Abstract: Dust accumulation on the surface of solar panels reduces light transmittance, degrades power generation efficiency, and may induce hot‑spot effects that permanently damage photovoltaic modules. To improve cleaning efficacy while protecting the panels, this study systematically investigates the contact mechanism and key parameters in roller brush cleaning of solar panels. A theoretical analysis reveals the adhesion forces between dust particles and the solar panel surface, and a mechanical model is established for the bristle‑panel contact. Using MATLAB, the compound motion trajectory of the roller brush is simulated, and an optimal rotational speed of 200 r/min is determined. Transient dynamic simulations in ANSYS Workbench compare two bristle materials – nylon and polypropylene – under the same operating conditions. The results show that nylon bristles generate greater contact pressure and frictional stress at the contact region, with a safety factor of 7.3, significantly outperforming polypropylene. Field cleaning experiments are conducted on naturally soiled solar panels, and the cleaning efficiency is quantified by Image‑J grayscale analysis. With nylon bristles and a rotational speed of 200 r/min, the system achieves a cleaning efficiency of 88.01 %. This study provides a theoretical foundation and experimental support for material selection and parameter optimization of roller brush cleaning devices for solar panels.
Keywords: solar panels; roller brush cleaning; contact mechanism; mechanical model; finite element analysis; numerical simulation; cleaning efficiency
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1. Introduction
Solar energy is one of the most promising renewable energy sources worldwide. The efficiency of power conversion in solar panels depends critically on the surface condition of the photovoltaic modules. In outdoor environments, dust, bird droppings, pollen, and other contaminants accumulate on the glass cover, reducing the transmittance of incident sunlight. Numerous studies have shown that a dust layer as thin as 0.1 mm can reduce the power output by 5 %–20 %, and severe accumulation can lead to a drop of 17 %–40 % in efficiency. Moreover, localized heating caused by non‑uniform soiling may trigger the hot‑spot effect, which permanently damages the solar cells, solder joints, and encapsulation materials. Therefore, effective and safe cleaning of solar panels is essential for maintaining long‑term performance and reliability.
Various cleaning technologies have been developed, including manual washing, high‑pressure water jets, semi‑automatic sweepers, and robotic cleaning systems. Among these, robotic cleaning has gained increasing attention due to its high safety, automation capability, and adaptability to large‑scale photovoltaic plants. The core component of such robots is the roller brush assembly, which determines the cleaning efficiency and the degree of mechanical wear on the panel surface. The brush bristle material, stiffness, geometry, and operating parameters (rotational speed, penetration depth, forward velocity) directly influence the contact forces, the removal of dust particles, and the potential for surface scratching. However, most existing studies focus on the overall robot design and path planning, while the fundamental contact mechanics and parameter optimization of the roller brush remain insufficiently explored.
In this work, we aim to fill this gap by performing a comprehensive analysis of the contact mechanism between the roller brush and the solar panel surface. We first derive the adhesion forces acting on dust particles and establish a mechanical model for a single bristle contacting the panel. Then we design an integrated roller brush cleaning system and simulate the compound motion trajectory of the bristle tip using MATLAB, determining the optimal rotational speed. Subsequently, transient dynamic finite element analysis is carried out in ANSYS Workbench to compare the contact performance of two common bristle materials – nylon and polypropylene (PP). Finally, field cleaning experiments on naturally soiled solar panels are conducted, and the cleaning efficiency is evaluated by image‑based grayscale analysis. The results provide practical guidance for selecting bristle materials and setting operating parameters for roller brush cleaning systems on solar panels.
2. Theoretical Analysis of Dust Adhesion and Bristle‑Panel Contact Mechanics
2.1 Optical effect of dust on solar panels
When light passes through a dust layer on a solar panel, part of the incident energy is absorbed and converted into heat, part is scattered, and only a fraction reaches the photovoltaic cell. The reduction in light transmittance directly decreases the photocurrent. Additionally, prolonged exposure to acidic or alkaline contaminants can corrode the glass cover, creating surface micro‑cavities that cause further diffusion and reflection losses. These optical degradation mechanisms underscore the necessity of regular and effective cleaning.
2.2 Adhesion forces of dust particles on solar panels
To remove dust particles efficiently, it is necessary to understand the forces that bind them to the panel surface. The dominant adhesion forces are van der Waals force and electrostatic forces (including contact electrostatic force and double‑layer electrostatic force). The van der Waals force between a spherical dust particle and a flat surface can be expressed as:
$$
F_w = \frac{h_w R}{8\pi D_0^2} – \frac{h_w R}{8\pi (D_0 + R)^2}
$$
where \( h_w \) is the Lifshitz constant (typically 0.96–1.44 eV), \( R \) is the particle radius, and \( D_0 \) is the intermolecular separation at intimate contact (on the order of 0.4 nm). The electrostatic forces are given by:
$$
F_{es} = \frac{Q^2}{4\pi\varepsilon\varepsilon_0 (R + D_0)^2}, \quad F_{el} = \frac{\pi\varepsilon\varepsilon_0 R U^2}{R + D_0}
$$
where \( Q \) is the particle charge, \( U \) is the contact potential difference, \( \varepsilon \) is the relative permittivity of air (≈1), and \( \varepsilon_0 = 8.85\times10^{-12} \) F/m. Based on previous measurements for various particle sizes, the van der Waals force ranges from \(10^{-11}\) to \(10^{-9}\) N, while electrostatic forces are typically below \(10^{-12}\) N. Hence, van der Waals force is the dominant adhesion mechanism that must be overcome by the brush bristle.
