1. Introduction
At present, lithium-ion batteries are widely used in electric vehicles (EVs), aerospace, and energy storage systems [
1,
2,
3] because of their high energy density, high power density, lack of memory effect, low self-discharge, and long service life [
4,
5,
6]. However, due to variations in manufacturing tolerances, operating temperatures, and aging levels, inevitable differences exist among cells in terms of electrical parameters such as internal resistance and capacity [
7]. As the number of charge/discharge cycles increases, these differences also increase, resulting in inconsistency of cells. This inconsistency can lead to battery over-charging or over-discharging, which can range from a decrease in the effective capacity and lifespan of the battery pack to severe safety incidents such as fire outbreaks and explosions. State of health (SOH) and battery balancing techniques are exploited to eliminate the aforementioned safety hazards. SOH is usually utilized in the diagnosis of lithium-ion battery health conditions. This technique allows for the screening of lithium-ion batteries with health faults and ensures proper operation of the whole battery pack. Consequently, its diagnostic results always depend on highly reliable mathematical models and analysis methods. The mathematical models and analytical methods proposed in [
8,
9,
10] can be applied to SOH to improve the reliability and accuracy of its diagnostic results. For healthy lithium-ion batteries, battery balancing techniques are usually employed to address the inconsistency of cells in the battery pack [
11,
12].
Typically, battery balancing techniques are divided into two main categories: passive balancing (also called dissipative balancing) and active balancing (also called non-dissipative balancing) [
13]. Passive balancing usually connects a resistor in parallel with a cell to dissipate excess energy in the cell. The advantages of this balancing method include simple circuit structure, low circuit cost, and lack of requirement of complex control strategies, but the thermal management problem caused by energy consumption is the main drawback of this method [
14,
15]. Active balancing uses active circuits to transfer energy from a high-energy cell to a low-energy cell. It is important to mention that active balancing and its circuits are now widely applied in PV to address the adverse effects of partial shading conditions (PSCs) on series-connected PV modules/submodules, removing the obstacles to maximum power extraction [
16,
17,
18,
19]. According to the path of energy transfer during balancing, active balancing can be further divided into the following categories: Adjacent Cell-to-Cell (AC2C), Direct Cell-to-Cell (DC2C), Cell-to-Pack (C2P), Pack-to-Cell (P2C), Any Cell-to Any Cell (AC2AC), and Multicell-to-Multicell (MC2MC) [
20].
The characteristic of Adjacent Cell-to-Cell (AC2C) is the transfer of energy by setting balancing main circuits between adjacent cells [
21,
22,
23,
24]. The advantage of this approach is that the whole balancing circuit can be controlled using an easy approach, and the balancing process has high reliability. However, when the cells involved in balancing are located far apart, the balancing energy needs to be sequentially transferred through multiple balancing main circuits, resulting in slow balancing speed and energy loss during the balancing process, thereby reducing the balancing efficiency. To address the drawbacks of AC2C, Direct Cell-to-Cell (DC2C) is studied in [
25,
26,
27]. Compared to AC2C, DC2C typically requires only a single universal circuit for balancing, simplifying the structural design of the balancing circuit and reducing cost. In addition, since the balancing energy can be directly transferred between any two cells, DC2C addresses the problem present in AC2C where the energy transfer efficiency is low when the cells being equalized are located far apart, thus improving balancing efficiency. However, the disadvantage of DC2C is also obvious: only two cells can be balanced at a time, which means that when a larger number of cells are involved in the balancing process, the other cells have to wait, resulting in longer balancing time.
Cell-to-Pack (C2P), as shown in [
28,
29,
30], involves transferring energy from a cell to the whole battery pack. When there are few cells with high power, the C2P balancing method can improve balancing. However, the balancing speed of this method is very slow when there is only one cell with low power in the pack. In contrast to C2P, Pack-to-Cell (P2C), as shown in [
31,
32], refers to the transfer of energy from the whole battery pack to a cell. This approach enhances balancing speed when there are fewer cells with low power. Like C2P, the balancing speed of P2C is also very slow when there is only one cell with high power in the battery pack. Furthermore, C2P and P2C will suffer from external energy loss due to the unrelated cells in the battery pack being charged or discharged.
