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Open AccessJournal ArticleDOI

A Critical Look at Coulomb Counting Approach for State of Charge Estimation in Batteries

Kiarash Movassagh, +3 more
- 06 Jul 2021 - 
- Vol. 14, Iss: 14, pp 4074
TLDR
This paper formally construct and quantify the state-of-charge estimate error during Coulomb counting due to four types of error sources, and presents methods for reducing time-cumulative and state- of-charge-proportional mistakes through simulation analysis.
Abstract
In this paper, we consider the problem of state-of-charge estimation for rechargeable batteries. Coulomb counting is a well-known method for estimating the state of charge, and it is regarded as accurate as long as the battery capacity and the beginning state of charge are known. The Coulomb counting approach, on the other hand, is prone to inaccuracies from a variety of sources, and the magnitude of these errors has not been explored in the literature. We formally construct and quantify the state-of-charge estimate error during Coulomb counting due to four types of error sources: (1) current measurement error; (2) current integration approximation error; (3) battery capacity uncertainty; and (4) timing oscillator error/drift. It is demonstrated that the state-of-charge error produced can be either time-cumulative or state-of-charge-proportional. Time-cumulative errors accumulate over time and have the potential to render the state-of-charge estimation utterly invalid in the long term.The proportional errors of the state of charge rise with the accumulated state of charge and reach their worst value within one charge/discharge cycle. The study presents methods for reducing time-cumulative and state-of-charge-proportional mistakes through simulation analysis.

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Citations
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Journal ArticleDOI

A novel fuzzy adaptive cubature Kalman filtering method for the state of charge and state of energy co-estimation of lithium-ion batteries

TL;DR: Based on the second-order resistor-capacitor equivalent circuit model and online parameter identification using variable forgetting factor recursive least square (VFF-RLS), a fuzzy adaptive controller is proposed to improve the convergence speed of the cubature Kalman filter (CKF) for the SOC estimation as mentioned in this paper .
Journal ArticleDOI

State of charge estimation for lithium-ion battery using Transformer with immersion and invariance adaptive observer

TL;DR: In this article , a Transformer neural-network is employed to predict the state of charge (SOC) of lithium-ion batteries with the sequence of current, voltage, and temperature data as inputs.
Journal ArticleDOI

Modeling Economic Sharing of Joint Assets in Community Energy Projects Under LV Network Constraints

TL;DR: In this paper, a heuristic-based battery control algorithm was proposed to maximize the self-consumption of local renewable energy generated and stored in assets that are typically connected to lowvoltage distribution networks.
Journal ArticleDOI

Battery Management System Algorithm for Energy Storage Systems Considering Battery Efficiency

TL;DR: The SoH can be predicted from the CC charging time of the battery and the battery efficiency, as proposed in this paper and the validity of the proposed BMS algorithm is demonstrated by applying it in a 3-kW ESS.
Journal ArticleDOI

An optimized relevant long short-term memory-squared gain extended Kalman filter for the state of charge estimation of lithium-ion batteries

TL;DR: In this paper , the effect of the training and testing working conditions on the accuracy of the state of charge (SOC) estimation using a long short-term memory (LSTM) network is studied through transfer learning.
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

A review on lithium-ion battery ageing mechanisms and estimations for automotive applications

TL;DR: In this paper, the authors present a summary of techniques, models, and algorithms used for battery ageing estimation, going from a detailed electrochemical approach to statistical methods based on data, and their respective characteristics are discussed.
Journal ArticleDOI

Simulation of capacity fade in lithium-ion batteries

TL;DR: In this paper, the authors reviewed the technical literature, including datasheets from battery manufacturers, to identify the major characteristics of capacity fade: impedance growth and capacity loss, and numerical simulations were used to explore the effect of porous electrodes on fade behavior.