scholarly journals State of Charge Estimation of Composite Energy Storage Systems with Supercapacitors and Lithium Batteries

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Kai Wang ◽  
Chunli Liu ◽  
Jianrui Sun ◽  
Kun Zhao ◽  
Licheng Wang ◽  
...  
Keyword(s):  
Energy Storage ◽  
Kalman Filtering ◽  
Lithium Batteries ◽  
Estimation Error ◽  
Storage System ◽  
Energy Storage System ◽  
Least Square ◽  
Recursive Least Square ◽  
Soc Estimation ◽  
Composite Energy

This paper studies the state of charge (SOC) estimation of supercapacitors and lithium batteries in the hybrid energy storage system of electric vehicles. According to the energy storage principle of the electric vehicle composite energy storage system, the circuit models of supercapacitors and lithium batteries were established, respectively, and the model parameters were identified online using the recursive least square (RLS) method and Kalman filtering (KF) algorithm. Then, the online estimation of SOC was completed based on the Kalman filtering algorithm and unscented Kalman filtering algorithm. Finally, the experimental platform for SOC estimation was built and Matlab was used for calculation and analysis. The experimental results showed that the SOC estimation results reached a high accuracy, and the variation range of estimation error was [−0.94%, 0.34%]. For lithium batteries, the recursive least square method is combined with the 2RC model to obtain the optimal result, and the estimation error is within the range of [−1.16%, 0.85%] in the case of comprehensive weighing accuracy and calculation amount. Moreover, the system has excellent robustness and high reliability.

scholarly journals SOC Estimation of Lead Carbon Batteries Based on the Operating Conditions of an Energy Storage System in a Microgrid System

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 33
Author(s):  
Yuanyuan Chen ◽  
Zilong Yang ◽  
Yibo Wang
Keyword(s):  
Wavelet Transform ◽  
Energy Storage ◽  
Storage System ◽  
Estimation Method ◽  
Energy Storage System ◽  
Operating Conditions ◽  
Estimation Methods ◽  
Extend Kalman Filter ◽  
Practical Applications ◽  
Soc Estimation

The environment for practical applications of an energy storage system (ESS) in a microgrid system is very harsh, and therefore actual operating conditions become complex and changeable. In addition, the signal of the ESS sampling process contains a great deal of system and measurement noise, the sampled current fluctuates significantly, and also has high frequency. In this case, under such conditions, it is difficult to accurately estimate the state of charge (SOC) of the batteries in the ESS by common estimation methods. Therefore, this study proposes a compound SOC estimation method based on wavelet transform. This algorithm is very suitable for microgrid systems with large current, frequent fluctuating conditions, and high noise interference. The experimental results and engineering data show that the relative error of the method is 0.5%, which is much lower than the extend Kalman filter (EKF) based on wavelet transform.

scholarly journals Research on Dynamic Equivalent SOC Estimation of Hybrid Energy Storage System Based on Sliding Mode Observer

2021 ◽  
Vol 9 ◽  
Author(s):  
Yifei Wang ◽  
Wei Jiang ◽  
Chengwei Zhu ◽  
Zhiqi Xu ◽  
Yifan Deng
Keyword(s):  
Energy Storage ◽  
Real Time ◽  
Sliding Mode ◽  
Storage System ◽  
Estimation Method ◽  
Energy Storage System ◽  
Sliding Mode Observer ◽  
Hybrid Energy ◽  
Soc Estimation ◽  
Hybrid Energy Storage

This article proposes a sliding mode observer based dynamic equivalent state of charge (ESOC) estimation method for hybrid energy storage system (HESS). Since different types of energy storage components and power electronics circuit are coupled in the HESS, the traditional SOC estimation method cannot reflect the real-time operation characteristics of the HESS. To tackle this problem, a sliding mode observer based on the model of the HESS is built in this article. By collecting the corresponding voltage and current signals, the internal parameters of energy storage elements can be observed accurately in real time. The dynamic ESOC is further defined with the idea of real-time charge balance to reflect the accurate available capacity of the HESS. Finally, the simulation results based on MATLAB/Simulink model are given to verify the feasibility of the proposed dynamic ESOC.

scholarly journals SOC Estimation of Lithium-Ion Battery Based on Kalman Filter Algorithm for Energy Storage System in Microgrids

2018 ◽  
Vol 57 ◽  
pp. 02006 ◽  
Author(s):  
Dae-Won Chung ◽  
Seung-Hak Yang
Keyword(s):  
Kalman Filter ◽  
Energy Storage ◽  
Power Systems ◽  
Lithium Ion Battery ◽  
Storage System ◽  
Lithium Ion ◽  
Energy Storage System ◽  
Accurate Estimation ◽  
Soc Estimation ◽  
Internal States

State-of-charge (SOC) is one of the vital factors for the energy storage system (ESS) in the microgrid power systems to guarantee that a battery system is operating in a safe and reliable manner for the system. Many uncertainties and noises, such as nonlinearities in the internal states of a battery, sensor measurement accuracy and bias, temperature effects, calibration errors, and sensor failures, pose a challenge to the accurate estimation of SOC in most applications. This study makes two contributions to the existing literatures. First, a more accurate extended Kalman filter (EKF) algorithm is proposed to estimate the battery nonlinear dynamics. Due to its discrete form and ease of implementation, this straightforward approach could be more suitable for real applications on the ESS. Second, its order selection principle and parameter identification method are illustrated in detail. It can accurately demonstrate the characteristics of the lithium-ion battery to show the feasibility and effectiveness of the algorithm for the ESS.

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