scholarly journals PNGV Equivalent Circuit Model and SOC Estimation Algorithm for Lithium Battery Pack Adopted in AGV Vehicle

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 23639-23647 ◽  
Author(s):  
Xiangyong Liu ◽  
Wanli Li ◽  
Aiguo Zhou
Keyword(s):  
Equivalent Circuit ◽  
Lithium Battery ◽  
Equivalent Circuit Model ◽  
Estimation Algorithm ◽  
Circuit Model ◽  
Battery Pack ◽  
Soc Estimation

A Strategy for Estimating State-of-Charge and State-of-Health of Li-Ion Batteries in Electric and Hybrid Electric Vehicles

2012 ◽  
Author(s):  
Xiaowei Zhao ◽  
Guoyu Zhang ◽  
Lin Yang
Keyword(s):  
Equivalent Circuit ◽  
Estimation Method ◽  
Equivalent Circuit Model ◽  
Circuit Model ◽  
State Of Charge ◽  
State Of Health ◽  
Li Ion Batteries ◽  
Soc Estimation ◽  
Kaiman Filtering ◽  
Li Ion

A task that has to be solved for the application of batteries in vehicles with an electric drive train is the determination of the actual state-of-health (SOH) and state-of-charge (SOC) of the battery cells. In this paper, an on board strategy for estimating SOC and SOH of Li-ion batteries is proposed. The equivalent circuit model is used for both SOC and SOH estimations. In SOH algorithm, the estimated value of battery capacity not only reflects the aging degree of battery pack, but also provides information for SOC estimation. Meanwhile, the extended Kaiman filtering is used in SOC estimation. Because the performance of the equivalent circuit model will be better at small currents than at high currents, extended Kaiman filtering is substituted by Ampere-Hour counting when the absolute value of current is greater than a calibration value. The Digatron battery tester was used to evaluate the proposed estimation method, and results show that the estimation method has high accuracy and efficiency at ordinary temperatures.

scholarly journals Cranking Capability Estimation Algorithm Based on Modeling and Online Update of Model Parameters for Li-Ion SLI Batteries

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3365
Author(s):  
Tae-Won Noh ◽  
Jung-Hoon Ahn ◽  
Byoung Kuk Lee
Keyword(s):  
Equivalent Circuit ◽  
Voltage Drop ◽  
Equivalent Circuit Model ◽  
Estimation Algorithm ◽  
Circuit Model ◽  
Estimation Accuracy ◽  
Voltage Response ◽  
Model Parameters ◽  
Voltage Range ◽  
Terminal Voltage

The terminal voltage of a starting–lighting–ignition (SLI) battery can decrease to a value lower than the allowable voltage range because of the high discharge current required to crank the engine of a vehicle. To avoid the safety problems generated by this voltage drop, this paper proposes a cranking capability estimation algorithm. The proposed algorithm includes an equivalent circuit model for describing the instantaneous voltage response to the cranking current profile. This algorithm predicts the minimum value of the terminal voltage for the cranking transient period by analyzing the polarization voltage and dynamic characteristic of the equivalent circuit model. The estimation accuracy is adjusted by an online update for the parameters of the equivalent circuit model, which varies with temperature, aging, and other factors. The proposed algorithm was validated by experiments with a 60Ah LiFePO4-type SLI battery.

scholarly journals An equivalent circuit model analysis for the lithium-ion battery pack in pure electric vehicles

2019 ◽  
Vol 52 (3-4) ◽  
pp. 193-201 ◽  
Author(s):  
Jie Su ◽  
Maosong Lin ◽  
Shunli Wang ◽  
Jin Li ◽  
James Coffie-Ken ◽  
...  
Keyword(s):  
Lithium Ion Battery ◽  
Equivalent Circuit ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Internal Resistance ◽  
Circuit Model ◽  
Battery Pack ◽  
Power Pulse ◽  
Simulation Error ◽  
Joint Experiment

According to the demand of vehicle lithium-ion battery pack, the splice equivalent circuit model is constructed. First, a joint experiment of intermittent discharge and hybrid power pulse characterization, basis of the requirements of parameter identification for the model, is designed to identify the parameters. Study shows that it can identify the parameters. Second, the splice equivalent circuit model of vehicle lithium-ion battery pack is simulated by MATLAB/Simulink, which shows the model is feasible to describe the vehicle lithium-ion battery pack. The simulation error of ohmic internal resistance R0 should be less than 0.05 mΩ. Study suggests that the vehicle lithium-ion battery pack has a stable discharge period within the state-of-charge range of [20%, 80%]. However, when stage of charge is below 20%, vehicle lithium-ion battery pack is no longer stable and the parameters of the splice equivalent circuit model change dramatically.

scholarly journals State of Charge Estimation of a Lithium Ion Battery Based on Adaptive Kalman Filter Method for an Equivalent Circuit Model

2019 ◽  
Vol 9 (13) ◽  
pp. 2765 ◽  
Author(s):  
Xiao Ma ◽  
Danfeng Qiu ◽  
Qing Tao ◽  
Daiyin Zhu
Keyword(s):  
Kalman Filter ◽  
Equivalent Circuit ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Circuit Model ◽  
State Of Charge ◽  
Filter Method ◽  
Adaptive Kalman Filter ◽  
Soc Estimation ◽  
Kalman Filter Method

Due to its accuracy, simplicity, and other advantages, the Kalman filter method is one of the common algorithms to estimate the state-of-charge (SOC) of batteries. However, this method still has its shortcomings. The Kalman filter method is an algorithm designed for linear systems and requires precise mathematical models. Lithium-ion batteries are not linear systems, so the establishment of the battery equivalent circuit model (ECM) is necessary for SOC estimation. In this paper, an adaptive Kalman filter method and the battery Thevenin equivalent circuit are combined to estimate the SOC of an electric vehicle power battery dynamically. Firstly, the equivalent circuit model is studied, and the battery model suitable for SOC estimation is established. Then, the parameters of the corresponding battery charge and the discharge experimental detection model are designed. Finally, the adaptive Kalman filter method is applied to the model in the unknown interference noise environment and is also adopted to estimate the SOC of the battery online. The simulation results show that the proposed method can correct the SOC estimation error caused by the model error in real time. The estimation accuracy of the proposed method is higher than that of the Kalman filter method. The adaptive Kalman filter method also has a correction effect on the initial value error, which is suitable for online SOC estimation of power batteries. The experiment under the BBDST (Beijing Bus Dynamic Stress Test) working condition fully proves that the proposed SOC estimation algorithm can hold the satisfactory accuracy even in complex situations.

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