Lithium iron phosphate battery management system and state-of-charge estimation for electric vehicles

2013 ◽  
Author(s):  
Lujia Lin
Keyword(s):  
Electric Vehicles ◽  
Management System ◽  
Lithium Iron Phosphate ◽  
Iron Phosphate ◽  
State Of Charge ◽  
Battery Management System ◽  
Battery Management ◽  
State Of Charge Estimation

Validation and benchmark methods for battery management system functionalities: State of charge estimation algorithms

2016 ◽  
Vol 7 ◽  
pp. 38-51 ◽  
Author(s):  
Christian Campestrini ◽  
Max F. Horsche ◽  
Ilya Zilberman ◽  
Thomas Heil ◽  
Thomas Zimmermann ◽  
...  
Keyword(s):  
Management System ◽  
State Of Charge ◽  
Battery Management System ◽  
Battery Management ◽  
Estimation Algorithms ◽  
State Of Charge Estimation

Research on State of Charge Estimation of Lithium Iron Phosphate Battery Used on Electric Vehicle

2011 ◽  
Vol 179-180 ◽  
pp. 3-8
Author(s):  
Cheng Lin Liao ◽  
Li Ye Wang ◽  
Li Fang Wang
Keyword(s):  
Simulation Model ◽  
Electric Vehicle ◽  
Management System ◽  
Lithium Iron Phosphate ◽  
Equivalent Circuit Model ◽  
Iron Phosphate ◽  
Least Square ◽  
Battery Management System ◽  
Battery Management ◽  
Management Algorithms

Lithium iron phosphate battery (LiFeO4 battery) is a very promising power battery. The research on LiFeO4 battery and the realization of its battery management system are very significant for the development of Electric Vehicle. Based on a large number of test data, the equivalent circuit model of battery is established, the parameters of the battery model are obtained using least-square method, and then the improved SOC estimation algorithm is studied in simulation conditions. All of the battery management algorithms are achieved in simulation model. The C code is generated from simulation model and applied in battery management system. Finally, the battery management algorithms are verified by simulation and hardware-in-loop test and bench test.

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