2.3 Mechanical model of bristle‑panel contact
When the roller brush presses against the solar panel, the bristles deform and generate a normal contact force \( N \). An empirical formula for the elastic contact force of a single bristle is:
$$
N = 0.17 \; E \, J \, z_B \left( \frac{Y_K + R_1}{S} \right)^{1/8} \arccos\!\left( \frac{Y_K}{R_1 + S} \right)
$$
where \( E \) is the Young’s modulus of the bristle material, \( J \) is the polar moment of inertia of the bristle cross‑section, \( z_B \) is the number of bristles in contact with the panel, \( Y_K \) is the vertical distance between the roller shaft and the panel, \( R_1 \) is the roller shaft radius, and \( S \) is the bristle length. The deformation angle \( \beta \) between the bristle and the panel surface is related to the lateral deflection \( L \) of a point 10 mm from the shaft center:
$$
\alpha = 2\arcsin\!\left( \frac{L}{2(10+R_1)} \right), \quad \beta = 90^\circ + \alpha
$$
The larger the angle \( \beta \), the greater the bristle deflection, leading to higher contact area and larger normal force. Therefore, to achieve effective cleaning, the brush must be designed such that the contact force exceeds the adhesion forces of dust particles while remaining below the threshold that could damage the panel surface.
| Force type | Magnitude (N) |
|---|---|
| van der Waals force | \(10^{-11}\) – \(10^{-9}\) |
| Contact electrostatic force | ≤ \(10^{-12}\) |
| Double‑layer electrostatic force | \(10^{-13}\) – \(10^{-12}\) |
3. Design and Kinematic Analysis of the Roller Brush Cleaning System
3.1 System design
We designed a roller brush cleaning system consisting of a dust cover, a 24 V DC brushless geared motor (power 60–100 W, torque ≥1.5 N·m, speed adjustable up to 350 r/min, protection class IP54), a timing belt drive with a 1:1 ratio, and a roller brush with a diameter of 160 mm. The bristles are 60 mm long, and the central drum diameter is 40 mm. The control system uses an Arduino Mega as the main controller, an MSSD‑20LMA motor driver, encoders and torque sensors for feedback, and a 24 V, 12 000 mAh Li‑FePO₄ battery pack. The system is designed for autonomous cleaning of solar panels in large‑scale photovoltaic plants.
3.2 Compound motion trajectory analysis
When the robot moves forward at a constant speed \( v \), each bristle tip undergoes a combination of rotation and translation. The horizontal and vertical displacements of a bristle tip are described by:
$$
X = vt + R \cos\!\left( \omega t + \theta – \frac{\pi}{2} \right)
$$
$$
Y =
\begin{cases}
R \sin\!\left( \omega t + \theta – \frac{\pi}{2} \right) + \frac{\pi R}{2}, & \frac{2\pi i – \pi}{\omega} < t \le \frac{2\pi i}{\omega} \\[6pt]
\frac{\pi R}{2} \cos\!\left( \frac{\omega \theta}{\pi} \right), & \frac{2\pi i}{\omega} < t \le \frac{2\pi(i+1) – \pi}{\omega}
\end{cases}
$$
where \( R \) is the brush radius (80 mm), \( \omega \) is the angular velocity, \( \theta \) is the initial phase angle, and \( i \) is the number of revolutions. We set \( v = 6 \) km/h and simulated the trajectories for three rotational speeds: 100, 200, and 300 r/min.
| Rotational speed (r/min) | Number of cycles in 0.5 s | Average tip speed (m/s) | Trajectory characteristics |
|---|---|---|---|
| 100 | 3 | 1.758 | Large spacing between contacts, possible incomplete cleaning |
| 200 | 7 | 2.006 | Uniform distribution, adequate impact without excessive overlap |
| 300 | 10 | 2.644 | Dense overlap, higher energy consumption and potential bristle wear |
From the simulation, 200 r/min provides the best balance between cleaning coverage and mechanical stress. At this speed, the bristle tip trajectories are nearly evenly spaced, ensuring that every area of the solar panel is contacted several times without excessive redundant impacts. Therefore, we adopted 200 r/min as the optimal operating speed for subsequent analysis and experiments.
