| 1. |
- Han, Weiji, 1987, et al.
(author)
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Analysis and Estimation of the Maximum Switch Current during Battery System Reconfiguration
- 2022
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In: IEEE Transactions on Industrial Electronics. - 0278-0046 .- 1557-9948. ; 69:6, s. 5931-5941
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Journal article (peer-reviewed)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.
(author)
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Near-Fastest Battery Balancing by Cell/Module Reconfiguration
- 2019
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In: IEEE Transactions on Smart Grid. - 1949-3053 .- 1949-3061. ; 10:6, s. 6954-6964
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Journal article (peer-reviewed)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.
(author)
-
Next-Generation Battery Management Systems: Dynamic Reconfiguration
- 2020
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In: IEEE Industrial Electronics Magazine. - 1941-0115 .- 1932-4529. ; 14:4, s. 20-31
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Journal article (peer-reviewed)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.
(author)
-
Sensitivity Analysis of the Battery System State of Power
- 2022
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In: IEEE Transactions on Transportation Electrification. - 2332-7782. ; 8:1, s. 976-989
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Journal article (peer-reviewed)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.
(author)
-
State of Power Prediction for Battery Systems with Parallel-Connected Units
- 2022
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In: IEEE Transactions on Transportation Electrification. - 2332-7782. ; 8:1, s. 925-935
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Journal article (peer-reviewed)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. |
- Ouyang, Quan, et al.
(author)
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Cell Balancing Control for Lithium-Ion Battery Packs: A Hierarchical Optimal Approach
- 2020
-
In: IEEE Transactions on Industrial Informatics. - 1941-0050 .- 1551-3203. ; 16:8, s. 5065-5075
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Journal article (peer-reviewed)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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| 7. |
- Dong, Guangzhong, 1991, et al.
(author)
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Dynamic Bayesian Network based Lithium-ion Battery Health Prognosis for Electric Vehicles
- 2021
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In: IEEE Transactions on Industrial Electronics. - 0278-0046 .- 1557-9948. ; 68:11, s. 10949-20958
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Journal article (peer-reviewed)abstract
- IEEE Battery prognostics and health management (PHM) are essential for lithium-ion batteries in electric vehicles. In the battery PHM, accurate estimation of the battery state of health (SOH) and prediction of the remaining useful life (RUL) are crucial to ensure safe and efficient battery operation. This paper presents a probabilistic method for the battery degradation modeling and health prognosis based on the features extracted from the charging process using the dynamic Bayesian network (DBN). First, an aggregated feature, combining the incremental capacity analysis (ICA) of constant-current (CC) charging and the time constant of constant-voltage (CV) charging, is developed to characterize the battery degradation dynamics in case some CC or CV charging information is absent. The DBN is then employed to explore the underlying correlation between the battery aging and the extracted features. The proposed model treats the degradation dynamics as a rich family of probability distributions to model real-world battery operation more accurately. Moreover, the battery SOH estimation and RUL prediction are carried out using the particle filtering (PF) inference algorithm. Experimental tests are conducted on two different battery cells and the results show that the proposed methods can provide accurate and robust battery SOH estimation and reliable RUL prediction.
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| 8. |
- Han, Weiji, 1987, et al.
(author)
-
Analysis and estimation of the maximum circulating current during the parallel operation of reconfigurable battery systems
- 2020
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In: 2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020. ; , s. 229-234
-
Conference paper (peer-reviewed)abstract
- Reconfigurable battery systems (RBSs) are emerging as a promising solution to safe, efficient, and robust energy storage and delivery through dynamically adjusting the battery connection topology. When the system connection is switched from series to parallel, circulating currents between parallel battery cells/modules can be triggered due to their voltage imbalance. During the hardware design of an RBS, the current rating of associated components, such as batteries, switches, and wires, depends on the maximum circulating currents. Moreover, given a developed RBS, the maximum circulating current also determines whether it is feasible to perform the relevant system reconfiguration. Thus, this paper is focused on modeling and analyzing the current distribution during the series-to-parallel battery reconfiguration and estimating the maximum circulating currents as well as their upper bound under various system states and operating scenarios. A prototype is set up to experimentally verify the effectiveness of the proposed method for estimating the maximum circulating currents.
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| 9. |
- Han, Weiji, et al.
