| 1. |
- Du, Banghua, et al.
(författare)
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Energy management and performance analysis of an off-grid integrated hydrogen energy utilization system
- 2024
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Ingår i: Energy Conversion and Management. - 0196-8904. ; 299
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Tidskriftsartikel (refereegranskat)abstract
- In integrated hydrogen energy utilization systems, due to the low efficiency of hydrogen/electricity conversion, coordination of energy management and efficient waste heat recovery is required to optimize performance. To address this challenge, this paper presents a comprehensive and sophisticated modeling and energy management strategy to enhance the off-grid energy utilization rate while prolonging the main components' lifetime. The developed model incorporates multiphase flow and heat transport balance for electricity and heat production, enabling a highly accurate representation of real-world behaviors of the system. The proposed off-grid operation strategy is complemented by a designed heat recovery scheme, ensuring the use of energy resources and waste heat. In addition, the proposed energy management strategy monitors the real-time status of each subsystem, actively reducing the number of harmful start-stop cycles of the hydrogen production system, thereby mitigating short-term power impacts and delaying its aging. Specifically, the voltage degradation of the reduction cell is reduced from 4.67 mV to 4.48 mV, the energy utilization rate is increased from 47.6 % to 53.9 %, and the energy efficiency of fuel cells significantly increases from 53.6 % to 78.1 %.
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| 2. |
- Li, Yang, 1984, et al.
(författare)
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Constrained Ensemble Kalman Filter for Distributed Electrochemical State Estimation of Lithium-Ion Batteries
- 2021
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Ingår i: IEEE Transactions on Industrial Informatics. - 1941-0050 .- 1551-3203. ; 17:1, s. 240-250
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Tidskriftsartikel (refereegranskat)abstract
- This article proposes a novel model-based estimator for distributed electrochemical states of lithium-ion (Li-ion) batteries. Through systematic simplifications of a high-order electrochemical–thermal coupled model consisting of partial differential-algebraic equations, a reduced-order battery model is obtained, which features an equivalent circuit form and captures local state dynamics of interest inside the battery. Based on the physics-based equivalent circuit model, a constrained ensemble Kalman filter (EnKF) is pertinently designed to detect internal variables, such as the local concentrations, overpotential, and molar flux. To address slow convergence issues due to weak observability of the battery model, the Li-ion's mass conservation is judiciously considered as a constraint in the estimation algorithm. The estimation performance is comprehensively examined under a wide operating range. It demonstrates that the proposed EnKF-based nonlinear estimator is able to accurately reproduce the physically meaningful state variables at a low computational cost and is significantly superior to its prevalent benchmarks for online applications.
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| 3. |
- Li, Yang, 1984, et al.
(författare)
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Control-Oriented Modeling of All-Solid-State Batteries Using Physics-Based Equivalent Circuits
- 2022
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Ingår i: IEEE Transactions on Transportation Electrification. - 2332-7782. ; 8:2, s. 2080-2092
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Tidskriftsartikel (refereegranskat)abstract
- Considered as one of the ultimate energy storage technologies for electrified transportation, the emerging all-solid-state batteries (ASSBs) have attracted immense attention due to their superior thermal stability, increased power and energy densities, and prolonged cycle life. To achieve the expected high performance, practical applications of ASSBs require accurate and computationally efficient models for the design and implementation of many onboard management algorithms, so that the ASSB safety, health, and cycling performance can be optimized under a wide range of operating conditions. A control-oriented modeling framework is thus established in this work by systematically simplifying a rigorous partial differential equation (PDE) based model of the ASSBs developed from underlying electrochemical principles. Specifically, partial fraction expansion and moment matching are used to obtain ordinary differential equation based reduced-order models (ROMs). By expressing the models in a canonical circuit form, excellent properties for control design such as structural simplicity and full observability are revealed. Compared to the original PDE model, the developed ROMs have demonstrated high fidelity at significantly improved computational efficiency. Extensive comparisons have also been conducted to verify its superiority to the prevailing models due to the consideration of concentration-dependent diffusion and migration. Such ROMs can thus be used for advanced control design in future intelligent management systems of ASSBs.
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| 4. |
- Li, Yang, 1984, et al.
