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Lithium-ion batteries exhibit a dynamic voltage behaviour depending nonlinearly on current and state of charge. The modelling of lithium-ion batteries is therefore complicated and model parametrisation is often time demanding. Grey-box models combine physical and data-driven modelling to benefit from their respective advantages. Neural ordinary differential equations (NODEs) offer new possibilities for grey-box modelling. Differential equations given by physical laws and NODEs can be combined in a single modelling framework. Here we demonstrate the use of NODEs for grey-box modelling of lithium-ion batteries. A simple equivalent circuit model serves as a basis and represents the physical part of the model. The voltage drop over the resistor–capacitor circuit, including its dependency on current and state of charge, is implemented as a NODE. After training, the grey-box model shows good agreement with experimental full-cycle data and pulse tests on a lithium iron phosphate cell. We test the model against two dynamic load profiles: one consisting of half cycles and one dynamic load profile representing a home-storage system. The dynamic response of the battery is well captured by the model.

Lithium-ion batteries exhibit a dynamic voltage behaviour depending nonlinearly on current and state of charge. The modelling of lithium-ion batteries is therefore complicated and model parametrisation is often time demanding. Grey-box models combine physical and data-driven modelling to benefit from their respective advantages. Neural ordinary differential equations (NODEs) offer new possibilities for grey-box modelling. Differential equations given by physical laws and NODEs can be combined in a single modelling framework. Here we demonstrate the use of NODEs for grey-box modelling of lithium-ion batteries. A simple equivalent circuit model serves as a basis and represents the physical part of the model. The voltage drop over the resistor–capacitor circuit, including its dependency on current and state of charge, is implemented as a NODE. After training, the grey-box model shows good agreement with experimental full-cycle data and pulse tests on a lithium iron phosphate cell. We test the model against two dynamic load profiles: one consisting of half cycles and one dynamic load profile representing a home-storage system. The dynamic response of the battery is well captured by the model.

Spinel LiNi0.5Mn1.5O4 as one of the high-energy positive electrode materials for next generation Li-ion batteries has attracted significant interest due to its economic and environmental advantages. However, the sensitivity of this type of material upon short to long term ambient storage conditions and the impact on the electrochemical performances remains poorly explored. Nevertheless, this remains an important aspect for practical large-scale synthesis, storage and utilization. Herein, we study and compare the evolution of surface chemistry, bulk crystal structure and elemental content evolution and distribution of LiNi0.5Mn1.5O4 using a variety of characterization techniques including XPS and STEM-EDS-EELS, as well as electrochemical analysis. We show that Mn species dominate the outer surface (0–5 nm), while Ni and Li are preferentially located further away and in the bulk. The studied LiNi0.5Mn1.5O4 material is found to be stable, with minor changes in surface or bulk characteristics detected, even after 12 months of storage under ambient air conditions. The low surface reactivity to air also accounts for the minor changes to the electrochemical performance of the air-exposed LiNi0.5Mn1.5O4, compared to the pristine material. This study provides guidance for the appropriate storage, handling and processing of this high-performance cathode material.

Spinel LiNi0.5Mn1.5O4 as one of the high-energy positive electrode materials for next generation Li-ion batteries has attracted significant interest due to its economic and environmental advantages. However, the sensitivity of this type of material upon short to long term ambient storage conditions and the impact on the electrochemical performances remains poorly explored. Nevertheless, this remains an important aspect for practical large-scale synthesis, storage and utilization. Herein, we study and compare the evolution of surface chemistry, bulk crystal structure and elemental content evolution and distribution of LiNi0.5Mn1.5O4 using a variety of characterization techniques including XPS and STEM-EDS-EELS, as well as electrochemical analysis. We show that Mn species dominate the outer surface (0–5 nm), while Ni and Li are preferentially located further away and in the bulk. The studied LiNi0.5Mn1.5O4 material is found to be stable, with minor changes in surface or bulk characteristics detected, even after 12 months of storage under ambient air conditions. The low surface reactivity to air also accounts for the minor changes to the electrochemical performance of the air-exposed LiNi0.5Mn1.5O4, compared to the pristine material. This study provides guidance for the appropriate storage, handling and processing of this high-performance cathode material.

Global fossil fuel reserves are declining due to differential uses, especially for power generation. Everybody can help to do their bit for the environment by using solar energy. Geographically, Bangladesh is a potential zone for harnessing solar energy. In March 2021, the renewable generation capacity in Bangladesh amounted to 722.592 MW, including 67.6% from solar, 31.84% from hydro, and 0.55% from other energy sources, including wind, biogas, and biomass, where 488.662 MW of power originated from over 6 million installed solar power systems. Concurrently, over 42% of rural people still suffer from a lack of electricity, where solar energy can play a vital role. This paper highlights the present status of various forms of solar energy progress in Bangladesh, such as solar parks, solar rooftops, solar irrigation, solar charging stations, solar home systems, solar-powered telecoms, solar street lights, and solar drinking water, which can be viable alternative sources of energy. This review will help decision-makers and investors realize Bangladesh’s up-to-date solar energy scenario and plan better for the development of a sustainable society.

Global fossil fuel reserves are declining due to differential uses, especially for power generation. Everybody can help to do their bit for the environment by using solar energy. Geographically, Bangladesh is a potential zone for harnessing solar energy. In March 2021, the renewable generation capacity in Bangladesh amounted to 722.592 MW, including 67.6% from solar, 31.84% from hydro, and 0.55% from other energy sources, including wind, biogas, and biomass, where 488.662 MW of power originated from over 6 million installed solar power systems. Concurrently, over 42% of rural people still suffer from a lack of electricity, where solar energy can play a vital role. This paper highlights the present status of various forms of solar energy progress in Bangladesh, such as solar parks, solar rooftops, solar irrigation, solar charging stations, solar home systems, solar-powered telecoms, solar street lights, and solar drinking water, which can be viable alternative sources of energy. This review will help decision-makers and investors realize Bangladesh’s up-to-date solar energy scenario and plan better for the development of a sustainable society.

AbstractSmart Grids are electrical grids that require a decentralised way of controlling electric power conditioning and thereby control the production and distribution of energy. Yet, the integration of Distributed Renewable Energy Sources (DRESs) in the Smart Grid introduces new challenges with regards to electrical grid balancing and storing of electrical energy, as well as additional monetary costs. Furthermore, the future smart grid also has to take over the provision of Ancillary Services (ASs). In this paper, a distributed ICT infrastructure to solve such challenges, specifically related to ASs in future Smart Grids, is described. The proposed infrastructure is developed on the basis of the Smart Grid Architecture Model (SGAM) framework, which is defined by the European Commission in Smart Grid Mandate M/490. A testbed that provides a flexible, secure, and low-cost version of this architecture, illustrating the separation of systems and responsibilities, and supporting both emulated DRESs and real hardware has been developed. The resulting system supports the integration of a variety of DRESs with a secure two-way communication channel between the monitoring and controlling components. It assists in the analysis of various inter-operabilities and in the verification of eventual system designs. To validate the system design, the mapping of the proposed architecture to the testbed is presented. Further work will help improve the architecture in two directions; first, by investigating specific-purpose use cases, instantiated using this more generic framework; and second, by investigating the effects a realistic number and variety of connected devices within different grid configurations has on the testbed infrastructure.