Research on Mechanism Design and Kinematic Characteristics of Self-Propelled Photovoltaic Cleaning Robot

Abstract

A hydraulic drive-based self-propelled photovoltaic panel cleaning robot was developed to tackle the challenges of harsh environmental conditions, difficult roads, and incomplete cleaning of dust particles on the photovoltaic panel surface in photovoltaic power plants. The robot has the characteristics of the crawler wheel drive, rear-wheel-independent turning and three-point-independent suspension design, which makes it adhere to the walking requirements of complex environmental terrains, more flexible in turning and automatically levelling so that the stability of the boom mechanism during walking can be ensured. The kinematics model of the upper arm structure equipped with the end cleaning device was built, and the optimized Circle chaotic map and nonlinear weight factor were introduced to enhance the search ability and convergence speed of the sparrow algorithm. Furthermore, the boom running track was optimized in combination with the seven-order non-uniform B-spline curve. Through optimization, the running time of the boom was reduced by 18.7%, and the cleaning efficiency of photovoltaic panel surface was increased. The effectiveness of self-propelled photovoltaic panel cleaning robot cleaning and the reliability of time-optimal trajectory planning were confirmed through simulation and experiment.

Robotics, Artificial Intelligence, and Drones in Solar Photovoltaic Energy Applications—Safe Autonomy Perspective

“…Table 2 provides a snapshot of some of the RAID applications in Solar PV systems [4,[12][13][14][15][16][17]62,63]. It is important to note that this list is not exhaustive and serves as a representative sample of the diverse range of system implementations that exist, depending on the developers and their specific objectives.…”

“…For solar photovoltaic energy generation, drones equipped with sophisticated cameras and AI algorithms can inspect solar panels to detect faults and damages [12,13], enabling timely maintenance and repair. Autonomous robots can clean solar panels [14], and AI can optimize the operation of Solar PV systems [15]. Additionally, machine learning algorithms can analyse data from solar panels, weather forecasts, and energy markets to predict energy production and consumption patterns, allowing for the system's optimal operation [16,17].…”

Analysis of Soiling Loss in Photovoltaic Modules: A Review of the Impact of Atmospheric Parameters, Soil Properties, and Mitigation Approaches

“…Al Shehri et al [70] mentioned that choosing an optimal brush type is important to meet the required level of cleaning while preventing abrasion, which can lead to the degradation of the transmittance. To address the issues of severe climatic conditions, tough roadways, and incomplete dust particle cleaning on solar module surfaces, an improved robotic cleaning system might be a solution [149].Furthermore, robotic devices consume power, resulting in high operation and maintenance costs, which may not be cost-effective in some applications [150].…”