(författare)
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Physics-based model predictive control for power capability estimation of lithium-ion batteries
- 2023
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Ingår i: IEEE Transactions on Industrial Informatics. - 1941-0050 .- 1551-3203. ; 19:11, s. 10763 -10774
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Tidskriftsartikel (refereegranskat)abstract
- The power capability of a lithium-ion battery signifies its capacity to continuously supply or absorb energy within a given time period. For an electrified vehicle, knowing this information is critical to determining control strategies such as acceleration, power split, and regenerative braking. Unfortunately, such an indicator cannot be directly measured and is usually challenging to be inferred for today's high-energy type of batteries with thicker electrodes. In this work, we propose a novel physics-based battery power capability estimation method to prevent the battery from moving into harmful situations during its operation for its health and safety. The method incorporates a high-fidelity electrochemical-thermal battery model, with which not only the external limitations on current, voltage, and power, but also the internal constraints on lithium plating and thermal runaway, can be readily taken into account. The online estimation of maximum power is accomplished by formulating and solving a constrained nonlinear optimization problem. Due to the relatively high system order, high model nonlinearity, and long prediction horizon, a scheme based on multistep nonlinear model predictive control is found to be computationally affordable and accurate.
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| 5. |
- Wan, Wenxin, et al.
(författare)
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Operating conditions combination analysis method of optimal water management state for PEM fuel cell
- 2023
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Ingår i: Green Energy and Intelligent Transportation. - 2773-1537 .- 2097-2512. ; 2:4
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Tidskriftsartikel (refereegranskat)abstract
- The water content of proton exchange membrane fuel cells (PEMFCs) affects the transport of reactants and the conductivity of the membrane. Effective water management measures can improve the performance and extend the lifespan of the fuel cell. The water management state of the stack is influenced by various external operating conditions, and optimizing the combination of these conditions can improve the water management state within the stack. Considering that the stack's internal resistance can reflect its water management state, this study first establishes an internal resistance-operating condition model that considers the coupling effect of temperature and humidity to determine the variation trend of total resistance and stack humidity with single-factor operating conditions. Subsequently, the water management state optimization method based on the ANN-HGPSO algorithm is proposed, which not only quantitatively evaluates the influence weights of different operating conditions on the stack's internal resistance but also efficiently and accurately obtains the optimal combination of five operating conditions: working temperature, anode gas pressure, cathode gas pressure, anode gas humidity, and cathode gas humidity to achieve the optimal water management state in the stack, within the entire range of current densities. Finally, the response surface experimental results of the stack also validate the effectiveness and accuracy of the ANN-HGPSO algorithm. The method mentioned in this article can provide effective strategies for efficient water management and output performance optimization control of PEMFC stacks.
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| 6. |
- Wang, Shaojin, et al.
(författare)
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Comparison of techniques based on frequency response analysis for state of health estimation in lithium-ion batteries
- 2024
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Ingår i: Energy. - 0360-5442 .- 1873-6785. ; 304
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Tidskriftsartikel (refereegranskat)abstract
- Frequency response analysis (FRA) methods are commonly used in the field of State of Health (SOH) estimation for Lithium-ion batteries (Libs). However, identifying their appropriate application scenarios can be challenging. This paper presents four FRA techniques, including electrochemical impedance spectra (EIS), mid-frequency and low-frequency domain equivalent circuit model (MLECM), distribution of relaxation time (DRT) and non-linear FRA (NFRA) technique. This paper proposes two estimation frameworks, machine learning and curve fitting, to be applied to each of the four techniques. Eight SOH estimation models are developed by linking the extracted feature parameters to the battery capacity variations. The paper compares the accuracy of estimation, estimation range, and other properties of the eight models. Application scenarios are identified for the techniques by using three classification methods: different estimation frameworks, frequency response linearity, and impedance technique. The results demonstrate that MLF is recommended for scenarios with a large amount of battery data, while CFF is recommended for scenarios with a small amount of data. NFRA could be applied to electric vehicle power batteries, while LFRA is recommended to be used for retired batteries. EIS method is recommended for complex and dynamic scenarios, while non-EIS method is recommended for scenarios that require high accuracy.
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| 7. |
- Wang, Zhewei, et al.
(författare)
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Multi-time scale scheduling optimization of integrated energy systems considering seasonal hydrogen utilization and multiple demand responses
- 2024
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Ingår i: International Journal of Hydrogen Energy. - 0360-3199. ; 67, s. 728-749
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Tidskriftsartikel (refereegranskat)abstract
- Hydrogen energy is recognized as a crucial solution for addressing energy crises and advancing energy conservation and emissions reduction. It will play a significant role in the future integrated energy systems (IESs). However, the influence of seasonal variations in scheduling optimization of hydrogen-integrated energy system has rarely been investigated. A low-carbon scheduling model for IES, adopting multiple demand responses and a ladder-type carbon trading mechanism, has been established. Additionally, a multi-time scale dispatch optimization strategy considering seasonal hydrogen utilization is thus proposed in this paper. Specifically, day-ahead scheduling optimizes the system taking into account the seasonal variations of renewable energy and load. In the intraday stage, rolling optimization is adopted to address the forecasting errors introduced by wind and photovoltaic fluctuations. In the real-time stage, chance-constrained methods are employed to ensure short-term supply-demand balance. The efficacy of the proposed strategy is verified using real-world measurements, and the results show the multi-time scale scheduling strategy and multiple demand responses effectively enhanced the system's self-regulation capability, leading to a 12% increase in renewable energy absorption. In addition, seasonal hydrogen utilization is essential for system design, as it enhances the absorption of renewable energy, reducing the purchase cost by 4% and the total cost by 2.6%.
