Research PapersResearch on two-stage equalization strategy based on fuzzy logic control for lithium-ion battery packs
Introduction
Lithium-ion batteries are widely used in electric vehicles because of their high power and energy density, long life, low self-discharge rate, and low environmental pollution [1], [2]. Because the voltage of a single cell is not enough to meet the demand, multiple cells are usually connected in series to form a battery pack [3]. However, the variation in internal resistance, unequal capacity, aging and changes in ambient temperature of each cell lead to inconsistencies in the battery pack, which have a certain impact on the performance and service life of the battery pack, and it is essential to equalize the battery pack in order to extend its service life [4], [5], [6].
Equilibrium methods can be divided into passive and active [7], [8]. Passive equalization dissipates the excess energy of a high energy battery in the form of heat, mainly by connecting resistors in parallel [9]. This equalization method has the advantages of simple control, low cost and high reliability, but suffers from high losses, low equalization efficiency and long equalization times [10]. Considering the energy utilization and equalization speed in equalization, active equalization with energy storage elements such as inductors, capacitors, and converters as energy transfer medium has attracted a lot of attention [11], [12], [13]. Vardhan et al. presented in Ref. [14] an equalization topology based on a single inductor, but the number of switches used in the circuit is large and the energy loss is high. Fan et al. presented in Ref. [15] an improved Buck-Boost circuit topology, but it can only achieve energy transfer between two adjacent cells, with low equalization efficiency and low equalization speed. Ma et al. presented in Ref. [16] a grouped equalization topology based on the Buck-Boost circuit, where equalization can be achieved simultaneously within the group, which improves the equalization efficiency compared to the conventional Buck-Boost circuit. However, when there are too many cells in the group, the energy needs to be transferred through the intermediate batteries, increasing the energy transfer path and thus the equalization time and energy loss.
The circuit topology has been improved by considering the advantages and disadvantages of the balanced topology in the Refs. [14], [15], [16]. In this paper, the two-stage equalization topology based on the buck-Boost circuit is proposed. Grouping the batteries so that energy transfer between any individual cells can be achieved within the group and simultaneous equalization is possible, using the double-layer switches as the switching array, thus showing better advantages in term of equalization speed and energy loss.
After selecting the equalization circuit, it is necessary to choose an effective optimal equalization algorithm. The maximum balance method can easily achieve battery equilibrium, but its balance efficiency is not high [17]. The mean and difference comparison method takes the average of the capacities of all the individual cells in the battery pack as the standard, which is simple to control, but is only applicable to a small number of cells, and can lead to inefficient equalization if the equalization between individual cells involves energy transfer between multiple cells [18]. Wu et al. presented in Ref. [19] the voltage-SOC balancing control scheme, which retains the advantages of the voltage equalization method in terms of less calculation and great equalization performance of the SOC equalization method, however, the performance of the voltage-SOC balancing control scheme depends on the accuracy of the OCV-SOC curve, which changes as the battery ages. Mccurlie et al. presented in Ref. [20] the K-value clustering algorithm to equalize battery groups, which is relatively simple to implement, but also has certain limitations; determining a reasonable K-value is difficult, and the randomness of the initial cluster center selection can lead to unstable clustering results. The model prediction method can achieve battery equalization relatively quickly. This method relies on a battery model, but it is difficult to build an accurate mathematical model for the battery due to the inconsistent differences in capacity and internal resistance of the individual cells in the battery pack [21], [22]. Compared to traditional control strategies, the use of fuzzy logic control to achieve equalization has a better optimization performance in terms of equalization efficiency [23], [24]. Zhang et al. presented in Ref. [25] a method that adjusts the equalization period online according to the voltage difference between the batteries and the battery voltage. But the equalization topology is complex, and energy utilization rate is not considered.
Wang et al. presented in Ref. [26] a stepwise equalization based on the variation characteristics of SOC over the full cycle range, but it does not consider the influence of battery aging, temperature, and other factors on the battery OCV-SOC curve. In this paper, FLC [27], [28], [29], which does not need accurate mathematical models, is used to improve the inconsistency of batteries and optimize equalization efficiency by its strong nonlinearity, robustness, and fault tolerance.
This paper provides four contributions.
- (1)
A two-stage balanced topology based on the Buck-Boost circuit is proposed, and the advantages compared with the traditional topology are further analyzed.
- (2)
An equalization control scheme based on fuzzy logic control is proposed and compared with the traditional maximum value equalization method.
- (3)
Extensive experimental results verify the equilibrium control scheme of fuzzy logic control.
- (4)
To better quantify the equalization effect, the battery differences and energy utilization rate are defined for evaluation.
The structural arrangement of this paper is as follows. The second section introduces the topology of two-stage equalization based on the Buck-Boost circuit and analyzes its working principle. The third section introduces the hierarchical control strategy based on FLC and the design of the fuzzy logic controller. In the fourth section, the equilibrium topology and FLC-based hierarchical control strategy are verified by modeling and simulation with Matlab/Simulink software. Finally, the relevant conclusions are given in the fifth section.
Section snippets
Analysis of equalization circuit
A traditional single inductor centralized bidirectional active equalization topology is shown in Fig. 1, containing p single cells, 2p+4 MOSFET tubes, 4 diodes, and 1 inductor. When the batteries are being equalized, they are transferred through the inductor for energy transfer and control is relatively simple, but when the number of batteries is high, the equalization time is slow and there are more switching tubes in the circuit, which increases the losses as the number of switches increases.
Equalization control strategy
The equalization variables include battery voltage, battery capacity, and state of charge (SOC). With the battery voltage as the equalization variable, only the voltage acquisition module needs to be used for detection and no extensive calculations are required. However, when the battery capacity is between 10% and 90%, the battery voltage varies very little and the equalization effect depends largely on the acquisition accuracy of the voltage acquisition module. Taking the battery capacity as
Simulation experiment and analysis
In this paper, Matlab/Simulink 2019b is used for modeling and simulation, the parameters of lithium-ion batteries are 3.7 V/3.2 Ah, and the initial SOC values of each battery are 76%, 73%, 71%, 68%, 64%, 62%, 60%, 58%, and 57%, respectively. The equalization simulation model includes the battery module, oscilloscope, double-layer switch, Buck-Boost module, switch control module, and current control module based on FLC. Oscilloscopes are used to collect the SOC value of every single cell. The
Conclusion
In this paper, a two-stage balanced topology based on the Buck-Boost circuit is proposed for the inconsistency of series lithium-ion battery. The equalization topology within the group is the first stage equalization topology, the equalization within the group is the first stage equalization, the equalization between groups is the second stage equalization topology, and the equalization between groups is the second stage equalization. The topology can realize the equalization between the
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
This work is supported by the Open Foundation of Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System (Grant No. HBSEES202102) and the National Natural Science Foundation of China (Grant No. 52177212).
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