation ◽  
Li Ion

Design on Electric Vehicle Battery Management System with FlexRay Bus

2015 ◽  
Vol 789-790 ◽  
pp. 784-790
Author(s):  
Jian Kun Peng ◽  
Hong Wen He ◽  
Deng Pan
Keyword(s):  
Electric Vehicle ◽  
Management System ◽  
Fault Tolerant ◽  
Estimation Method ◽  
Battery Management System ◽  
Battery Management ◽  
Soc Estimation ◽  
Electric Vehicle Battery ◽  
Bench Experiment ◽  
Li Ion

FlexRay bus is considered as a more promising bus in the future with the performance of real-time, scalable, and fault-tolerant. In this paper we will design an electric vehicle battery management system (BMS) based on FlexRay bus, including the hardware design, the SoC estimation method, FlexRay protocol design and software development. The test bench experiment results show the system design is reasonable and feasible.Keywords- FlexRay, BMS, Li-ion battery,SoC, Design

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