scholarly journals Kalman filter applied to Thevenin’s modeling of a lead-acid battery

2022 ◽  
Vol 12 (2) ◽  
pp. 1350
Author(s):  
Jose Alfredo Palacio-Fernádez ◽  
Edwin García Quintero
Keyword(s):  
Kalman Filter ◽  
Open Circuit Voltage ◽  
Open Circuit ◽  
State Of Charge ◽  
Model Estimation ◽  
Lead Acid Battery ◽  
Battery Model ◽  
Internal Parameters ◽  
Different Types ◽  
Lead Acid

<span>This article determines the internal parameters of a battery analyzed from its circuit equivalent, reviewing important information that can help to identify the battery’s state of charge (SOC) and its state of health (SOH). Although models that allow the dynamics of different types of batteries to be identified have been developed, few have defined the lead-acid battery model from the analysis of a filtered signal by applying a Kalman filter, particularly taking into account the measurement of noise not just at signal output but also at its input (this is a novelty raised from the experimental). This study proposes a model for lead-acid batteries using tools such as MATLAB<sup>®</sup> and Simulink<sup>®</sup>. First, a method of filtering the input and output signal is presented, and then a method for identifying parameters from 29 charge states is used for a lead-acid battery. Different SOCs are related to different values of open circuit voltage (OCV). Ultimately, improvements in model estimation are shown using a filter that considers system and sensor noise since the modeled and filtered signal is closer to the original signal than the unfiltered modeled signal.</span>

scholarly journals Parameter Identification and State-of-Charge Estimation for Lithium-Ion Batteries Using Separated Time Scales and Extended Kalman Filter

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1054
Author(s):  
Kuo Yang ◽  
Yugui Tang ◽  
Zhen Zhang
Keyword(s):  
Kalman Filter ◽  
Parameter Identification ◽  
Open Circuit Voltage ◽  
Lithium Ion ◽  
Open Circuit ◽  
State Of Charge ◽  
Recursive Least Squares ◽  
Model Parameters ◽  
Soc Estimation ◽  
Battery Model

With the development of new energy vehicle technology, battery management systems used to monitor the state of the battery have been widely researched. The accuracy of the battery status assessment to a great extent depends on the accuracy of the battery model parameters. This paper proposes an improved method for parameter identification and state-of-charge (SOC) estimation for lithium-ion batteries. Using a two-order equivalent circuit model, the battery model is divided into two parts based on fast dynamics and slow dynamics. The recursive least squares method is used to identify parameters of the battery, and then the SOC and the open-circuit voltage of the model is estimated with the extended Kalman filter. The two-module voltages are calculated using estimated open circuit voltage and initial parameters, and model parameters are constantly updated during iteration. The proposed method can be used to estimate the parameters and the SOC in real time, which does not need to know the state of SOC and the value of open circuit voltage in advance. The method is tested using data from dynamic stress tests, the root means squared error of the accuracy of the prediction model is about 0.01 V, and the average SOC estimation error is 0.0139. Results indicate that the method has higher accuracy in offline parameter identification and online state estimation than traditional recursive least squares methods.

Correlation between Battery Voltage under Loaded Condition and Estimated State of Charge at Valve-Regulated Lead Acid Battery on Discharge Condition using Open Circuit Voltage Method

2018 ◽  
Vol 9 (1) ◽  
pp. 357
Author(s):  
Ahmad Qurthobi ◽  
Anggita Bayu Krisna Pambudi ◽  
Dudi Darmawan ◽  
Reza Fauzi Iskandar
Keyword(s):  
Open Circuit Voltage ◽  
Open Circuit ◽  
State Of Charge ◽  
Lead Acid Battery ◽  
Battery Voltage ◽  
Measured Voltage ◽  
The Common ◽  
Loaded Voltage ◽  
Vrla Battery ◽  
Lead Acid

One of the common methods that developed to predict state of charge is open circuit voltage (OCV) method. The problem which commonly occurs is to find the correction parameter between open circuit voltage and loaded voltage of the battery. In this research, correlation between state of charge measurement at loaded condition of a Panasonic LC-VA1212NA1, which is a valve-regulated lead acid (VRLA) battery, and open circuit voltage had been analyzed. Based on the results of research, correlation between battery’s measured voltage under loaded condition and open circuit voltage could be approached by two linearization area. It caused by K v ’s values tend to increase when measured voltage under loaded condition V M &lt; 11.64 volt. However, K v values would be relatively stable for every V M ≥ 11.64 volts. Therefore, estimated state of charge value, in respect to loaded battery voltage, would increase slower on V M &lt; 11.64 volts and faster on other range.

