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 New Cell Balancing Charging System Research for Lithium-ion Batteries

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1393
Author(s):  
Chan-Yong Zun ◽  
Sang-Uk Park ◽  
Hyung-Soo Mok
Keyword(s):  
High Capacity ◽  
Lithium Ion ◽  
High Energy ◽  
High Energy Density ◽  
Battery Management ◽  
Battery Cell ◽  
Charging System ◽  
Charging Time ◽  
Battery Management Systems ◽  
Cell Balancing

With recent advancements in the electrical industry, the demand for high capacity and high energy density batteries has increased, subsequently increasing the demand for fast and reliable battery charging. A battery is an assembly of a plurality of cells, in which maintaining a balance between neighboring cells is crucial for stable charging. To this end, various methods have been applied to battery management systems. Representative methods for maintaining the balance in battery cells include a passive method of adjusting the balance using a resistor and an active method involving the exchange of energy between the cells. However, these methods are limited in terms of efficiency, lifespan, and charging time. Therefore, in this study, we propose a new charging method at the battery cell level and demonstrate its effectiveness through experiments.

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.

Estimation of Remaining Useful Lifetime of Lithium-Ion Battery Based on Acoustic Emission Measurements

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Nejra Beganovic ◽  
Dirk Söffker
Keyword(s):  
Acoustic Emission ◽  
Lithium Ion Battery ◽  
Lithium Ion ◽  
High Energy ◽  
High Energy Density ◽  
Storage Device ◽  
Health State ◽  
Battery Management ◽  
Application Fields ◽  
Useful Lifetime

Lithium-ion battery (LIB) utilization as energy storage device in electric and hybrid-electric vehicles, wind turbine systems, a number of portable electrical devices, and in many other application fields is encouraged due to LIB small size alongside high energy density. Monitoring of LIB health state parameters, calculation of additional LIB operating parameters, and the fulfillment of safety requirements are provided through battery management systems. Prediction of remaining useful lifetime (RUL) of LIB and state-of-health (SoH) estimation are identified as still challenging and not completely solved tasks. In this contribution, previous works on RUL/SoH estimation, mainly relied on modeling of underlying electrochemical processes inside LIB, are compared with newly developed approach. The proposed approach utilizes acoustic emission measurements for LIB aging indicators estimation. Developed model for RUL estimation is closely related to frequency spectrum analysis of captured acoustic emission (AE) signal. Features selected from AE measurements are considered as model inputs. The novelty of this approach is the opportunity to estimate RUL/SoH of LIB without necessity to capture some intermediate variables, only indirectly related to RUL/SoH (charging/discharging currents, temperature, and similar). The proposed approach provides the possibility to obtain reliable information about current RUL/SoH without the knowledge about underlying physical processes occurred in LIB. Experimental data sets gathered from LIB aging tests are used for model establishment, training, and validation. The experimental results demonstrate the applicability of the novel approach.

scholarly journals Next-Generation Battery Management Systems: Dynamic Reconfiguration

2020 ◽  
Author(s):  
Weiji Han ◽  
Torsten Wik ◽  
Anton Kersten ◽  
Guangzhong Dong ◽  
Changfu Zou
Keyword(s):  
Large Scale ◽  
Dynamic Reconfiguration ◽  
Management Systems ◽  
Future Research ◽  
Battery Management ◽  
Next Generation ◽  
Battery System ◽  
Battery Management Systems ◽  
Battery Systems ◽  
Battery Cells

<div>Batteries are widely applied to the energy storage and power supply in portable electronics, transportation, power systems, communication networks, etc. They are particularly demanded in the emerging technologies of vehicle electrification and renewable energy integration for a green and sustainable society. To meet various voltage, power, and energy requirements in large-scale applications, multiple battery cells have to be connected in series and/or parallel. While battery technology has advanced significantly in the past decade, existing battery management systems (BMSs) mainly focus on state monitoring and control of battery systems packed in fixed configurations. In fixed configurations, though, the battery system performance is in principle limited by the weakest cells, which can leave large parts severely underutilized. Allowing dynamic reconfiguration of battery cells, on the other hand, allows individual and flexible manipulation of the battery system at cell, module, and pack levels, which may open up a new paradigm for battery management. Following this trend, this paper provides an overview of next-generation BMSs featuring dynamic reconfiguration. Motivated by numerous potential benefits of reconfigurable battery systems (RBSs), the hardware designs, management principles, and optimization algorithms for RBSs are sequentially and systematically discussed. Theoretical and practical challenges during the design and implementation of RBSs are highlighted in the end to stimulate future research and development.</div>

scholarly journals Next-Generation Battery Management Systems: Dynamic Reconfiguration

2020 ◽  
Author(s):  
Weiji Han ◽  
Torsten Wik ◽  
Anton Kersten ◽  
Guangzhong Dong ◽  
Changfu Zou
Keyword(s):  
Large Scale ◽  
Dynamic Reconfiguration ◽  
Management Systems ◽  
Future Research ◽  
Battery Management ◽  
Next Generation ◽  
Battery System ◽  
Battery Management Systems ◽  
Battery Systems ◽  
Battery Cells

<div>Batteries are widely applied to the energy storage and power supply in portable electronics, transportation, power systems, communication networks, etc. They are particularly demanded in the emerging technologies of vehicle electrification and renewable energy integration for a green and sustainable society. To meet various voltage, power, and energy requirements in large-scale applications, multiple battery cells have to be connected in series and/or parallel. While battery technology has advanced significantly in the past decade, existing battery management systems (BMSs) mainly focus on state monitoring and control of battery systems packed in fixed configurations. In fixed configurations, though, the battery system performance is in principle limited by the weakest cells, which can leave large parts severely underutilized. Allowing dynamic reconfiguration of battery cells, on the other hand, allows individual and flexible manipulation of the battery system at cell, module, and pack levels, which may open up a new paradigm for battery management. Following this trend, this paper provides an overview of next-generation BMSs featuring dynamic reconfiguration. Motivated by numerous potential benefits of reconfigurable battery systems (RBSs), the hardware designs, management principles, and optimization algorithms for RBSs are sequentially and systematically discussed. Theoretical and practical challenges during the design and implementation of RBSs are highlighted in the end to stimulate future research and development.</div>

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.

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