# Modeling and Evaluating GaN HEMTs for Efficient Multicell Battery Balancing with Dual-Active Bridge Converters

Robert Alfie S. Pena, Boud Verbrugge, Omar Hegazy

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Robert Alfie S. Pena, Boud Verbrugge, Omar Hegazy. Modeling and Evaluating GaN HEMTs for Efficient Multicell Battery Balancing with Dual-Active Bridge Converters. The 26th European Conference on Power Electronics and Applications, GDR SEEDS France & EPE Association, Mar 2025, Paris, France. 10.34746/epe2025-0285. hal-05082279

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# Modeling and Evaluating GaN HEMTs for Efficient Multicell Battery Balancing with Dual-Active Bridge Converters

Robert Alfie S. Peña¹,², Boud Verbrugge¹,², and Omar Hegazy¹,²

¹VRIJE UNIVERSITEIT BRUSSEL (VUB)

MOBI-EPOWERS Research Group, ETEC Department, Vrije Universiteit Brussel (VUB)

1050 Brussels, Belgium

²FLANDERS MAKE

3001 Heverlee, Belgium

Tel.: +32 / (2) - 629.29.92

E-Mail: omar.hegazy@vub.be

URL: https://mobi.research.vub.be/epowers-research-group

## ACKNOWLEDGMENT

This research has received funding within the Chips Joint Undertaking (Chips JU), a public-private partnership in collaboration with the European Union's Horizon Europe (HORIZON) Framework Programme and National authorities under grant agreement number 101112306 (EcoMobility). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them. The authors also acknowledge Flanders Make for the support to their research group.

*Index Terms*—Battery management system (BMS), gallium nitride (GaN), bi-directional converters, dual active bridge (DAB) dc-dc converter.

*Abstract*—This paper evaluates the feasibility of gallium nitride (GaN) high-electron-mobility transistors (HEMTs) in battery active balancing circuits. A comparative analysis of GaN models, including loss and efficiency, is presented, which demonstrates the superior performance of GaN-based solutions and highlights its potential in efficient and reliable battery management systems (BMSs).

## I. INTRODUCTION

Battery management systems (BMSs) are critical components in ensuring optimal performance and longevity of battery packs. Passive balancing, while simpler and more cost-effective, relies on dissipating excess energy as heat, leading to energy inefficiency.

Active balancing, on the other hand, transfers energy between cells, maximizing pack utilization. While more complex and expensive, it offers superior performance and extends battery life [1]–[3].

The choice between passive and active balancing hinges on factors such as battery size, application requirements, and cost constraints. As battery technologies advance and energy density increases, the demand for efficient and effective balancing solutions grows, making active balancing an increasingly attractive option.

Building upon the limitations of passive balancing, active balancing emerges as a superior strategy for optimizing battery pack performance. While active balancing presents technical challenges, the advent of gallium nitride high-electron-mobility transistors (GaN HEMTs) offers a compelling solution [4]–[6]. The exceptional characteristics of GaN HEMTs, including high-frequency switching capabilities, low on-resistance, and high power density, make them ideal candidates for active balancing circuits. By enabling faster and more efficient energy transfer between cells, GaN HEMTs can significantly enhance the balancing process, leading to improved battery life, safety, and overall system performance.

Moreover, the high-temperature tolerance of GaN HEMTs is particularly advantageous in BMSs, where thermal management is a critical concern. The ability to operate under demanding conditions without much degradation allows for more compact and efficient circuit designs. Consequently, GaN HEMT-based active balancing solutions can contribute to smaller, lighter, and more powerful battery packs, which are essential
for applications in electric vehicles, renewable energy storage, and portable electronics.

The integration of GaN HEMTs into active balancing circuits represents a significant advancement in battery management technology. By addressing the shortcomings of passive balancing and leveraging the unique properties of GaN, this approach offers the potential to revolutionize battery pack performance and extend the lifespan of energy storage systems.