(author)
-
Estimation of Cell SOC Evolution and System Performance in Module-based Battery Charge Equalization Systems
- 2019
-
In: IEEE Transactions on Smart Grid. - 1949-3053 .- 1949-3061. ; 10:5, s. 4717-4728
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Journal article (peer-reviewed)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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| 10. |
- Kersten, Anton, 1991, et al.
(author)
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Elimination/Mitigation of Output Voltage Harmonics for Multilevel Converters Operated at Fundamental Switching Frequency using Matlab's Genetic Algorithm Optimization
- 2020
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In: 2020 22nd European Conference on Power Electronics and Applications, EPE 2020 ECCE Europe. ; , s. 1-12
-
Conference paper (peer-reviewed)abstract
- This paper deals with the optimization of the output voltage waveform of a multilevel converter operated with fundamental frequency switching. For a high number of output voltage levels, nearest-level control is typically used, whereas an optimized waveform can be presumably used to eliminate a selection of low order harmonics. A nonlinear optimization problem for any kind of multilevel inverter, operating in a single or three-phase arrangement, is formulated. It is shown that the set of nonlinear equations, defining this optimization problem, cannot be numerically solved, if the number of output voltage levels is higher than nine. Thus, an optimization algorithm, e.g., Matlab's genetic algorithm, should be used instead. Based on the concept of the weighted THD, it is shown that an optimized waveform has no effect on the output current's quality of a single phase multilevel converter. However, considering an ungrounded three-phase system, the content of the to be eliminated harmonic components is shifted towards the triplen harmonics and, consequently, the expected current quality, based on the WTHD, can be significantly improved.
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| 11. |
- Kersten, Anton, 1991, et al.
(author)
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Online and On-Board Battery Impedance Estimation of Battery Cells, Modules or Packs in a Reconfigurable Battery System or Multilevel Inverter
- 2020
-
In: IECON Proceedings (Industrial Electronics Conference). - 2162-4704 .- 2577-1647. ; 2020-October, s. 1884-1891
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Conference paper (peer-reviewed)abstract
- This paper shows two approaches to determine the battery impedance of battery cells or battery modules when used in a reconfigurable battery system (RBS) or in any type of modular multilevel converter (MMC) for electric drive applications. A generic battery model is used and the concepts of the recursive time and frequency-domain parameter extraction, using a current step and an electrochemical impedance spectroscopy, are explained. Thus, it is shown and demonstrated that the balancing current of neighboring cells/modules ,when in parallel operation, can be used, similar to the time-domain parameter extraction utilizing a current step, to determine the battery parameters. Furthermore, it is shown and demonstrated that a part of the inverter can be used as variable AC voltage source to control a sinusoidal current through the motor inductances of the drive train, which can be injected to the inserted battery cells/modules of an adjacent phase to perform an on-board impedance spectroscopy. Using either of the two presented approaches, the individual battery impedances can be easily determined, yielding the state of health (SOH) and the power capability of individual battery cells/modules. Nonetheless, the analyzed approaches were just considered to be applied at machine standstill, which is not suitable for grid-tied applications.
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| 12. |
- Kersten, Anton, 1991, et al.
(author)
-
Output voltage synthesis of a modular battery system based on a cascaded h-bridge multilevel inverter topology for vehicle propulsion: Multilevel pulse width modulation vs. fundamental selective harmonic elimination
- 2020
-
In: 2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020. ; , s. 296-302
-
Conference paper (peer-reviewed)abstract
- Lately, the research interest for modular battery systems has increased due to the possibility of a better utilization of individual battery packs/cells and the steadily reducing costs of low voltage power electronics. This paper deals with the output voltage synthesis of a modular battery system based on a seven level Cascaded H-bridge (CHB) inverter topology used in a small passenger vehicle. Two methods are considered, Multilevel Pulse Width Modulation (MPWM) and Fundamental Selective Harmonic Elimination (FSHE). Using simulations, the inverter and battery losses, as well as the current THD, are used to assess the effectiveness of both techniques for the broad operating range of a vehicle's drivetrain. It has been shown that FSHE cannot be applied at a modulation index below 0.25, because of the high current THD (> > 5%). Exceeding a modulation index of 0.25, FSHE reduces the battery and inverter losses in comparison to MPWM, while maintaining an acceptable current THD. Operating at higher speeds, FSHE achieves an even better current THD than MPWM. Consequently, it seems reasonable to use a hybrid modulation technique, using MPWM at low and FSHE at higher speeds, respectively. The exact boundary between MPWM and FSHE can vary in accordance with the individual optimization weightings of current THD and drivetrain efficiency.
