Using Pseudo-Two-Dimensional (P2D) Reformulation Model with a Particle Filter to Estimate State of Charge, State of Health, and Remaining Useful Life in Li-Ion Battery Management System (BMS)

2015 ◽  
Keyword(s):  
Particle Filter ◽  
Remaining Useful Life ◽  
State Of Charge ◽  
Battery Management System ◽  
Battery Management ◽  
Two Dimensional ◽  
State Of Health ◽  
Li Ion Battery ◽  
Li Ion ◽  
Useful Life

scholarly journals Estimation of State of Charge (SoC) Using Modified Coulomb Counting Method With Open Circuit Compensation For Battery Management System (BMS)

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Puspita Ningrum ◽  
Novie Ayub Windarko ◽  
Suhariningsih Suhariningsih
Keyword(s):  
Management System ◽  
Voltage Divider ◽  
Open Circuit ◽  
Voltage Sensor ◽  
State Of Charge ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Battery ◽  
Control Center ◽  
Li Ion

Abstract— Battery is one of the important components in the development of renewable energy technology. This paper presents a method for estimating the State of Charge (SoC) for a 4Ah Li-ion battery. State of Charge (SoC) is the status of the capacity in the battery in the form of a percentage which makes it easier to monitor the battery during use. Coulomb calculations are widely used, but this method still contains errors during integration. In this paper, SoC measurement using Open Circuit Voltage Compensation is used for the determination of the initial SoC, so that the initial SoC reading is more precise, because if the initial SoC reading only uses a voltage sensor, the initial SoC reading is less precise which affects the next n second SoC reading. In this paper, we present a battery management system design or commonly known as BMS (Battery Management System) which focuses on the monitoring function. BMS uses a voltage sensor in the form of a voltage divider circuit and an ACS 712 current sensor to send information about the battery condition to the microcontroller as the control center. Besides, BMS is equipped with a protection relay to protect the battery. The estimation results of the 12volt 4Ah Li-ion battery SoC with the actual reading show an error of less than 1%.Keywords—Battery Management System, Modified Coulomb Counting, State of Charge.

Diagnostics and Prognostics of Lithium-Ion Batteries

2015 ◽  
Author(s):  
Zhimin Xi ◽  
Rong Jing ◽  
Cheol Lee
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Remaining Useful Life ◽  
State Of Charge ◽  
Data Driven ◽  
State Of Health ◽  
Li Ion Batteries ◽  
Battery State Of Charge ◽  
Li Ion ◽  
Useful Life

This paper investigates recent research on battery diagnostics and prognostics especially for Lithium-ion (Li-ion) batteries. Battery diagnostics focuses on battery models and diagnosis algorithms for battery state of charge (SOC) and state of health (SOH) estimation. Battery prognostics elaborates data-driven prognosis algorithms for predicting the remaining useful life (RUL) of battery SOC and SOH. Readers will learn not only basics but also very recent research developments on battery diagnostics and prognostics.

Implementation of the Li-Ion Battery Management System Based on DS2438

2015 ◽  
Vol 733 ◽  
pp. 714-717 ◽  
Author(s):  
Ping Yang ◽  
Hou Yu Yu ◽  
Yong Gang Yan
Keyword(s):  
Management System ◽  
State Of Charge ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Batteries ◽  
Li Ion Battery ◽  
Electric Cars ◽  
Power Battery ◽  
Electric Vehicle Battery ◽  
Li Ion

In order to ensure good performance and extend the lifetime of li-ion batteries in electric cars, effective real-time monitoring and management must be valued. This paper designs an electric vehicle battery management system based on a smart battery monitoring chip, DS2438. It integrates the measurement of battery's temperature, voltage, current, and power as a whole, which not only simplifies the circuit, but also saves system cost. The battery’s SOC (State Of Charge) can be easily estimated and displayed in this design. It improves the reliability of power battery pack and prolonged its life, which can be used as reference to battery management system design and application.

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 Takagi–Sugeno Observer Design for Remaining Useful Life Estimation of Li-Ion Battery System Under Faults

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1537
Author(s):  
Norbert Kukurowski ◽  
Marcin Pazera ◽  
Marcin Witczak
Keyword(s):  
Current Measurement ◽  
The State ◽  
Remaining Useful Life ◽  
Observer Design ◽  
State Of Charge ◽  
Li Ion Battery ◽  
Battery System ◽  
Li Ion ◽  
Useful Life ◽  
Takagi Sugeno

Among the existing estimation schemes of a battery state of charge, most deal with an assumption that the faults will never occur in the system. Nevertheless, faults may have a crucial impact on the state of charge estimation accuracy. The paper proposes a novel observer design to estimate the state of charge and the remaining useful life of a Li-ion battery system under voltage and current measurement faults. The approach starts with converting the battery system into the descriptor Takagi–Sugeno form, where the state includes the original states along with the voltage and current measurement faults. Moreover, external disturbances are bounded by an ellipsoid based on the so-called Quadratic Boundedness approach, which ensures the system stability. The second-order Resistor-Capacitor equivalent circuit model is considered to verify the performance and correctness of the proposed observer. Subsequently, a real battery model is designed with experimental data of the Li-ion 18650 battery delivered from the NASA benchmark. Another experiment deals with an automated guided vehicle fed with a battery of which the remaining useful life is estimated. Finally, the results are compared with another estimation scheme based on the same benchmark.

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