The proposed paper offers a significant contribution to the BMS literature by providing a loss analysis of GaN HEMTs for active balancing circuits. While the potential benefits of GaN HEMTs in power electronics are well-established, their specific application in battery balancing has not been extensively explored. This paper fills a critical gap by offering a model-based comparison between GaN and Si-based solutions.

Section II explores the use of dual-active bridge (DAB) converters as active balancers. The development of the GaN HEMT model is described in Section III. In section IV, the setup for the DAB converter and multicell battery pack and the comparative analysis of GaN HEMTs and Si MOSFETs in terms of losses and efficiency is presented. Finally, Section V summarizes the findings and highlights the significance of GaN HEMTs for active balancing circuits.

## II. ACTIVE BALANCING THROUGH THE DUAL-ACTIVE BRIDGE (DAB) CONVERTER

A multicell-to-multicell equalization structure is adopted for active balancing due to its exceptional balancing speed, manageable control complexity, high efficiency, and compact design [7]–[10]. In such a structure, a single battery pack services both the high-voltage (HV) and low-voltage (LV) buses in an automotive system [11]. As depicted in Fig. 1, modular dc-dc converters act as equalizers, connected directly to the battery pack. While the high cost of this structure is a production consideration, its outstanding performance more than justifies the investment.

The considered configuration in this paper includes three battery and active balancing modules. Active balancing transfers charge between groups of cells, or multicells. Each multicell is connected to a dedicated dc-dc converter, and the outputs of these converters are paralleled to supply both HV and LV loads. This configuration enables the transfer of charge from overcharged multicells to undercharged ones. The BMS host controller manages the bidirectional flow of current and power.

<figure><img src="image_2.png" /><figcaption>Fig. 1. Multicell-to-multicell equalization structure of active balancing.</figcaption></figure>

While the multicell-to-multicell structure balances multicells efficiently, passive balancing circuits should still be connected to individual cells within each multicell to ensure complete cell balancing.

Fig. 2 illustrates single battery and active balancing modules. A DAB dc-dc converter is selected to implement the active balancing module. The DAB converter's isolated, highly efficient, bidirectional topology, with low rms currents, aligns well with the modular architecture of the multicell-to-cell structure.

Employing GaN in the DAB topology further boosts converter efficiency. Specifically, the DAB converter was designed using enhancement-mode GaN HEMTs with exceptionally low $R_{DS(on)}$, enabling higher operating frequencies and power densities. The converter features a primary and secondary side, galvanically isolated by a high-efficiency transformer. Each side utilizes a full bridge of GaN HEMTs, whose gate controls are illustrated in Fig. 2(b). The bidirectional power flow of the DAB converter is controlled by the phase difference $\phi$ between the primary and secondary sides. Once integrated into the system, active balancing is regulated by the phase of each module.
<figure><img src="image_3.png" /><figcaption>Fig. 2. Control of battery and active balancing modules.</figcaption></figure>

### III. GAN HEMT MODELING

To accurately simulate and analyze GaN transistor behavior, researchers and engineers rely on a variety of modeling techniques. These models can be broadly categorized into three primary types: physical, behavioral, and analytical.

Physical models delve into the intricate details of GaN transistor physics. These models often involve complex mathematical equations and require substantial computational resources. Behavioral models, on the other hand, provide a simplified representation of GaN transistor behavior, focusing on the input-output relationship without delving into the underlying physical mechanisms. Lastly, analytical models employ mathematical equations to approximate GaN transistor characteristics. These models are often derived from simplified assumptions and may not capture the full range of device behavior [12], [13].

While physical models offer the highest level of accuracy, analytical models can still provide valuable insights, especially when computational resources are limited or when a rapid assessment of device performance

is required [12], [13]. By incorporating manufacturer-provided data from the component datasheet, the accuracy of analytical models can be enhanced. Refining the model parameters against datasheet values in this paper increases the confidence in the obtained results. This approach allows to effectively balance accuracy and computational efficiency, making analytical models a valuable tool for design and analysis in the context of GaN HEMT-based active balancing circuits.

