| 1. |
- Han, Weiji, 1987, et al.
(författare)
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Analysis and Estimation of the Maximum Switch Current during Battery System Reconfiguration
- 2022
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Ingår i: IEEE Transactions on Industrial Electronics. - 0278-0046 .- 1557-9948. ; 69:6, s. 5931-5941
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Tidskriftsartikel (refereegranskat)abstract
- Batteries are interconnected in series and/or parallel to meet wide-range power or energy demands in various industrial applications. To pursue the benefits of multiple connection structures in one system, reconfigurable battery systems (RBSs) have recently emerged for safe and efficient operation, extended energy storage and delivery, etc. Switches are the essential elements to enable the battery system reconfiguration, but selecting appropriate switches for RBS designs has not been systematically investigated. To bridge this gap, analytical expressions are derived in this paper to estimate the maximum switch current and its upper limit to facilitate the selection of RBS switches. An RBS prototype based on H-bridges is set up and experimental results verify the effectiveness and advantage of the proposed estimation method. These analytical expressions, relying only on resistances of batteries and switches, are readily applicable to practical RBS design and much more efficient than conducting numerous circuit experiments, simulation tests, or circuit analyses, especially for large-scale systems. Moreover, the analysis framework and estimation method proposed for series-parallel mutual conversion can be adaptively extended to other complex system reconfigurations to facilitate various RBS designs.
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| 2. |
- Han, Weiji, 1987, et al.
(författare)
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Near-Fastest Battery Balancing by Cell/Module Reconfiguration
- 2019
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Ingår i: IEEE Transactions on Smart Grid. - 1949-3053 .- 1949-3061. ; 10:6, s. 6954-6964
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Tidskriftsartikel (refereegranskat)abstract
- Charge imbalance is a very common issue in multi-cell/module/pack battery systems due to manufacturing variations, inconsistent charging/discharging, and uneven thermal distribution. As a consequence, the deliverable charge capacity, battery lifespan, and system reliability may all decrease over time. To tackle this issue, various external circuit designs can be attached for charge balance, and the internal battery cell/module/pack connection can also significantly affect the charge balance performance. This paper focuses on minimizing the battery charge equalization (BCE) time by battery cell/module reconfiguration. Specifically, for the reconfigurable module-based BCE system, we propose reconfiguration algorithms for fast charge equalization under different levels of system reconfigurability. For battery systems allowing module reconfiguration and intra-module cell reconfiguration, the proposed module-based bounded reconfiguration algorithm can reach or get very close to the minimum BCE times obtained by exhaustive search. When the reconfigurability level is extended by allowing inter-module cell reconfiguration, the proposed module-based complete reconfiguration algorithm can achieve similar optimality to that of the genetic algorithm (GA). Moreover, as compared to the circuit experiments, exhaustive search, and GA, the proposed algorithms take much less computational time. The optimality and computational efficiency of the proposed algorithms are demonstrated by both circuit and numerical experiments.
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| 3. |
- Han, Weiji, 1987, et al.
(författare)
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Next-Generation Battery Management Systems: Dynamic Reconfiguration
- 2020
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Ingår i: IEEE Industrial Electronics Magazine. - 1941-0115 .- 1932-4529. ; 14:4, s. 20-31
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 4. |
- Han, Weiji, 1987, et al.
(författare)
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Sensitivity Analysis of the Battery System State of Power
- 2022
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Ingår i: IEEE Transactions on Transportation Electrification. - 2332-7782. ; 8:1, s. 976-989
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Tidskriftsartikel (refereegranskat)abstract
- In battery-powered applications, it is necessary to estimate the battery system’s maximum allowed current/power for a certain future time horizon, commonly referred to as the system’s state of power (SoP). Battery system SoP is sensitive to multiple factors, such as battery state of health, state of charge, temperature, and their imbalances in multi-battery systems. Analyzing such sensitivities is important for selecting appropriate system components and connection structure during the system design as well as for predicting substantial SoP changes to proactively guide the online power control. However, such sensitivity analyses are challenging since the SoP is not directly expressed in terms of these factors and the SoP expression can become significantly complicated for interconnected heterogeneous battery cells. To address these challenges, qualitative and quantitative sensitivity analyses are first conducted for both series and parallel battery systems by deriving approximate expressions for the maximum system currents constrained by different operating limits. Some critical insights, commonly overlooked in industrial practices, have been revealed for improving the system SoPs. To pursue reliable analysis results, exact system SoPs are evaluated based on an accurate estimation method along with battery modeling parameters identified through experiments. Experimental tests are also performed to demonstrate some analysis results.
