Control and Analysis of a Modular Bridge for Battery Cell Voltage Balancing

Tavakoli, Atrin; Khajehoddin, S. Ali; Salmon, John

doi:10.1109/tpel.2018.2798636

Cited by 23 publications

(8 citation statements)

References 25 publications

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“…Besides, the polarization and ohmic effect are more significant if the battery ages severely, resulting in a more pronounced voltage drop at low SOC and voltage rise at high SOC [33][34][35][36]. us, adopting SOC as the single equalization criterion is not enough; this cannot prevent possible battery damage from overcharging and over-discharging [12,37,38]. Figure 7 is the SOC-OCV characteristic curve of the LIB.…”

Section: Equalization Control Algorithmmentioning

confidence: 99%

Active Equalization Strategy for Lithium-Ion Battery Packs Based on Multilayer Dual Interleaved Inductor Circuits in Electric Vehicles

Lei

Fan

et al. 2022

Journal of Advanced Transportation

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Lithium-ion batteries (LIBs) are widely used in electric vehicles (EVs) due to their superior power performance over other batteries. However, when connected in series, overcharged cells of LIBs face the risk of explosion, and undercharged cells decrease the life cycle of the battery. Eventually, the inconsistency phenomenon between cells resulting from manufacturing tolerance and usage process reduces the overall charging capacity of the battery and increases the risk of explosion after long-time use. Research has focused on synthesizing active material to achieve higher energy density and extended life cycle for LIBs while neglecting a comparative analysis of equalization technology on the performance of battery packs. In this paper, a nondissipative equalization structure is proposed to reconcile the inconsistency of series-connected LIB cells. In this structure, a circuit uses high-level equalization units to enable direct energy transfer between any two individual cells, and dual interleaved inductors in each equalization unit increase the equalization speed of a single cell in one equalization cycle by a factor of two. The circuit is compared with the classical inductor equalization circuit (CIEC), dual interleaved equalization circuit (DIEC), and parallel architecture equalization circuit (PAEC) in the states of standing, charging, and discharging, respectively, to validate the advantages of the proposed scheme. Considering the diversity of imbalance states, the state of charge (SOC) and terminal voltage are both chosen as the equalization criterion. The second-order RC model of the LIB and the adaptive unscented Kalman filter (AUKF) algorithm are employed for SOC estimation. For effective equalization, the adaptive fuzzy neural network (AFNN) is utilized to further reduce energy consumption and equalization time. The experiment results show that the AFNN algorithm reduces the total equalization time by approximately 37.4% and improves equalization efficiency by about 4.89% in contrast with the conventional mean-difference algorithm. Particularly, the experiment results of the equalization circuit verification certify that the proposed equalization structure can greatly accelerate the equalization progress and reduce the equalization loss compared to the other three equalization circuits.

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Section: Equalization Control Algorithmmentioning

confidence: 99%

Active Equalization Strategy for Lithium-Ion Battery Packs Based on Multilayer Dual Interleaved Inductor Circuits in Electric Vehicles

Lei

Fan

et al. 2022

Journal of Advanced Transportation

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“…Fuzzy logic control strategy [31] applied in transformer-based equalizers considers voltage as reference. Battery cell voltage balancing control [35] employed in a modular bridge equalizer aims at voltage consistency. The control strategy of active hierarchical equalization circuits [36] achieves voltage consistency.…”

Section: Introductionmentioning

confidence: 99%

An Active Equalization Method for Lithium-ion Batteries Based on Flyback Transformer and Variable Step Size Generalized Predictive Control

2021

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The inconsistency in large-scale battery pack significantly degrades the performance of electric vehicles. In order to diminish the inconsistency, the study designs an active equalization method comprising of equalizer and equalization strategy for lithium-ion batteries. A bidirectional flyback transformer equalizer (BFTE) is designed and analyzed. The BFTE is controlled by a pulse width modulation (PWM) controller to output designated balancing currents. Under the purpose of shortening equalization time and reducing energy consumption during the equalization process, this paper proposes an equalization strategy based on variable step size generalized predictive control (VSSGPC). The VSSGPC is improved on the generalized predictive control (GPC) by introducing the Step Size Factor. The VSSGPC surmounts the local limitation of GPC by expanding the control and output horizons to the global equalization process without increasing computation owing to the Step Size Factor. The experiment results in static operating condition indicate that the equalization time and energy consumption are reduced by 8.3% and 16.5%, respectively. Further validation in CC-CV and EUDC operating conditions verifies the performance of the equalizer and rationality of the VSSGPC strategy.

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“…The active and passive balancing methods for lithium-based batteries have also been studied thoroughly in [1], [20][21][22][23][24]. In addition, a comparison between different balancing methods has been reported by [23][24][25][26][27][28], where the balancing methodology is classified depending on the number of switches, transformers, capacitors, inductors, diodes, modularity, complexity, reliability, cost, and so on.…”

Section: Introductionmentioning

confidence: 99%

Active battery balancing system for electric vehicles based on cell charger

Amin

Budiman

Kaleg

et al. 2021

IJPEDS

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Cell imbalance can cause negative effects such as early stopping of the battery charging and discharging process which can reduce its capacity. In the previous active balancing research, the energy used for the balancing process was taken from the cell or battery pack, resulting in drop of electric vehicle driving range. In this paper, a cell charger based battery balancing system is proposed with a reduction in the number of switches. The use of a cell charger aims to increase the usable energy of the battery pack, since the energy used for the balancing process is taken directly from the grid. The use of fewer switches aims to reduce the cost and space used on the battery management system (BMS) hardware. The charger used for the balancing process has a maximum current of 3 A and a maximum voltage of 3.65 V while the number of switches used is n+5 for n batteries. A 15S1P 200 Ah LiFePO4 battery pack consists of 15 cells used for testing purpose. The test results show that the time needed to equalize the 15 cell battery voltage reaches 6 hours from the difference between the highest and lowest battery cell voltages of 145.1 mV to 15.1 mV.

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Control and Analysis of a Modular Bridge for Battery Cell Voltage Balancing

Cited by 23 publications

References 25 publications

Active Equalization Strategy for Lithium-Ion Battery Packs Based on Multilayer Dual Interleaved Inductor Circuits in Electric Vehicles

Active Equalization Strategy for Lithium-Ion Battery Packs Based on Multilayer Dual Interleaved Inductor Circuits in Electric Vehicles

An Active Equalization Method for Lithium-ion Batteries Based on Flyback Transformer and Variable Step Size Generalized Predictive Control

Active battery balancing system for electric vehicles based on cell charger

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