This paper utilizes an analytical equivalent circuit model to accurately represent the behavior of GaN HEMTs within the DAB converter employed for active balancing in a BMS. To accurately represent the GaN HEMT's behavior as a Simscape model in MATLAB & Simulink, the *I-V* and *C-V* characteristics were meticulously modeled using optimized lookup tables in the Curve Fitting Toolbox. These lookup tables were generated based on the extracted *I-V* and *C-V* data, capturing the nonlinear relationships between the device's terminal voltages and currents. By incorporating these lookup tables into the Simscape model, we effectively captured the complex dynamics of the GaN HEMT, enabling precise simulation and analysis of its performance.

#### A. GaN HEMT *I-V* characteristics model

The chosen analytical equivalent circuit model builds upon the established procedure presented in [13]. The specific GaN HEMT model employed in this study is the GS61008P from GaN Systems, part of Infineon Technologies [14]. This selection was driven by its exceptionally low $R_{DS(on)}$ characteristic, which is crucial for minimizing conduction losses and maximizing efficiency within the DAB converter. Fig. 3 illustrates the key elements of the analytical equivalent circuit model for the GS61008P. These elements include terminal resistances, nonlinear interterminal capacitances dependent on interterminal voltages, and a voltage-controlled current source representing the channel current.

Like metal-oxide-semiconductor field-effect transistors (MOSFETs), GaN HEMTs exhibit three distinct operating regions: cutoff, active, and ohmic. This similarity allows us to leverage the extensive body of knowledge developed for MOSFETs to analyze and predict the behavior of GaN HEMTs. Specifically, the transfer and output characteristics provided in GaN HEMT datasheets can be directly used to model the device's *I-V* relationship. By understanding these characteristics, we can accurately determine the device's current and voltage behavior under various operating conditions, facilitating the design and optimization of GaN HEMT-based circuits.
<figure><img src="image_4.png" /><figcaption>Fig. 3. Equivalent circuit model of a GaN HEMT.</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>Fig. 4. Smoothing spline model fit of GS61008P GaN HEMT transfer characteristics.</figcaption></figure>

The I-V characteristics of GaN HEMTs is described by the following model [13]:

$$i_{\text{ch}} = \begin{cases} f_1(v_{\text{GS}}), & \text{if } v_{\text{DS}} > v_{\text{GS}} - v_{\text{th}} \ge 0 \text{ or} \\ & v_{\text{DS}} > 0 > v_{\text{GS}} - v_{\text{th}} \\ f_2(v_{\text{GS}}, v_{\text{DS}}), & \text{if } v_{\text{GS}} - v_{\text{th}} > v_{\text{DS}} \ge 0 \\ -f_3(v_{\text{GD}}), & \text{if } -v_{\text{DS}} > v_{\text{GD}} - v_{\text{th}} \ge 0 \text{ or} \\ & -v_{\text{DS}} > 0 > v_{\text{GD}} - v_{\text{th}} \\ -f_4(v_{\text{GD}}, -v_{\text{DS}}), & \text{if } v_{\text{GD}} - v_{\text{th}} > -v_{\text{DS}} > 0 \end{cases} \quad (1)$$

where $v_{\text{GS}}$, $v_{\text{GD}}$, $v_{\text{DS}}$, and $v_{\text{th}}$ are the gate-to-source, gate-to-drain, drain-to-source, and threshold voltages, respectively. The functions $f_1$, $f_2$, $f_3$, and $f_4$ are the channel currents in different regions of operation. $f_1(v_{\text{GS}})$ describes GaN HEMT operation in the forward cutoff or active region modeled by a smoothing spline fit of the transfer characteristics, as seen in Fig. 4. Data were extracted from the transfer curve using WebPlotDigitizer [15]. On the other hand, $f_2(v_{\text{GS}}, v_{\text{DS}})$ represents operation in the forward ohmic region, which is modeled by a lowess surface fit of the output characteristics seen in Fig. 5.