4. Finite Element Simulation of Bristle Contact
4.1 Model setup
To compare the contact performance of nylon and polypropylene (PP) bristles, we performed transient dynamic simulations using ANSYS Workbench. The roller brush model was simplified: a single cluster of bristles was represented as a single bristle with a diameter of 1 mm (equivalent cross‑sectional area to a real cluster of 0.25 mm fibers). The brush outer diameter was 160 mm, bristle length 60 mm, and drum diameter 40 mm. The solar panel was modeled as a rigid fixed body with typical glass properties. The brush was constrained to rotate about the Z‑axis at 200 r/min (3.33 r/s), and a friction contact was defined between the bristles and the panel surface. The material properties used are listed in Table 3.
| Material | Young’s modulus (GPa) | Poisson’s ratio | Density (g/cm³) |
|---|---|---|---|
| Nylon | 3.0 | 0.40 | 1.16 |
| Polypropylene (PP) | 1.4 | 0.42 | 0.91 |
4.2 Simulation results
The simulation outputs for total deformation, equivalent (von Mises) stress, frictional stress, contact pressure, and strain energy were extracted for both materials. The key quantitative results are summarized in Table 4.
| Parameter | Nylon | PP |
|---|---|---|
| Maximum equivalent stress (MPa) | 10.3 | 4.9 |
| Maximum contact pressure (kPa) | 21.5 | 13.2 |
| Maximum frictional stress (kPa) | 8.7 | 5.1 |
| Total deformation (mm) | 0.85 | 0.86 |
| Safety factor (yield strength / max stress) | 7.3 | 6.1 |
Both materials exhibit similar total deformation because the geometry and boundary conditions are identical. However, nylon bristles generate higher contact pressure and frictional stress on the solar panel surface, indicating stronger dust removal capability. The equivalent stress in nylon is about twice that in PP, but the yield strength of nylon is approximately 75 MPa, yielding a safety factor of 7.3, which is still well above the typical design requirement of 2–3. In contrast, PP with a yield strength of about 30 MPa gives a safety factor of 6.1. Both are safe, but nylon offers a higher margin against fatigue and better wear resistance. Therefore, nylon is the preferred bristle material for the roller brush cleaning system.
5. Experimental Validation
5.1 Test setup
Field cleaning experiments were conducted on a naturally soiled solar panel located at an industrial site in Bengbu, China. The panel had accumulated a uniform layer of dust over several months. The roller brush used nylon bristles and was operated at the previously determined optimal speed of 200 r/min. The robot traversed the panel at a constant forward speed of 6 km/h. Photographs were taken before and after cleaning under uniform lighting conditions.
5.2 Image‑based cleaning efficiency evaluation
We used Image‑J software to perform grayscale analysis on the captured images. The images were converted to 8‑bit grayscale, and a region of interest covering the entire panel area was selected. The dust‑covered area (pixels with gray values below a threshold) was measured before and after cleaning. The cleaning efficiency \( \eta \) is defined as:
$$
\eta = \frac{A_0 – A_1}{A_0} \times 100\%
$$
where \( A_0 \) and \( A_1 \) are the dust areas (in pixels²) before and after cleaning, respectively. The results are summarized in Table 5.
| Condition | Number of dust‑covered regions | Total dust area (pixels²) | Average region size (pixels²) | Area fraction (%) |
|---|---|---|---|---|
| Before cleaning | 7,171 | 11,303,733 | 1,576.3 | 80.01 |
| After cleaning | 90,465 | 1,355,807 | 14.99 | 9.45 |
Substituting into the formula gives:
$$
\eta = \frac{11,303,733 – 1,355,807}{11,303,733} \times 100\% = 88.01\%
$$
This high cleaning efficiency confirms that the combination of nylon bristles and 200 r/min rotational speed is highly effective for removing typical dust deposits from solar panels. Visual inspection also showed no visible scratches or damage to the panel surface after cleaning, indicating that the contact pressure and frictional stresses are within safe limits.
6. Conclusion
In this study, we systematically investigated the contact mechanism and key parameters of a roller brush cleaning system for solar panels. The main findings are summarized as follows:
- Dust adhesion on solar panels is mainly governed by van der Waals forces ranging from \(10^{-11}\) to \(10^{-9}\) N, which must be overcome by the brush bristles.
- A kinematic analysis of the brush bristle tip trajectory, simulated in MATLAB, identified a rotational speed of 200 r/min as optimal for uniform coverage and efficient cleaning at a forward speed of 6 km/h.
- Transient finite element simulations show that nylon bristles produce higher contact pressure (21.5 kPa) and frictional stress (8.7 kPa) compared to polypropylene bristles, while maintaining a safety factor of 7.3, making nylon the superior material for this application.
- Field cleaning experiments using nylon bristles at 200 r/min achieved a cleaning efficiency of 88.01 %, validated by Image‑J grayscale analysis, without any surface damage to the solar panel.
These results provide a solid theoretical and experimental basis for the design and optimization of roller brush cleaning systems for solar panels. Future work could explore the influence of bristle geometry (e.g., diameter, length, density) on cleaning efficiency and panel wear, as well as the adaptation of the cleaning parameters for different types of soiling (e.g., oily residues, cementitious dust). The methodology developed here can be extended to guide the development of intelligent, adaptive cleaning robots for photovoltaic power plants.