Modelling and Simulation of a Lead Acid Battery for Traction Applications

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
D. Elangovan ◽  
G. Arunkumar ◽  
H.M. Tania ◽  
J.K Patra
Keyword(s):  
Equivalent Circuit ◽  
State Of Charge ◽  
Lead Acid Battery ◽  
Cell Temperature ◽  
Third Order ◽  
Electrical Equivalent Circuit ◽  
Battery Model ◽  
Terminal Voltage ◽  
Simulation Results ◽  
Lead Acid

In this paper, modeling of a lead acid battery was done by electrical equivalent circuit approach. Model based equivalent circuit approach was used to find the state of charge, terminal voltage, cell temperature and life of the battery at various temperatures. Based on complexity and accuracy, Thevinin’s third order equivalent battery model was simulated using MATLAB Simulink software. The simulation results were validated with the experimental state of charge and terminal voltage values.

scholarly journals State of charge estimation by using extended Kalman filter based on improved open circuit voltage model

2021 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Maamar Souaihia ◽  
Bachir Belmadani ◽  
Rachid Taleb ◽  
Kamel Tounsi
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Equivalent Circuit Model ◽  
Open Circuit ◽  
State Of Charge ◽  
Soc Estimation ◽  
Battery Model ◽  
Filter Approach ◽  
State Of Charge Estimation ◽  
Good Agreement

This paper focuses on the state of charge estimation (SOC) for battery Li-ion. By modeling a battery based on the equivalent circuit model, the extended Kalman filter approach can be applied to estimate the battery SOC. An electrical battery model is developed in Matlab, Where the structure of the model is detailed by equations and blocks. The battery model has been validated from the experiment results. The comparison shows a good agreement in predicting the voltage, SOC estimation and the model performs better in SOC estimation.

Research on State of Charge Estimation for Power Battery of Electric Vehicle

2013 ◽  
Vol 336-338 ◽  
pp. 799-803
Author(s):  
Chang Fu Zong ◽  
Hai Ou Xiang ◽  
Lei He ◽  
Dong Xue Chen
Keyword(s):  
Estimation Method ◽  
Open Circuit ◽  
State Of Charge ◽  
Method Of Least Squares ◽  
Soc Estimation ◽  
Battery Model ◽  
Power Battery ◽  
Internal Parameters ◽  
Battery State Of Charge ◽  
State Of Charge Estimation

An optimized battery state of charge (SOC) estimation method has been proposed in this paper. The method is based on extended Kalman filter (EKF) and combines Ah counting method and open-circuit voltage (OCV) method. According to the current excitation-response of a battery, the internal parameters of the battery model were identified by the method of least squares. Then the proposed estimation method is verified by experiments. The results show that the estimation method can reduce the cumulative error caused by long discharge and it can estimate the battery SOC effectively and accurately.

scholarly journals SOC (STATE of CHARGE) THREE-CELL LEAD DYNAMIC BATTERY MODEL

2021 ◽  
Vol 13 (2) ◽  
pp. 49-59
Author(s):  
Kurriawan Budi Pranata ◽  
Freygion Ogiek Rizal Sukma ◽  
Muhammad Ghufron ◽  
Masruroh Masruroh
Keyword(s):  
State Of Charge ◽  
Battery Management System ◽  
Battery Management ◽  
Lead Acid Battery ◽  
Battery Model ◽  
Secondary Battery ◽  
Battery Technology ◽  
Battery Energy ◽  
Full Charge ◽  
Lead Acid

Three-cells dynamic lead-acid battery has been widely manufactured as the latest secondary battery technology. It is being carried out by 10 cycles of charge-discharge treatment with a various types of SoC, such as 100% (Full charge 5100 mAh), 50% (2550 mAh), 25% (1275 mAh) and discharge current of 0.8A. This experiment aims to analyze the treatment of SOC conditions on the performance of the lead-acid battery. The cyclicality test has performed using a Battery Management System (BMS) by applying an electric current at charging 1 A and discharging 0.8A. The results of the SOC charging conditions at 100%, 50%, 25% respectively gave a difference in the value of voltage efficiency of 84%, 87%, 88%, capacity efficiency values of 84%, 80%, 69%, energy efficiency values of 70%, 70%, 62%. The 100% and 50% SOC treatments showed better performance and battery energy the 25% SOC treatment. This research can be a recommendation to predict the performance of the lead-acid battery model during the charging and discharging process.

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