The reverse characteristics of GaN HEMTs, $f_3(v_{\text{GD}})$ and $f_4(v_{\text{GD}}, -v_{\text{DS}})$, can easily be obtained from the forward characteristics by changing $v_{\text{GS}}$ and $v_{\text{DS}}$ in $f_1$ and $f_2$ to $v_{\text{GD}}$ and $-v_{\text{DS}}$ [13].

## B. GaN HEMT C-V characteristics model

Accurate C-V characteristic modeling is essential for precisely describing the dynamic behavior of GaN HEMTs and, consequently, the switching process. Datasheets typically provide curves for input capacitance $C_{\text{ISS}}$, output capacitance $C_{\text{OSS}}$, and reverse capacitance $C_{\text{RSS}}$ as functions of $v_{\text{DS}}$ allowing data extraction.

<figure><img src="image_6.png" /><figcaption>Fig. 5. Lowess surface model fit of GS61008P GaN HEMT output characteristics with 10% span.</figcaption></figure>

Equations (2)–(4) allow us to derive the curves for $C_{\text{GS}}$, $C_{\text{GD}}$, and $C_{\text{DS}}$ with respect to $v_{\text{DS}}$ [13]:

$$C_{\text{ISS}} = C_{\text{GS}} + C_{\text{GD}} \quad (2)$$

$$C_{\text{RSS}} = C_{\text{GD}} \quad (3)$$

$$C_{\text{OSS}} = C_{\text{DS}} + C_{\text{GD}} \quad (4)$$

It is noteworthy that $C_{\text{GS}}$ remains relatively constant with respect to $v_{\text{DS}}$, leading to its common approxi-
mation as a constant in conventional analytical models. However, this simplification overlooks the fact that all three interelectrode capacitances are inherently nonlinear and depend on their respective applied voltages [13]. For instance, $C_{GS}$ is strongly influenced by $v_{GS}$, while $C_{GD}$ and $C_{DS}$ are primarily related to $v_{GD}$ and $v_{DS}$, respectively.

Given the symmetrical structure of GaN HEMTs, these three nonlinear capacitances exhibit symmetrical behavior with regard to their respective voltages. To achieve accurate C-V characteristic models, it is imperative to fully utilize the datasheet information and employ appropriate derivations.

The $C_{DS}(v_{DS})$ smoothing spline fit, shown in Fig. 6, can be readily obtained by subtracting (3) from (4). Likewise, the $C_{GD}(v_{GD})$ fit, whose plot is seen in Fig. 7, can be extricated from datasheet C-V curves by considering that measurements were made under the condition $v_{GS} = 0$ V, so $v_{DS} = v_{GD}$. It is $C_{GS}(v_{GS})$ that cannot be easily derived from the datasheet [13]. In order to derive the latter, the gate charge $Q_G$ characteristic data had to be extracted and then fed into the following equation [13]:

$$ \frac{dQ_G}{dv_{GS}} = C_{GS}(v_{GS}) + C_{GD}(50 - v_{GS}) \quad (5) $$

where 50 V is the value of $v_{DS}$ at which the gate charge characteristics were measured. Fig. 8 shows the derived $C_{GS}(v_{GS})$ capacitance. Due to curve fitting lookup table optimization, there is a small difference between the model and the derived curve from the datasheet, unlike the less noticeable errors in the two previous capacitance models.

## IV. BALANCING SIMULATION

Once built, the analytical GaN HEMT Simscape equivalent circuit model could be used as switches within the DAB structure of Fig. 2(b). This approach allows for a more accurate representation of the GaN HEMT’s dynamic behavior compared to using idealized switches. The analytical model incorporates the nonlinear characteristics of the device leading to more precise predictions of the DAB converter’s performance. This is particularly important for BMS applications where accurate modeling of the switching transients is crucial for loss and efficiency analysis.

