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Open AccessJournal ArticleDOI

Reliable and Robust Observer for Simultaneously Estimating State-of-Charge and State-of-Health of LiFePO4 Batteries

TLDR
A reliable and robust observer is proposed which could estimate the SOC and SOH of LiFePO4 batteries simultaneously with high accuracy rates and the designed observer was proved by simulating ill-conditions that involve wrong initial estimates and wrong model parameters.
Abstract
Batteries are everywhere, in all forms of transportation, electronics, and constitute a method to store clean energy. Among the diverse types available, the lithium-iron-phosphate (LiFePO4) battery stands out for its common usage in many applications. For the battery’s safe operation, the state of charge (SOC) and state of health (SOH) estimations are essential. Therefore, a reliable and robust observer is proposed in this paper which could estimate the SOC and SOH of LiFePO4 batteries simultaneously with high accuracy rates. For this purpose, a battery model was developed by establishing an equivalent-circuit model with the ambient temperature and the current as inputs, while the measured output was adopted to be the voltage where current and terminal voltage sensors are utilized. Another vital contribution is formulating a comprehensive model that combines three parts: a thermal model, an electrical model, and an aging model. To ensure high accuracy rates of the proposed observer, we adopt the use of the dual extend Kalman filter (DEKF) for the SOC and SOH estimation of LiFePO4 batteries. To test the effectiveness of the proposed observer, various simulations and test cases were performed where the construction of the battery system and the simulation were done using MATLAB. The findings confirm that the best observer was a voltage-temperature (VT) observer, which could observe SOC accurately with great robustness, while an open-loop observer was used to observe the SOH. Furthermore, the robustness of the designed observer was proved by simulating ill-conditions that involve wrong initial estimates and wrong model parameters. The results demonstrate the reliability and robustness of the proposed observer for simultaneously estimating the SOC and SOH of LiFePO4 batteries.

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Citations
More filters

A Dynamic SOH-Coupled Lithium-Ion Cell Model for State and Parameter Estimation

TL;DR: In this paper , a SOH-coupled nonlinear electro-thermal-aging (ETA) model was proposed to estimate the state of charge (SOC), SOH, temperatures, and internal resistance using a filtering-based approach.
Journal ArticleDOI

Observer-Based Model Reference Tracking Control of the Markov Jump System with Partly Unknown Transition Rates

Weiqiang Song, +1 more
- 09 Jan 2023 - 
TL;DR: In this paper , a tracking control law composed of a feedforward compensator and a feedback control law was designed by calculating variations based on the designed observer, and a controller that can make the system stable under the condition that transition rates are partially unknown through the Lyapunov stability theory.
Journal ArticleDOI

A Dynamic SOH-Coupled Lithium-Ion Cell Model for State and Parameter Estimation

TL;DR: In this article , a SOH-coupled nonlinear electro-thermal aging (ETA) model was proposed to estimate the state of charge (SOC), SOH, temperatures, and internal resistance using a filtering-based approach.
Journal ArticleDOI

A hybrid CNN-BiLSTM approach for remaining useful life prediction of EVs lithium-Ion battery

TL;DR: In this paper , a hybrid neural network was proposed to improve the accuracy and stability of lithium-ion battery remaining useful life (RUL) prediction by using one dimensional convolutional neural network and bidirectional long short-term memory (BiLSTM) neural network simultaneously.
Proceedings ArticleDOI

Intelligent Control for Wind Turbines Connected to Utility Grid using MPC

TL;DR: In this article , an intelligent control system for the synchronous generator wind turbines using the model predictive controller (MPC) was proposed, where the coordination of pitch/torque sharing depend on the analysis performed, both generator power output quality, in addition load circumstances are maximized in a variable weight MPC technique.
References
More filters
Journal ArticleDOI

Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs: Part 2. Modeling and identification

TL;DR: In this article, an extended Kalman filter (EKF) was used to estimate the battery state of charge, power fade, capacity fade, and instantaneous available power of a hybrid electric vehicle battery pack.
Journal ArticleDOI

Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs: Part 3. State and parameter estimation

TL;DR: In this article, extended Kalman filtering (EKF) is used to estimate battery state-of-charge, power fade, capacity fade, and instantaneous available power for hybrid-electric-vehicle battery packs.
Journal ArticleDOI

Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs Part 1. Background

TL;DR: In this paper, an extended Kalman filter (EKF) was proposed to estimate the battery state of charge, power fade, capacity fade, and instantaneous available power of a hybrid-electric-vehicle battery pack.
Journal ArticleDOI

Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles

TL;DR: In this paper, the methods for monitoring the battery state of charge, capacity, impedance parameters, available power, state of health, and remaining useful life are reviewed with the focus on elaboration of their strengths and weaknesses for the use in on-line BMS applications.
Journal ArticleDOI

Optimal Charging of Li-Ion Batteries With Coupled Electro-Thermal-Aging Dynamics

TL;DR: This paper proposes an innovative approach to devising optimally health-conscious fast-safe charge protocols using the Legendre–Gauss–Radau pseudospectral method with adaptive multi-mesh-interval collocation to solve the resulting highly nonlinear six-state optimal control problem.
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