Journal ArticleDOI
State of Charge Estimation of Lithium-Ion Batteries in Electric Drive Vehicles Using Extended Kalman Filtering
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TLDR
A more accurate battery state of charge (SOC) estimation method for electric drive vehicles is developed based on a nonlinear battery model and an extended Kalman filter supported by experimental data.Abstract:
In this paper, a more accurate battery state of charge (SOC) estimation method for electric drive vehicles is developed based on a nonlinear battery model and an extended Kalman filter (EKF) supported by experimental data. A nonlinear battery model is constructed by separating the model into a nonlinear open circuit voltage and a two-order resistance-capacitance model. EKF is used to eliminate the measurement and process noise and remove the need of prior knowledge of initial SOC. A hardware-in-the-loop test bench was built to validate the method. The experimental results show that the proposed method can estimate the battery SOC with high accuracy.read more
Citations
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Journal ArticleDOI
Towards a Smarter Battery Management System for Electric Vehicle Applications: A Critical Review of Lithium-Ion Battery State of Charge Estimation
Muhammad Umair Ali,Amad Zafar,Sarvar Hussain Nengroo,Sadam Hussain,Muhammad Junaid Alvi,Hee-Je Kim +5 more
TL;DR: In this paper, Li-ion batteries have attracted considerable attention in the EV industry owing to their high energy density, lifespan, nominal voltage, power density, and cost, and a smart battery management system is one of the essential components; it not only measures the states of battery accurately, but also ensures safe operation and prolongs the battery life.
Journal ArticleDOI
SoC Estimation for Lithium-ion Batteries: Review and Future Challenges
TL;DR: A review of state of charge (SoC) estimation for lithium-ion batteries is presented in this article, focusing on the description of the techniques and the elaboration of their weaknesses for the use in online battery management systems (BMS) applications.
Journal ArticleDOI
Neural Network Approach for Estimating State of Charge of Lithium-Ion Battery Using Backtracking Search Algorithm
Mahammad A. Hannan,Molla Shahadat Hossain Lipu,Aini Hussain,Mohamad Hanif Md Saad,Afida Ayob +4 more
TL;DR: The obtained results show that the BPNN based BSA model outperforms other neural network models in estimating SOC with high accuracy under different EV profiles and temperatures.
Journal ArticleDOI
State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles
TL;DR: In this paper, Li et al. focused on battery state estimation and its issues and challenges by exploring different existing estimation methodologies, such as adaptive filter algorithm, learning algorithm, nonlinear observer, and hybrid method.
Journal ArticleDOI
Lithium-Ion Battery Parameters and State-of-Charge Joint Estimation Based on H-Infinity and Unscented Kalman Filters
TL;DR: This paper proposes a joint SoC estimation method, where battery model parameters are estimated online using the H-infinity filter, while the SoC are estimated using the unscented Kalman filter, and shows that the proposed method possesses high accuracy, fast convergence, excellent robustness and adaptability.
References
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Journal ArticleDOI
Accurate electrical battery model capable of predicting runtime and I-V performance
Min Chen,Gabriel A. Rincon-Mora +1 more
TL;DR: An accurate, intuitive, and comprehensive electrical battery model is proposed and implemented in a Cadence environment that accounts for all dynamic characteristics of the battery, from nonlinear open-circuit voltage, current-, temperature-, cycle number-, and storage time-dependent capacity to transient response.
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
Dynamic lithium-ion battery model for system simulation
TL;DR: In this article, the authors present a complete dynamic model of a lithium ion battery that is suitable for virtual prototyping of portable battery-powered systems, based on publicly available data such as the manufacturers' data sheets.