### A. DAB specifications

The sizing of battery modules depends on various factors, including the desired energy capacity, voltage level, and application requirements. For example, in an

<figure><img src="image_7.png" /><figcaption>Fig. 6. Smoothing spline model fit of GS61008P GaN HEMT drain-source capacitance.</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Fig. 7. Smoothing spline model fit of GS61008P GaN HEMT gate-drain capacitance.</figcaption></figure>

electric vehicle, the battery module’s capacity would be determined by the target driving range and the vehicle’s power consumption profile. The voltage level of the battery module is typically chosen based on the efficiency of the powertrain components and the availability of suitable battery cells. In this paper, the considerations were driven by building a BMS prototype demonstrator
<figure><img src="image_9.png" /><figcaption>Fig. 8. Smoothing spline model fit of GS61008P GaN HEMT gate-source capacitance.</figcaption></figure>

with three battery and active balancing modules. Table I lists the specifications of the balancing system. For a fair comparison, the values in the table are kept the same for two different switches: conventional Si MOSFETs and the latest GaN HEMTs.

<table><caption>TABLE I
BALANCING SYSTEM SPECIFICATIONS</caption><thead><tr><th>Component</th><th>Parameter</th><th>Value</th></tr></thead><tbody><tr><td rowspan="5">Battery module</td><td>Battery model</td><td>L148N58A</td></tr><tr><td>Nominal capacity</td><td>58 Ah</td></tr><tr><td>Voltage</td><td>2.75-4.35 V</td></tr><tr><td>Internal resistance</td><td>0.60-0.80 mΩ</td></tr><tr><td>No. cells in series</td><td>4</td></tr><tr><td rowspan="5">Active balancing module</td><td>Nominal power</td><td>205.9 W</td></tr><tr><td>Nominal output power</td><td>24 V</td></tr><tr><td>Inductor</td><td>1 μH</td></tr><tr><td>Capacitor</td><td>30 μF</td></tr><tr><td>Transformer turns ratio</td><td>0.5:1</td></tr><tr><td></td><td>Frequency</td><td>100 kHz</td></tr></tbody></table>

## B. DAB efficiency

The efficiency results comparing active balancing between DAB structures using Si and GaN transistors, as highlighted in Table II, demonstrate the superior performance of GaN-based solutions. For a fair comparison, BSC070N10NS3 G also from Infineon Technologies,

with almost similar specifications to GS61008P was chosen as the representative Si MOSFET. Due to their lower on-resistance and faster switching speeds, GaN HEMTs exhibit significantly lower switching losses and higher efficiency compared to Si MOSFETs. This translated to improved energy efficiency and reduced switch current stress. Additionally, the high-frequency capabilities of GaN HEMTs enable lower switching losses. Overall, the simulation result highlight the compelling advantages of GaN HEMTs in active balancing circuits, making them a promising technology for enhancing BMS performance.

<table><caption>TABLE II
SI-MOSFET VS. GAN-HEMT DAB ACTIVE BALANCING MODULE</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Si MOSFET</th><th colspan="3">GaN HEMT</th></tr><tr><th>Model</th><th>LTspice</th><th>PLECS</th></tr></thead><tbody><tr><th>Efficiency</th><td>88.01%</td><td>98.13%</td><td>98.05%</td><td>98.21%</td></tr></tbody></table>

For GaN HEMTs, additional simulations were conducted using manufacturer-provided SPICE models in LTspice IV and built-in PLECS models to compare the proposed model with existing modeling and simulation approaches. The results demonstrate the high accuracy of the proposed model.

## V. CONCLUSION

This paper presented an evaluation of GaN HEMTs for active balancing circuits in BMSs. By comparing Si MOSFETs and GaN HEMTs in terms of efficiency, the significant advantages of GaN-based solutions have been demonstrated.

The results of the modeling and analysis indicate that GaN HEMTs offer superior performance in terms of efficiency and high-frequency switching capabilities. These advantages can lead to more compact, efficient, and reliable BMSs. Additional analyses and simulations on the higher initial cost and investment on GaN HEMTs emerge as interesting follow-up studies.

In conclusion, GaN HEMTs represent a promising technology for active balancing circuits. Their exceptional characteristics make them well-suited for addressing the challenges associated with BMSs, particularly in applications that demand high performance and efficiency. As GaN technology continues to mature and costs decline, we anticipate widespread adoption of GaN HEMTs in a variety of battery-powered systems.

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