Comparative Analysis of Lithium-Ion Battery Resistance Estimation Techniques for Battery Management Systems

Models that can predict battery cells’ thermal and electrical behaviors are necessary for real-time battery management systems to regulate the imbalance within battery cells. This work introduces a Gaussian Process Regression (GPR)-based data-driven framework that succeeds the Multi-Scale Multi-Dimensional (MSMD) modeling structure. The framework can make highly accurate predictions at the same level as full-order full-distribution simulations based on MSMD. A pseudo-2D model is used to generate training data and is combined with a process that shifts computation burdens from real-time battery management systems to lab data preparation. The testing results highlight the reliability of the GPR-based data-driven framework in terms of accuracy and stability under various operational conditions.

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High End Battery Management Systems for Renewable Energy and EV Applications

Green ◽

10.1515/green-2012-0028 ◽

2013 ◽

Vol 3 (1) ◽

Cited By ~ 2

Author(s):

Max Jung ◽

Simon Schwunk

Keyword(s):

Lithium Ion ◽

Life Time ◽

High Energy ◽

High Energy Density ◽

Management Systems ◽

Battery Management ◽

Wind Generators ◽

Battery Management Systems ◽

Battery Systems ◽

Battery Packs

AbstractUsing renewable energies means having to deal with a strongly stochastic behaviour, since for photovoltaics the sun has to shine or for wind generators the wind has to blow. For being able to supply the load any time, storage solutions are needed. Decreasing costs and better availabilities of new battery technologies like lithium-ion therefore result in a growing demand for more sophisticated battery systems in off-grid and grid connected applications. In e.g. off-grid applications, lead-acid battery systems are state of the art. Though, lithium-ion batteries become more popular because of their high energy density and long life time. Another application for electrochemical storage systems are electric vehicles. In all those cases the battery storages need to be managed. But the management of a battery system is not a trivial problem. The batteries must be monitored and controlled, there are challenges regarding safety, electrical isolation and energy efficiency. The article gives an introduction to different architectures of battery management systems (BMS). There are different approaches to design a BMS the article describes in the first part. In the second part, there is a more precise description of the electronic hardware and the software behind a BMS. To understand both function and importance of a BMS, the article introduces in the third part a few applications of BMS in bigger battery packs.

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Battery Management Systems for Electric Vehicles using Lithium Ion Batteries

2019 Innovations in Power and Advanced Computing Technologies (i-PACT) ◽

10.1109/i-pact44901.2019.8959965 ◽

2019 ◽

Author(s):

V. Vaideeswaran ◽

S. Bhuvanesh ◽

M. Devasena

Keyword(s):

Lithium Ion Batteries ◽

Electric Vehicles ◽

Lithium Ion ◽

Management Systems ◽

Battery Management ◽

Battery Management Systems

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A Comparative Study of Open-Circuit-Voltage Estimation Algorithms for Lithium-Ion Batteries in Battery Management Systems

2019 6th International Conference on Control, Decision and Information Technologies (CoDIT) ◽

10.1109/codit.2019.8820292 ◽

2019 ◽

Cited By ~ 1

Author(s):

Jianwen Meng ◽

Moussa Boukhnifer ◽

Demba Diallo

Keyword(s):

Comparative Study ◽

Lithium Ion Batteries ◽

Open Circuit Voltage ◽

Lithium Ion ◽

Open Circuit ◽

Management Systems ◽

Battery Management ◽

Estimation Algorithms ◽

Battery Management Systems

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Characteristics of Battery Management Systems of Electric Vehicles with Consideration of the Active and Passive Cell Balancing Process

World Electric Vehicle Journal ◽

10.3390/wevj12030120 ◽

2021 ◽

Vol 12 (3) ◽

pp. 120

Author(s):

Muhammad Uzair ◽

Ghulam Abbas ◽

Saleh Hosain

Keyword(s):

Electric Vehicles ◽

Lithium Ion ◽

Management Systems ◽

Battery Management ◽

Comprehensive Overview ◽

Battery Modeling ◽

Vehicle Performance ◽

Efficient Operation ◽

Battery Management Systems ◽

Cell Balancing

Energy shortage and environmental pollution issues can be reduced considerably with the development and usage of electric vehicles (EVs). However, electric vehicle performance and battery lifespan depend on a suitable battery arrangement to meet the various battery performance demands. The safety, reliability, and efficiency of EVs largely depends on the constant monitoring of the batteries and management of battery packs. This work comprehensively reviews different aspects of battery management systems (BMS), i.e., architecture, functions, requirements, topologies, fundamentals of battery modeling, different battery models, issues/challenges, recommendations, and active and passive cell balancing approaches, etc., as compared to the existing works which normally discuss one or two aspects only. The work describes BMS functions, battery models and their comparisons in detail for an efficient operation of the battery pack. Similarly, the work presents a comprehensive overview of issues and challenges faced by BMS and also provides recommendations to address these challenges. Cell balancing is very important for the battery performance and in this work various cell balancing methodologies and their comparisons are also presented in detail. Modeling of a cell balancer is presented and a comparative study is also carried out for active and passive cell balance technique in MATLAB/Simulink with an eight cell battery packcell balancing approach. The result shows that the active cell balancing technique is more advantageous than passive balancing for electrical vehicles using lithium-ion batteries.

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