Any Cell-to-Any Cell (AC2AC), as shown in [
33,
34,
35], can realize transmission of energy between any cells. The advantage of this approach is that any cell within the battery pack can participate in the balancing process and transfer energy to the target cell, thereby improving balancing efficiency and reducing unnecessary energy loss. However, each cell needs to be equipped with a balancing main circuit to implement this method. Although the circuit is scalable, it can easily lead to complexities and high cost. Furthermore, modular design can also result in inevitable parameter variations among the balancing main circuits. For example, Shang et al. [
33] used a multi-winding transformer as the balancing main circuit, which offers the advantages of small size and low cost. However, ensuring the consistency of each winding’s parameter is challenging. Zhou et al. [
34] used switched capacitors to implement AC2AC, leading to lower complexity and ease of scalability. However, the massive use of capacitors and MOSFETs in the circuit leads to parameter variations among the components and increased cost. In [
35], Altemose et al. used a resonant reset forward converter to achieve balancing. This type of forward converter has a simple structure and achieves demagnetization through LC resonance between the excitation inductance on the primary side of the converter and the capacitors connected in parallel to the MOSFETs. Additionally, this circuit features low design complexity and ease of scalability. However, the widespread use of forward converters increases circuit cost and mismatch issues can arise due to variations in the inductance values of the converter and resonant capacitance of the resonant capacitor in practice. In addition, AC2AC balancing is typically performed automatically based on the voltage (or SOC) of each cell within the battery pack. This results in a dispersed energy transfer during the balancing process, leading to longer balancing times.
Compared with the aforementioned balancing methods, Multi-Cell-to-Multi-Cell (MC2MC) [
36,
37,
38] not only allows multiple cells to participate in a single balancing process for energy transfer, but also enables energy transfer between battery clusters. The concentration of energy transfer during the balancing process enhances balancing speed and reduces energy losses during the transfer. The circuit structure of MC2MC is typically composed of a common balancing main circuit and a switch matrix. Shang et al. [
36] proposed a balancing circuit based on a matrix LC resonant converter (MLCC) balancing circuit, which consists of an LC resonant converter and a relay matrix. This balancing circuit features a simple circuit structure and low cost. Luo. X et al. [
37] proposed a balancing circuit based on a bipolar-resonant LC converter (BRLCC), which utilizes an LC resonant converter as the balancing main circuit and introduces a symmetrical switch matrix composed of bidirectional MOSFETs, further simplifying the structure of the switch matrix. Luo. S et al. [
38] proposed a balancing circuit based on a Buck-Boost converter, which simplifies the structure of the switch matrix through cell grouping. However, the LC resonant converters used in [
36,
37,
38] often require bulky magnetic components and high-voltage switches when applied to balance high-voltage and large-capacity battery packs [
39]. Additionally, the use of numerous MOSFETs in the switch matrix in [
37] not only requires complex driver circuits, increasing circuit costs, but also adds complexity to circuit control. Although the structure of the switch matrix is simplified in [
38], there is a possibility of circuit malfunction when cells within the same group are involved in balancing, indicating a lower robustness of the circuit.
In general, the MC2MC balancing circuits proposed so far have improved balancing speed, but there is still room for optimizing balancing power, circuit cost, design, and control. Compared with the aforementioned converters, transformer-based balancing circuits offer advantages such as simplified control and easy isolation [
39].
In this article, a lithium-ion battery active balancing circuit based on a forward converter with resonant reset and a relay matrix is proposed. The MC2MC balancing method is realized by the proposed balancing circuit. The balancing main circuit utilizes the forward converter. It has a simple control method and enables high-power balancing. Compared to the switching matrix consisting of a MOSFET, the switching matrix consisting of relay is easier to drive and control. As a result, the costs of the balancing circuit are reduced.
The contributions of this paper are as follows: The proposed balancing circuit based on a forward converter with resonant reset is an improvement and optimization of the work presented in [
35], while also referencing the switch matrix proposed in [
36] for circuit design. These works simplify the structure of the balancing circuit and increase the balancing power. Furthermore, an “adaptive selection mode based on the state of high energy battery” balancing strategy is proposed. This strategy provides the proposed balancing circuit with multiple balancing modes and flexible balancing paths to deal with unbalancing states, thereby improving the balancing speed.