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| 5. |
- Han, Weiji, 1987, et al.
(författare)
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State of Power Prediction for Battery Systems with Parallel-Connected Units
- 2022
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Ingår i: IEEE Transactions on Transportation Electrification. - 2332-7782. ; 8:1, s. 925-935
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Tidskriftsartikel (refereegranskat)abstract
- To meet the ever-increasing demand for energy storage and power supply, battery systems are being vastly applied to, e.g., grid-level energy storage and automotive traction electrification. In pursuit of safe, efficient, and cost-effective operation, it is critical to predict the maximum acceptable battery power on the fly, commonly referred to as the battery system’s state of power (SoP). As compared to the SoP prediction at the battery cell level, predicting the SoP of a multi-battery system, especially including parallel-connected cells/modules/packs, is much more complicated and far less investigated. To solve this problem, a system-model-based SoP prediction method is first proposed in this paper. Specifically, based on the formulated system model and generic state-space representation, the challenge of non-monotonic system state evolution, arising from the dynamic parallel current distribution, is identified and systematically addressed by the proposed method. As demonstrated by tests on a battery system set up with experimentally verified parameter values, the proposed method outperforms the commonly applied cell-SoP based methods for providing a more accurate and reliable prediction of the battery system SoP. Moreover, the proposed prediction framework presented in generic forms can be readily applied to other system structures.
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| 6. |
- Li, Yang, 1984, et al.
(författare)
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Electrochemical Model-Based Fast Charging: Physical Constraint-Triggered PI Control
- 2021
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Ingår i: IEEE Transactions on Energy Conversion. - 1558-0059 .- 0885-8969. ; 36:4, s. 3208-3220
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Tidskriftsartikel (refereegranskat)abstract
- This paper proposes a new fast charging strategy for lithium-ion (Li-ion) batteries. The approach relies on an experimentally validated high-fidelity model describing battery electrochemical and thermal dynamics that determine the fast charging capability. Such a high-dimensional nonlinear dynamic model can be intractable to compute in real-time if it is fused with the extended Kalman filter or the unscented Kalman filter that is commonly used in the community of battery management. To significantly save computational efforts and achieve rapid convergence, the ensemble transform Kalman filter (ETKF) is selected and tailored to estimate the nonuniform Li-ion battery states. Then, a health- and safety-aware charging protocol is proposed based on successively applied proportional-integral (PI) control actions. The controller regulates charging rates using online battery state information and the imposed constraints, in which each PI control action automatically comes into play when its corresponding constraint is triggered. The proposed physical constraint-triggered PI charging control strategy with the ETKF is evaluated and compared with several prevalent alternatives. It shows that the derived controller can achieve close to the optimal solution in terms of charging time and trajectory, as determined by a nonlinear model predictive controller, but at a drastically reduced computational cost.
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| 7. |
- Ouyang, Quan, et al.
(författare)
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Cell Balancing Control for Lithium-Ion Battery Packs: A Hierarchical Optimal Approach
- 2020
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Ingår i: IEEE Transactions on Industrial Informatics. - 1941-0050 .- 1551-3203. ; 16:8, s. 5065-5075
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Tidskriftsartikel (refereegranskat)abstract
- Effective cell equalization is of extreme importance to extract the maximum capacity of a battery pack. In this article, two cell balancing objectives, including balancing time reduction and cells' temperature rise suppression, are taken into consideration simultaneously. Furthermore, hard constraints are imposed on the cells' state-of-charge levels, currents, and equalizing currents. Based on a developed module-based cell-to-cell balancing system model, a multiobjective constrained optimization problem is formulated, which aims at the coordinated control of all equalizers rather than individually controlling the equalizer for its two adjacent cells' equalization. Next, a hierarchical cell equalizing control approach is proposed, where the module-level controlled equalizing currents are first designed at the top layer, and then, the cell-level equalizers are controlled for each battery module in parallel at the bottom layer. The designed hierarchical structure significantly reduces the computational burden, making the cell equalizing algorithm more implementable in real time. Following the Lyapunov stability analysis, the convergence of the designed cell equalizing control algorithm is proved. Illustrative results demonstrate that the balancing time can be reduced by up to 29.8 % compared with the decentralized equalizing control.
