Journal ArticleDOI
Genetic Algorithm Driven Generic Estimation Model of Lithium-Ion Battery for Energy Balance Calculation in Spacecraft
TLDR
The proposed genetic algorithm driven generic estimation - energy balance (GAGE-EB) model uses cell open circuit voltage characteristics, internal resistance ($r_{\text{int}}$) characteristics, and coulomb counting to estimate deliverable capacity and internal resistance in lithium-ion battery.Abstract:
Lithium-ion battery is generally used as energy storage device in spacecraft and other applications. Spacecraftbattery modeling and energy balance estimation is critical. The proposed genetic algorithm driven generic estimation - energy balance (GAGE-EB) model uses cell open circuit voltage characteristics, internal resistance ( $r_{\text{int}}$ ) characteristics, and coulomb counting. The cell characteristics are obtained by offline tests. For series-parallel or parallel-series configured battery, the model estimates deliverable capacity and internal resistance by accurately matching the terminal voltage. Estimated parameters are used to check the energy balance for new load and generation profiles. The GAGE-EB model is validated for electrical performance with various cell types and battery configurations with respect to experimental data and is within 1% and 2% accuracy for voltage and capacity estimation, respectively.read more
Citations
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Journal ArticleDOI
A power loss minimization strategy based on optimal placement and sizing of distributed energy resources
Sohrab Mirsaeidi,Shang Li,Subash Devkota,Meng Li,Jinghan He,Dimitrios Tzelepis,Charalambos Konstantinou,Dalila Mat Said +7 more
TL;DR: In this article , the authors proposed a GA-based strategy for minimizing active and reactive power losses through optimal location and size of DGs and quantified and tallies the total network power losses for the cases with random as well as optimal allocation of generators.
Journal ArticleDOI
Reinforcement of Power System Performance Through Optimal Allotment of Distributed Generators Using Metaheuristic Optimization Algorithms
Sohrab Mirsaeidi,Shangru Li,Subash Devkota,Jinghan He,Meng Li,Xijun Wang,Charalambos Konstantinou,Dalila Mat Said,Kashem M. Muttaqi +8 more
TL;DR: In this article , the optimal size and location of DGs using metaheuristic optimization algorithms so that the network performance is enhanced was explored. But the authors did not consider the impact of enhancement in the number of DG on different aspects of power system performance.
References
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Journal ArticleDOI
An Introduction to Genetic Algorithms.
TL;DR: An Introduction to Genetic Algorithms as discussed by the authors is one of the rare examples of a book in which every single page is worth reading, and the author, Melanie Mitchell, manages to describe in depth many fascinating examples as well as important theoretical issues.
Journal ArticleDOI
The Li-ion rechargeable battery: a perspective.
John B. Goodenough,Kyusung Park +1 more
TL;DR: New strategies are needed for batteries that go beyond powering hand-held devices, such as using electrode hosts with two-electron redox centers; replacing the cathode hosts by materials that undergo displacement reactions; and developing a Li(+) solid electrolyte separator membrane that allows an organic and aqueous liquid electrolyte on the anode and cathode sides, respectively.
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.
Proceedings ArticleDOI
A Generic Battery Model for the Dynamic Simulation of Hybrid Electric Vehicles
TL;DR: In this paper, an easy-to-use battery model applied to dynamic simulation software is presented, which uses only the battery State-Of-Charge (SOC) as a state variable in order to avoid the algebraic loop problem.
Journal ArticleDOI
Data-driven prediction of battery cycle life before capacity degradation
Kristen A. Severson,Peter M. Attia,Norman Jin,Nicholas Perkins,Benben Jiang,Zi Yang,Michael H. Chen,Muratahan Aykol,Patrick Herring,Dimitrios Fraggedakis,Martin Z. Bazant,Stephen J. Harris,Stephen J. Harris,William C. Chueh,Richard D. Braatz +14 more
TL;DR: In this article, a machine learning method was used to predict battery lifetime before the onset of capacity degradation with high accuracy. But, the prediction often cannot be made unless a battery has already degraded significantly.