Hybrid energy storage
systems: Materials,
devices, modeling, and
applications
Introduction
In smart grids and electric vehicles, the use of lithium-ion batteries can effectively reduce greenhouse gas
emissions, thus achieving environmental sustainability and low-carbon purposes. The performance
degradation and capacity decay phenomenon seriously restrict the power capacity of batteries, and the
problems of battery system mileage, lifespan and safety have become technical bottlenecks that restrict the
development of electric vehicles (Tang et al., 2019). Therefore, the management of the energy storage system is
important. Wang et al. (2020a) summarized the key problems in battery management systems. Liu et al. (2022a)
presented a critical review of AI-based manufacturing and management strategies for long-lifetime batteries. To
improve battery life, the hybrid energy storage system (HESS) has become one of the hot spots of energy
storage technology research. As a typical complex system, the HESS contains state coupling, input coupling,
environmental sensitivity, life decay and other characteristics. How to accurately estimate the internal states of the
system, improve the system lifespan, and realize the coordinated and optimal control of power and energy has
become the focus and difficulty of the HESS. The key issues for control and management in HESS have been
summarized by Wang et al. (2020b).
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Wang et 10.3389/fenrg.2022.990653
A HESS consists of two or more types of energy storage SOC and capacitance. The results indicated that the proposed
technologies, and the complementary features make the balancing method has a fast balancing speed and better
hybrid system outperform any single component, such as balancing efficiency.
batteries, flywheels, ultracapacitors, and fuel cells. HESSs
have recently gained broad application prospects in smart
grids, electric vehicles, electric ships, etc. The harmonic Conclusion
integration of multiple dynamic energy storage
technologies offers improved overall performance in HESSs are complex systems with the characteristics of
efficiency, reliability, financial profitability, and lifespan state coupling, environmental sensitivity and life attenuation.
compared with single energy storage devices. This research Accurately estimating the internal states of the system,
topic focuses on all aspects of advanced component energy improving the system lifespan, and realizing optimal control
storage devices and their integration for HESSs. of power and energy systems have become difficult problems.
In conclusion, this research topic provided key technologies in
HESSs, focusing on system modelling, state estimation, load
System modeling and state estimation prediction and energy management. The goal of this topic is
to provide new ideas and inspirations for the future study of
Accurate modeling such as equivalent circuit (Tang et al., HESSs.
2021) or electrochemical models (Liu et al., 2022b) and state
estimation are the basis of energy storage system management.
Moreover, the accurate estimation of the battery state-of-charge
(SOC) is crucial for providing information on the performance
and remaining range of electric vehicles. Several filter algorithms
are compared and evaluated by He et al. 2022 from the
perspectives of algorithm accuracy and complexity. There are
indeed many estimation methods for SOC, and good estimation
results have been achieved. Zhou et al. proposed an SOC
estimation method for lithium-ion batteries at the low-
capacity range. The approach has achieved good adaptability
to the estimation accuracy of low battery capacity SOC in
different cycle conditions. Fang et al. presented a hybrid data-
driven method to achieve accurate early predictions of battery
capacity and reliable analysis of battery component effects. The
research results have certain practical significance and
application value.
Power and energy management
It is of great significance to carry out research related to
improving the performance of lithium-ion batteries. Chen
et al. presented reliable electrode mass loading predictions
and effect analysis of manufacturing parameters of interest.
Lu et al. proposed a hierarchical power allocation strategy for
a CMC-based star-connected battery-SC HESS and solved the
challenge caused by the synchronous AC current on the
converter arms. The presented hierarchical control aims to
achieve asymmetrical power coordination by distributing the
output voltage of the SC and battery clusters. Battery
balancing is also important to the safe and reliable use of
batteries. Liu et al. (2022a) presented an active balancing
method for lithium-ion batteries in electric vehicles based on
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