Embedded Fiber Optic Sensing for Accurate State Estimation in Advanced Battery Management Systems

2014 ◽  
Vol 1681 ◽  
Author(s):  
Lars Wilko Sommer ◽  
Ajay Raghavan ◽  
Peter Kiesel ◽  
Bhaskar Saha ◽  
Tobias Staudt ◽  
...  
Keyword(s):  
State Estimation ◽  
Fiber Optic ◽  
Lithium Ion ◽  
Management Systems ◽  
Battery Management ◽  
Cell State ◽  
Battery Management Systems ◽  
Fbg Sensors ◽  
Selective Sensitivity ◽  
Interesting Alternative

ABSTRACTThe problems of using performance parameters such as voltage, current and temperature measured with electrical sensors in today’s battery management systems (BMS) are well known. These parameters can be weakly informative about cell state, particularly as cells age, and contribute to over-conservative utilization and oversizing of a battery pack. Fiber optic (FO) sensors can offer an interesting alternative to conventional electrical sensors, with several advantages such as high selective sensitivity to various parameters, light weight, robustness to EMI, and multiplexing capabilities. In this study, a particular type of FO sensors, fiber Bragg grating (FBG) sensors were externally attached to lithium ion pouch cells for monitoring additional informative cell parameter such as strain and temperature. Multiple charge and discharge cycle were performed to examine the qualification of these signals for cell state estimation in BMS. In comparison to corresponding measurements using conventional electrical sensors, the FBG signals showed very promising results for utilization in effective BMS.

scholarly journals Fiber Optic Sensing Technologies for Battery Management Systems and Energy Storage Applications

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1397
Author(s):  
Yang-Duan Su ◽  
Yuliya Preger ◽  
Hannah Burroughs ◽  
Chenhu Sun ◽  
Paul Ohodnicki
Keyword(s):  
Energy Storage ◽  
Fiber Optics ◽  
Fiber Optic ◽  
Gas Sensing ◽  
Fiber Optic Sensors ◽  
Management Systems ◽  
Practical Implementation ◽  
Battery Management ◽  
Battery Management Systems ◽  
Battery Systems

Applications of fiber optic sensors to battery monitoring have been increasing due to the growing need of enhanced battery management systems with accurate state estimations. The goal of this review is to discuss the advancements enabling the practical implementation of battery internal parameter measurements including local temperature, strain, pressure, and refractive index for general operation, as well as the external measurements such as temperature gradients and vent gas sensing for thermal runaway imminent detection. A reasonable matching is discussed between fiber optic sensors of different range capabilities with battery systems of three levels of scales, namely electric vehicle and heavy-duty electric truck battery packs, and grid-scale battery systems. The advantages of fiber optic sensors over electrical sensors are discussed, while electrochemical stability issues of fiber-implanted batteries are critically assessed. This review also includes the estimated sensing system costs for typical fiber optic sensors and identifies the high interrogation cost as one of the limitations in their practical deployment into batteries. Finally, future perspectives are considered in the implementation of fiber optics into high-value battery applications such as grid-scale energy storage fault detection and prediction systems.

scholarly journals A Data-Driven Framework to Predict Lithium-Ion Battery Cell Imbalance for Real-Time Battery Management Systems

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8492
Author(s):  
Chao Li ◽  
Assimina A. Pelegri
Keyword(s):  
Real Time ◽  
Lithium Ion ◽  
Training Data ◽  
Data Driven ◽  
Management Systems ◽  
Battery Management ◽  
Battery Cell ◽  
Operational Conditions ◽  
Battery Management Systems ◽  
Battery Cells

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.

High End Battery Management Systems for Renewable Energy and EV Applications

Green ◽  
2013 ◽  
Vol 3 (1) ◽  
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.

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

Energies ◽  
2018 ◽  
Vol 11 (6) ◽  
pp. 1490 ◽  
Author(s):  
Manoj Mathew ◽  
Stefan Janhunen ◽  
Mahir Rashid ◽  
Frank Long ◽  
Michael Fowler
Keyword(s):  
Comparative Analysis ◽  
Lithium Ion Battery ◽  
Lithium Ion ◽  
Management Systems ◽  
Battery Management ◽  
Estimation Techniques ◽  
Battery Management Systems
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