Active model-based balancing strategy for self-reconfigurable batteries

Bouchhima, Nejmeddine; Schnierle, Marc; Schulte, Sascha; Birke, Kai Peter

doi:10.1016/j.jpowsour.2016.05.027

Cited by 54 publications

(34 citation statements)

References 7 publications

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“…Two parts of the ECANI 4-2 can be in parallel or in series and two cells in each part are in series. The ECANI 4-2 has four equalization modes [23,24]. The ECANI 4-2 in Figure 6b is divided into two parts.…”

Section: Four Cells Equalization Circuitmentioning

confidence: 99%

A Novel Lithium Battery Equalization Circuit with Any Number of Inductors

Kang

Luo

et al. 2019

Energies

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Even with the same voltage level, different types of battery packs have different requirements for the volume of the battery equalization circuit. However, most equalization circuits have the same problem: the volume of the equalization circuit is fixed once the voltage level of the battery pack is determined. In order to solve this problem, this paper proposes a novel lithium battery equalization circuit with any number of inductors (ECANI). It can select any number of inductors less than half the number of batteries, even when the voltage level of the battery pack is determined. Simulation and experiments are used to verify the performance of the equalization circuit. The current error and the average final voltage error in the experiment are 1.69% and 0.33% lower than those in the simulation, respectively. So the circuit can achieve equalization with good accuracy.

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Section: Four Cells Equalization Circuitmentioning

confidence: 99%

A Novel Lithium Battery Equalization Circuit with Any Number of Inductors

Kang

Luo

et al. 2019

Energies

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“…The macroscopic temperature model of the battery is coupled to not only accurately obtain macroscopic physical quantities but also predict the state of the interior of the battery through model simulation. Therefore, the coupled model is very suitable for Li‐ion battery safety analysis and optimization design . The SOC estimation methods are variables like ampere‐hour counting, open‐circuit voltage method, and Kalman filter.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the coupled model is very suitable for Li-ion battery safety analysis and optimization design. [12][13][14] The SOC estimation methods are variables like ampere-hour counting, open-circuit voltage method, and Kalman filter. Different methods have merits and demerits; considering the accuracy of extended Kalman filter (EKF) and its possible applicability on a nonlinear system, 15,16 the coupled model utilizes the algorithm to calculate SOC as an equalization variable.…”

Section: Introductionmentioning

confidence: 99%

Active equalization control strategy of Li‐ion battery based on state of charge estimation of an electrochemical‐thermal coupling model

Lin

Wang

et al. 2020

Int J Energy Res

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Summary Aiming at solving the problem of poor battery cell consistency caused by excessive decay of cell capacity or increased internal resistance during the operation of lithium‐ion battery packs for vehicles, the paper proposes an active equalization control with 12‐V power supply as an equalization energy source, which achieves efficient energy replenishment of individual cells with low power. The electrochemical‐thermal coupling model of lithium‐ion battery is built, and the order reduction of large‐scale system theory ensures that the model had higher accuracy and lower amount of calculation, which is suitable for vehicle battery management system (BMS). Then the extended Kalman filter algorithm is used to calculate the real‐time state of charge (SOC) of each cell and set as an equalization variable. The equalization simulation circuit is built with MATLAB/Simulink, the experimental platform of active equalization system for battery packs is constructed, and the battery packs are tested for equalization in static state. The simulation and experimental results show that the proposed active equalization control strategy can rapidly improve the voltage inconsistency between single cells, and the energy transfer efficiency can reach about 85% during the equalization process.

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“…Among the SOC estimation techniques, adaptive method especially Artificial Neural Network (ANN) is the most popular and accurate method because of its self-processing characteristics [9]. BMS observes the battery condition by estimating SOC for each cell and transfers the directions via DC/DC converter according to its requirements [10], [11]. In this paper, an active cell balancing topology based on SOC estimation is accomplished standing on BPNN algorithm as well as a DC/DC buck-boost converter is engaged for each cell to observe the charge equilibrium scheme.…”

Section: Introductionmentioning

confidence: 99%

Active Cell Balancing Control Method for Series-Connected Lithium-Ion Battery

Qays¹,

Buswig²,

Anyi³

2019

IJITEE

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Power conveyance potentiality for series and parallel allied battery-packages are constrained by the wickedest cell of the string. Every cell contains marginally dissimilar capability and terminal voltage because of industrialized acceptances and functional situations. During charging or discharging progression, the charge status of the cell strings become imbalanced and incline to loss equalization. Therefore, the enthusiasm of this paper is to design an active charge balancing system for Lithium-ion battery pack with the help of online state of charge (SOC) estimation technique. A Battery Management System (BMS) is modeled by means of controlling the SOC of the cells to upsurge the efficacy of rechargeable batteries. The capacity of each cell is calculated by dint of SOC function estimated as a result of Backpropagation Neural Network (BPNN) algorithm through four switched DC/DC Buck-Boost converter. The simulation results confirm that the designed BMS can synchronize the cell equalization via curtailing the SOC estimation error (RMSE 1.20%) productively.

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Active model-based balancing strategy for self-reconfigurable batteries

Cited by 54 publications

References 7 publications

A Novel Lithium Battery Equalization Circuit with Any Number of Inductors

A Novel Lithium Battery Equalization Circuit with Any Number of Inductors

Active equalization control strategy of Li‐ion battery based on state of charge estimation of an electrochemical‐thermal coupling model

Active Cell Balancing Control Method for Series-Connected Lithium-Ion Battery

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