An Intelligent Thermal Management Fuzzy Logic Control System Design and Analysis Using ANSYS Fluent for a Mobile Robotic Platform in Extreme Weather Applications

Journal of Intelligent and Robotic Systems - Tập 107 - Trang 1-25 - 2023
Misha Afaq1, Ali Jebelli1, Rafiq Ahmad1
1Smart & Sustainability Manufacturing Systems Laboratory (SMART Lab), Department of Mechanical Engineering, University of Alberta, Edmonton, Canada

Tóm tắt

In this paper, various thermal management designs are explored for robotic operation in extreme temperature environments, which includes options for component and chip level electronics heating/cooling like TIM’s, heat sinks, heat spreader, insulation material, and PCM’s. Furthermore, other active/passive thermal management systems are investigated, such as Heat pipes, Loop Heat Pipes (LHP), and Capillary Pump Loop (CPL) developed by NASA, Fuzzy Logic and PID temperature control methods. Some of the thermal management design challenges faced by the heat pipes, LHP, and CPL devices are decrease in the heating/cooling efficiency with abrupt drop in temperatures, costly equipment, high power consumption, and increase in the overall weight of the robot due to several components. With the limited space available inside the robot design, it requires the use of minimal hardware. A Fuzzy Logic temperature controller is considered for the mobile robot to overcome all the aforementioned thermal challenges. A Fuzzy Logic control system is designed and tested in a simulation environment using a flow simulation software; Ansys Fluent, to authenticate its ability to minimize power consumption by controlling the amount of power supplied to the fan/heater based on the current temperature reading from the sensor, a set-point temperature, and if–then based logical rule-base. The heating/cooling simulation setup consists of four heating units located at different locations inside the robot body and two miniature fans. Moreover, three outlets are included on the wall opposite to the fans for the cooling setup. The opening/closing of the outlets is contingent to the temperature inside the robot and will allow the excess heat to escape the robot's body. Based on the internal flow simulation results, the Fuzzy Logic controller setup was able to increase the extreme low temperature of – 40° C to the desired temperature of 8° C in a total time of 80 s and with a maximum power of 10 W for each heating unit and fans rotating at 1800 rpm for air circulation. However, the power output was minimized by the Fuzzy Logic controller as the internal temperature approached closer to the desired temperature. Moreover, an extreme high temperature of 50° C was decreased rapidly to 8° C in a total time of 12 s with the pressure outlet and inner wall temperatures lower than 15° C. However, in a situation where the initial temperature of the pressure outlet and inner wall are the same as the internal air temperature, the electronics can be cooled by the fans through the forced convection method.

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