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| 8. |
- Weng, Zebin, et al.
(författare)
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Performance improvement of variable-angle annular thermoelectric generators considering different boundary conditions
- 2022
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Ingår i: Applied Energy. - : Elsevier BV. - 1872-9118 .- 0306-2619. ; 306
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Tidskriftsartikel (refereegranskat)abstract
- Practical applications of thermoelectric generators are impeded by their low thermoelectric conversion efficiency, and improving the efficiency is vital for the advancements of thermoelectric technology. In this paper, a novel method is proposed for the performance analysis and improvement of the annular thermoelectric generators with variable-angle PN legs (VATEGs). The influence of the PN leg angle on the output performance of the VATEG is investigated by introducing an angle function. Given the volume of the PN legs, the relationship of output performance between the VATEG and traditional constant-angle ATEG (CATEG) is established under different boundary conditions based on a proposed generic model of VATEG. The results are verified numerically using the finite element method. Using the model, it is shown that the output performance of the VATEG is significantly affected by the shape of the PN leg. Finally, the thermal stress on the PN leg is next investigated using a high-fidelity 3D model of the variable-angle PN legs implemented in COMSOL, and it is found that the shape difference has a considerable influence on the thermal stability of VATEG. Under the condition of constant heat flux on the hot side and constant temperature on the cold side of the thermoelectric modules, it shows that when the radius factor is 2, the output performance can be improved by 35% with the designed VATEG, at the expense of 30% higher maximum thermal stress on the PN legs.
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| 9. |
- Wu, Hangyu, et al.
(författare)
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Hybrid physics-based and data-driven prognostic for PEM fuel cells considering voltage recovery
- 2023
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Ingår i: IEEE Transactions on Energy Conversion. - 1558-0059 .- 0885-8969. ; 39:1, s. 601-612
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Tidskriftsartikel (refereegranskat)abstract
- Predicting the degradation behaviors is challenging and essential for prognostics and health management for proton exchange membrane fuel cells (PEMFCs). However, existing methods based on data-driven or model-based methods can face the problem of significant performance inconsistencies in different prediction stages. We investigate the cause and attribute it to the ignorance of the voltage recovery phenomena of PEMFCs observed during the frequent start-stop processes during practical applications. A novel prognostic method is proposed to provide a more comprehensive analysis of PEMFC aging that integrates data-driven and model-based methods. Specifically, a physics-based aging model considering voltage recovery (PA-VR) is first reported as a model-based method to enhance the prediction effect at voltage mutation points. Then, the moving window method with iterative function is used to combine the data-driven method with the PA-VR model, which realizes the online update of model parameters. Finally, the weightings on individual approaches are dynamically determined at different stages throughout the PEMFC lifecycle. The proposed hybrid method achieves an effective improvement in prediction performance by combining the overall degradation trend predicted by the PA-VR model and the local dynamic characteristics predicted by the data-driven method.
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| 10. |
- Xiong, Binyu, et al.
(författare)
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Design of A Two-Stage Control Strategy of Vanadium Redox Flow Battery Energy Storage Systems for Grid Application
- 2022
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Ingår i: IEEE Transactions on Sustainable Energy. - 1949-3029 .- 1949-3037. ; 13:4, s. 2079-2091
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Tidskriftsartikel (refereegranskat)abstract
- The low energy conversion efficiency of the vanadium redox flow battery (VRB) system poses a challenge to its practical applications in grid systems. The low efficiency is mainly due to the considerable overpotentials and parasitic losses in the VRB cells when supplying highly dynamic charging and discharging power for grid regulation. Apart from material and structural advancements, improvements in operating strategies are equally essential for achieving the expected high-performance VRB system, although an optimized solution has not been fully exploited in the existing studies. In this paper, a two-stage control strategy is thus developed based on a proposed and experimental validated multi-physics multi-time-scale electro-thermo-hydraulic VRB model. Specifically, in the first stage, the optimal flow rate of the VRB is obtained based on online optimization to reduce parasitic loss and enhance instantaneous system efficiency, and the result serves as the set point of a feedback flow rate controller. In the second stage, dual time scales are specifically considered. And the current and flow rate controllers are designed to meet the highly varying power demands for grid-connected applications. The effectiveness of the proposed control strategy is verified under a scenario to smooth wind power generation. Comparative studies show that compared to the prevailing approaches, higher efficiency can be achieved in tracking the theoretical optimal power profiles for online battery control.
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