The remaining sections of this paper are organized as follows.
Section 2 presents the balancing circuit structure and operating principle of the proposed topology, along with parameter analysis.
Section 3 verifies the proposed balancing circuit through simulation of a six-cell battery circuit and analyzes the balancing performance.
Section 4 introduces the “adaptive selection model based on the state of high energy battery” balancing strategy.
Section 5 describes the experimental setup, where an eight-cell battery pack configuration is selected to validate the effectiveness of the proposed balancing circuit and strategy. The discussion and comparison of the balancing circuit is presented in
Section 6. Finally,
Section 7 provides the conclusions of this paper.
6. Discussion
This section systematically evaluates the balancing circuits in terms of their size, cost, balancing speed, and switch driving. Assuming a battery pack is composed of n cells, the component requirements for different balancing circuits are shown in
Table 5.
To provide a more detailed comparison of different balancing circuits, a battery pack of eight cells is selected for analysis in
Table 5. The component prices were referenced from [
30], where the approximate unit prices for each component are as follows: M (MOSFET, USD 0.2), D (Diode, USD 0.15), L (Inductor, USD 0.6), C (Capacitor, USD 0.2), RE (Relay, USD 0.2), T (Transformer, USD 1), DR (Switch Driver IC, USD 0.8).
According to the comparisons in
Table 5 and
Table 6, the SC circuit in [
24] needs 2n MOSFETs to switch, and it requires n-1 capacitors and inductors for ZCS, resulting in a larger circuit size Although each switch is configured with a driver IC, the control of each switch group is achieved through a pair of complementary PWM signals, simplifying the overall driving scheme. However, the inclusion of numerous driver ICs, MOSFETs, inductors, and capacitors significantly increases the cost of the balancing circuit. Furthermore, the AC2C balancing approach employed by this circuit leads to long balancing time and slower speed, which remains its major drawback.
The LCSR circuit utilized in [
26] results in a significant reduction in the size of the balancing circuit and enables ZCS, thus reducing switching loss. However, the use of bipolar switches in the switch matrix of the circuit still requires many MOSFETs to be implemented, which increases the complexity of the driver design. Although only one inductor and capacitor are needed, the adoption of bipolar switches still requires a large number of driver ICs, resulting in relatively high cost. In addition, this circuit achieves DC2C balancing, which is faster than AC2C, but the overall balancing speed is generally moderate.
In [
30], C2P balancing is achieved by multi-winding flyback converters. Although a certain number of MOSFETs and ICs are needed to be switches and drivers, no additional inductor and capacitor are required in this circuit. As a result, the circuit structure is simple, and the design of the drive scheme is easy. Therefore, the circuit has low cost and a small size. However, this balancing circuit requires a longer balancing time and the balancing speed is moderate.
In [
35], the modularized forward converter with resonant reset introduces size and cost issues for the circuit. It achieves AC2AC balancing, but the energy transfer is more dispersed, resulting in a longer balancing time for the circuit. In terms of switch driving, the adoption of phase-locked loop control simplifies the design of the driving scheme.
Like [
26], the HBLC circuit in ref. [
37] only uses one inductor and capacitor. It has a smaller size and reduces switch losses by achieving ZCS. However, the extensive use of bipolar switches and the implementation of MC2MC balancing make the design of switch driving more challenging, resulting in higher cost. Although the circuit achieves shorter balancing time through MC2MC balancing, further reduction in balancing time would require lager inductors and capacitors, leading to an increase in the size of the circuit.
Based on the comparisons above, the balancing circuit proposed in this paper has a fast balancing speed and a simple structure of balancing the main circuit. Additionally, the ZVS of MOSFETs is realized by using the inherent LC structures of the converters and the switching losses are reduced. Moreover, the use of fewer MOSFETs simplifies the design of switch driving, as it only requires a single UCC27524 chip. Consequently, the proposed circuit has a lower cost. However, the large number of relays employed leads to the large size of the proposed balancing circuit, which is the significant limitation of this balancing circuit.