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| 13. |
- Li, Xiaoyu, et al.
(author)
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Lithium-ion batteries fault diagnostic for electric vehicles using sample entropy analysis method
- 2020
-
In: Journal of Energy Storage. - : Elsevier BV. - 2352-152X. ; 27
-
Journal article (peer-reviewed)abstract
- Fault detection plays a vital role in the operation of lithium-ion batteries in electric vehicles. Typically, during the operation of battery systems, voltage signals are susceptible to noise interference. In this paper, a novel fault detection method based on the Empirical Mode Decomposition and Sample Entropy is proposed to identify battery faults under various operating conditions. Firstly, effective fault features are extracted through the proposed Empirical Mode Decomposition method by decomposing battery voltage signals and removing the noise interference during the voltage sampling process. Experiments are conducted to quantitatively illustrate the fault features extracted by the Empirical Mode Decomposition. Then, based on these extracted fault features, the Sample Entropy values are calculated to help accurately detect and locate the battery faults. Moreover, an evaluation strategy of the detected faults is designed to indicate the battery fault level. Finally, the effectiveness of the proposed approach is verified against real-world data measured from electric vehicles in the presence of regular and sudden faults.
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| 14. |
- Pei, Mingyang, et al.
(author)
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Life-Cycle analysis of economic and environmental effects for electric bus transit systems
- 2024
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In: Transportation Research Part D: Transport and Environment. - 1361-9209. ; 131
-
Journal article (peer-reviewed)abstract
- Electric buses play a crucial role in reducing the carbon footprint. This study evaluates the life cycle costs (LCCs) and environmental impacts of three e-bus transit systems: stationary charging, battery swapping, and dynamic wireless charging. A mixed-integer nonlinear optimization problem is formulated to determine the optimal design parameters for the charging infrastructure, bus fleet size, and battery capacity for each e-bus transit system considering battery degradation. Taking Guangzhou's Bus Rapid Transit (BRT) system as an example, a sensitivity analysis of the optimized solution is conducted. The LCC analysis framework is extended to BRT systems in 38 cities globally. The results indicate the superiority of battery swapping in most cases, while stationary charging and dynamic wireless charging are more competitive in cases with long circuit lengths and high service frequencies. Dynamic wireless charging becomes the best option when charging infrastructure is shared with other bus lines or private cars.
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| 15. |
- Theliander, Oskar, et al.
(author)
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Battery Modeling and Parameter Extraction for Drive Cycle Loss Evaluation of a Modular Battery System for Vehicles Based on a Cascaded H-Bridge Multilevel Inverter
- 2020
-
In: IEEE Transactions on Industry Applications. - 0093-9994 .- 1939-9367. ; 56:6, s. 6968-6977
-
Journal article (peer-reviewed)abstract
- This article deals with the modeling and the parameterization of the battery packs used in cascaded H-bridge multilevel propulsion inverters. Since the battery packs are intermittently conducting the motor currents, the battery cells are stressed with a dynamic current containing a substantial amount of low-order harmonic components up to a couple of kHz, which is a major difference in comparison to a traditional two-level inverter drive. Different models, such as pure resistive and dynamic RC -networks, are considered to model the energy losses for different operating points (OPs) and driving cycles. Using a small-scale setup, the models’ parameters are extracted using both a low-frequency, pulsed current, and an electrochemical impedance spectroscopy (EIS) sweep. The models are compared against measurements conducted on the small-scale setup at different OPs. Additionally, a drive cycle loss comparison is simulated. The simple resistive model overestimates the losses by about 20% and is, thus, not suitable. The dynamic three-time-constant model, parameterized by a pulsed current, complies with the measurements for all analyzed OPs, especially at low speed, with a maximum deviation of 3.8%. Extracting the parameters using an EIS seems suitable for higher speeds, though the losses for the chosen OPs are underestimated by 1.5%–7.9%.
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