scholarly journals A Novel State of Charge Estimation Algorithm for Lithium-Ion Battery Packs of Electric Vehicles

Energies ◽  
2016 ◽  
Vol 9 (9) ◽  
pp. 710 ◽  
Author(s):  
Zheng Chen ◽  
Xiaoyu Li ◽  
Jiangwei Shen ◽  
Wensheng Yan ◽  
Renxin Xiao
Keyword(s):  
Lithium Ion Battery ◽  
Electric Vehicles ◽  
Lithium Ion ◽  
Estimation Algorithm ◽  
State Of Charge ◽  
Battery Packs ◽  
State Of Charge Estimation

Thermal State of Charge Estimation in Phase Change Composites for Passively Cooled Lithium-Ion Battery Packs

2018 ◽  
Vol 54 (1) ◽  
pp. 426-436 ◽  
Author(s):  
Mohamad Salameh ◽  
Stephen Wilke ◽  
Ben Schweitzer ◽  
Peter Sveum ◽  
Said Al-Hallaj ◽  
...  
Keyword(s):  
Phase Change ◽  
Lithium Ion Battery ◽  
Thermal State ◽  
Lithium Ion ◽  
State Of Charge ◽  
Battery Packs ◽  
Phase Change Composites ◽  
State Of Charge Estimation

scholarly journals State of Charge Estimation Techniques for Lithium-ION Batteries Used in Electric Vehicle Applications

2021 ◽  
Vol 9 (8) ◽  
pp. 2750-2760
Author(s):  
Nikhil P
Keyword(s):  
Lithium Ion Battery ◽  
Electric Vehicles ◽  
Lithium Ion ◽  
High Energy ◽  
State Of Charge ◽  
High Energy Density ◽  
Estimation Methods ◽  
Estimation Techniques ◽  
Soc Estimation ◽  
Battery Packs

Abstract: Lithium-ion battery packs constitute an important part of Electric vehicles. The usage of Lithium-ion based chemistries as the source of energy has various advantages like high efficiency, high energy density, high specific energy, longevity among others. However, the management of lithium-ion battery packs require a Battery Management System (BMS). The BMS deals with functions like safety, prevention of abusive usage of battery pack, overcharging & over-discharging protection, cell balancing and others. One of the prominent features of the BMS is the estimation of State of charge (SOC). SOC is like a fuel gauge in automobile, it indicates how much more the battery can be used before charging it again. SOC is also required for other functions of BMS like State of Health (SOH) tracking, Range calculation, power & energy availability calculations. However, there is no means of measuring it directly (at least not on-board a vehicle) or estimating it easily. Various techniques should be used to estimate SOC indirectly. This paper starts from classical techniques that have existed since long time and reviews some of the modern & developing methods for SOC estimation. It contains a brief review about most of these SOC estimation methods, thus highlighting the methodology, advantages & disadvantages of each of these techniques. A brief review of other developing SOC estimation techniques is also provided. Keywords: State of Charge, SOC, Lithium-ion battery packs, Electric vehicles, Kalman Filter.

Application of Kalman Filter in SOC Estimation of Power Lithium-Ion Battery

2012 ◽  
Vol 605-607 ◽  
pp. 1939-1943
Author(s):  
Chen Zhao ◽  
Xi Kun Chen
Keyword(s):  
Kalman Filter ◽  
Lithium Ion Battery ◽  
Lithium Ion ◽  
Estimation Algorithm ◽  
State Of Charge ◽  
Voltage Response ◽  
Integrated Method ◽  
Soc Estimation ◽  
Terminal Voltage ◽  
State Of Charge Estimation

This paper analyses the application of Kalman Filter (KF) in Power Lithium-ion Battery SOC (State of Charge) estimation algorithm. After the analysis of two popular SOC estimate algorithm based on KF, an improved KF-SOC algorithm is proposed. The main advance of this improved algorithm is the introduction of parameter-rectification. The parameter-rectification which based on analysis of battery electrochemical principle and battery terminal voltage response curve is also achieved by KF. The main algorithm of improved KF-SOC is generated by the combination of KF and Ampere-hour integrated method. Later the simulations proved the new algorithm with high accuracy.

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