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| 8. |
- Cai, Yao, 1996, et al.
(författare)
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Fast Charging Control of Lithium-Ion Batteries: Effects of Input, Model, and Parameter Uncertainties
- 2022
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Ingår i: 2022 European Control Conference, ECC 2022. ; , s. 1647-1653
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Konferensbidrag (refereegranskat)abstract
- The foundation of advanced battery management is computationally efficient control-oriented models that can capture the key battery characteristics. The selection of an appropriate battery model is usually focused on model order, whereas the effects of input and parameter uncertainties are often overlooked. This work aims to pinpoint the minimum model complexity for health-conscious fast charging control of lithiumion batteries in relation to sensor biases and parameter errors. Starting from a high-fidelity physics-based model that describes both the normal intercalation reaction and the dominant side reactions, Padé approximation and the finite volume method are employed for model simplification, with the number of control volumes as a tuning parameter. For given requirements on modeling accuracy, extensive model-based simulations are conducted to find the simplest models, based on which the effects of current sensor biases and parameter errors are systematically studied. The results show that relatively loworder models can be well qualified for the control of voltage, state of charge, and temperature. On the other hand, high-order models are necessary for health management, particularly during fast charging, and the choice of the safety margin should also take the current sensor biases into consideration. Furthermore, when the parameters have a certain extent of uncertainties, increasing the model order will not provide improvement in model accuracy.
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| 9. |
- Dong, Guangzhong, et al.
(författare)
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Active Balancing of Lithium-Ion Batteries Using Graph Theory and A-Star Search Algorithm
- 2021
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Ingår i: IEEE Transactions on Industrial Informatics. - 1941-0050 .- 1551-3203. ; 17:4, s. 2587-2599
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Tidskriftsartikel (refereegranskat)abstract
- The heterogeneity of cells in a battery pack is inevitable but brings high risks of premature failure and even safety hazards. Accordingly, for safe and long-life operation, it is necessary to adjust the state of charge (SOC) of all in-pack cells to the same level. To address this problem, this article first proposes a battery SOC observer and analyzes its stability and convergence analysis using the Lyapunov direct method. Different to most available estimators is that the proposed method does not require the information of cell capacities. Then, after modeling the equalization system as a directed graph, the equalization problem is cast as a path searching problem. Finally, an A-star algorithm subject to balancing constraints is proposed to find the shortest path in this graph, corresponding to the most efficient SOC equalization. Experimental results show that the steady-state error of the proposed observer is less than 2%. It also demonstrates that the A-star algorithm can decrease the balancing time and energy loss during the balancing process by 9.59% and 19.5%, respectively, relative to the mean-difference-average method.
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| 10. |
- Han, Weiji, et al.
(författare)
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Estimation of Cell SOC Evolution and System Performance in Module-based Battery Charge Equalization Systems
- 2019
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Ingår i: IEEE Transactions on Smart Grid. - 1949-3053 .- 1949-3061. ; 10:5, s. 4717-4728
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Tidskriftsartikel (refereegranskat)abstract
- Large-scale battery systems have been applied to a number of grid-level energy storage services such as microgrid capability and distribution upgrade due to the penetration of solar/wind energy. In these battery applications, charge imbalance among battery cells/modules/packs becomes a common issue, which can reduce available battery capacity, accelerate battery degradation, and even cause some safety hazards. To tackle this issue, various battery charge equalization (BCE) systems have been proposed in recent decades, among which the module-based BCE system is widely viewed as a promising solution and has drawn increasing attention. In this paper, we study the module-based BCE systems by presenting a mathematical model that can characterize the charge transfer behavior in such systems, and then proposes computationally efficient algorithms to estimate the instantaneous battery cell state of charge (SOC), charge equalization time, and charging/discharging time, based on given system parameters and various initial battery cell SOCs. In addition, the conditions are derived to ensure that all battery cells can reach charge equalization and then get fully charged/discharged together without overcharging/overdischarging. All theoretical results are illustrated and justified through extensive numerical experiments.
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