| Author: | Zhang, Xiaohui |
| Title: | Soft robotic fabric and clothing for adaptive personal thermal management |
| Advisors: | Shou, Dahua (SFT) Fan, Jintu (SFT) |
| Degree: | Ph.D. |
| Year: | 2024 |
| Subject: | Textile fabrics -- Thermal properties Textile fabrics -- Technological innovations Electronic textiles Human comfort Hong Kong Polytechnic University -- Dissertations |
| Department: | School of Fashion and Textiles |
| Pages: | xviii, 206 pages : color illustrations |
| Language: | English |
| Abstract: | Recently, personal thermal management technology has been garnering substantial interest in the fashion and textile field, primarily due to the significance of thermal comfort for human beings. As a fundamental and indispensable requirement, it ensures the optimal performance of the human body. Failure to maintain thermal comfort can cause serious health issues and may even prove fatal in extreme conditions. In general, humans possess a remarkable ability to maintain their core body temperature within a narrow range of around 37 °C. Hence, textile and clothing play a pivotal role in managing body thermal comfort. However, most clothing exhibits only static thermal properties, which may not adequately accommodate complex and unpredictable weather conditions. Thus, this study aims to investigate the thermal behavior of textile and develop fabric and clothing that can adapt to variations in environmental conditions, such as temperature and radiation. Specifically, this study would integrate soft robotic elements with traditional textiles to create smart textiles with dynamic thermal properties, thereby establishing a new paradigm in adaptive personal thermal management. The study explores the innovative application of soft robotics incorporated with textiles to achieve personal thermal regulation. These soft robotic elements have the unique ability to alter the properties of textile, specifically the geometric shape. Such changes in thickness and coverage area can significantly influence the thermal conductivity, thermal convection, or thermal radiation through fabric. This can be particularly beneficial for people experiencing thermal discomfort in different environmental conditions, as the soft robots have the ability to regulate their shape, thereby achieving optimal thermal comfort. These soft robotic elements are highly reversible, which allows for reversible alterations to the shape of the wearable robots. Moreover, soft robotic textiles can be equipped with sensors or responsive materials, which can enable them to automatically adapt to changes in the external environment. Such adaptive thermal management systems are realized through a combination of fabric substrates, soft robotics, and either passive or active control systems, offering a groundbreaking approach to maintaining thermal comfort across diverse conditions. In the first part of the study, we introduced an innovative passive soft robotic fabric engineered for adaptive thermal protection. This fabric leverages the unique capabilities of soft actuators, which in corporate a low boiling point fluid to enable significant volume changes during phase transitions. As ambient temperatures rise, the fluid evaporates, causing the soft actuators to expand. This expansion separates the fabric layers, creating an insulating airgap that effectively minimizes heat transfer from the environment to the skin. Conversely, under normal conditions, the fluid remains in its liquid state, allowing the actuators to contract and the fabric layers to come into contact, thereby reducing thermal resistance. The results of the study demonstrate that the use of a low boiling point fluid within soft robotic elements can dynamically adjust the fabric's thickness, providing reversible thermal insulation. This adaptability ensures personal thermal comfort across diverse environmental conditions, highlighting the transformative potential of soft robotics in advancing thermal management capabilities in textiles. In the second part of the research, we developed dynamic soft robotic clothing specifically designed for adjustable thermal resistance in cold weather conditions. These garments feature soft actuators that mimic the structure of the human skeleton, providing a snug and comfortable fit that ensures both warmth and flexibility. Utilizing pneumatic technology, the actuators employ air as an insulating material, delivering lightweight yet highly efficient thermal performance. A key innovation in this design is the active control system, which allows the clothing to respond swiftly and safely to changes in temperature. Experimental results confirm that the fabric's thickness can be dynamically adjusted to suit various ambient temperatures. The deformation capabilities of the soft robotic elements enable the fabric's geometry to adapt, maintaining body comfort even with a temperature change of up to 5°C. This highlights the significant potential of soft robotics in enhancing the adaptability and comfort of thermal clothing. In the third part of the study, we developed a breathable three-dimensional (3D) knitted fabric that leverages the principles of soft robotics to enhance thermal management. This fabric's intricate 3D structure is achieved through the inherent physical forces of the yarn within the loops, forming a complex sculptural shape through an entirely automated process. The fabric can seamlessly transition between 3D and 2D states, allowing for adjustments in thickness and consequently altering thermal resistance. Additionally, the coated sections of the fabric are designed to stretch and conform to the body's contours during these transitions, enhancing coverage and comfort. The surface coatings also play a critical role in reflecting solar radiation, thereby facilitating radiative cooling. An active control system is integrated into this design, enabling precise control over the deformation of the soft actuators attached to the fabric, thus facilitating the transition between 3D and 2D states. Experimental results demonstrate that when the fabric is stretched from a 3D to a 2D configuration, there is a notable reduction in thermal resistance alongside an effective radiative cooling effect. This underscores the potential of soft actuators in transforming traditional textiles into smart fabrics capable of dynamic thermal regulation and enhanced adaptability to environmental conditions. In conclusion, this research systematically and scientifically developed three innovative soft robotic fabrics designed to provide adaptive personal thermal management. These fabrics, integrated with advanced soft robotics technology, offer dynamic adaptability to varying environmental conditions, ensuring consistent thermal comfort. The evaluation of their thermal properties, supported by a rigorous evaluation system and human trials, demonstrated their effectiveness in real-world scenarios. The integration of soft robotics allows these textiles to dynamically alter their structure and thermal properties, showcasing features such as reversible deformation and lightweight insulation through pneumatic actuators. The fabrics can transition between three-dimensional and two-dimensional states, optimizing thermal resistance and enabling effective radiative cooling through specialized surface coatings. Active control systems further enhance functionality by ensuring quick and responsive adjustments to temperature changes. While the proposed textiles exhibit promising adaptive capabilities, they also present certain limitations that need addressing. Nonetheless, this study not only paves the way for the adoption of robotic technology within the textile and clothing industry but also offers a preliminary exploration that supplements existing research. It provides valuable insights for refining and evolving intelligent textiles. As artificial intelligence (AI) technology becomes increasingly prevalent, its integration with these smart fabrics could further enhance their intelligence and adaptability, marking a significant advancement in the field of personal thermal management. |
| Rights: | All rights reserved |
| Access: | open access |
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