Design of structure and control system of semiconductor refrigeration box

Abstract In order to create low temperature environment for the valve testing, a new type of semiconductor refrigeration box based on semiconductor refrigeration chip and PLC control system is designed. The power of the semiconductor refrigeration chip is determined by calculating the heat dissipation characteristics of the semiconductor refrigeration box. Combining natural convection heat dissipation with forced air cooling, the heat sink of semiconductor refrigeration chip is designed. In the control strategy, switch control is combined with an intelligent control strategy. Adaptive single neuron optimization algorithm based on quadratic optimization is adopted to adjust and optimize the parameters of the PID controllers in real time. Taking into account the limited hardware capabilities of the PLC, the Jacobian information in parameter adjustment is redesigned into a simplified form of identification. The actual test results of refrigeration box show good control performance.

[1]  Mohammad Mehdi Rashidi,et al.  Entropy Generation on MHD Casson Nanofluid Flow over a Porous Stretching/Shrinking Surface , 2016, Entropy.

[2]  Wang Wanyue,et al.  The Research on Semiconductor Refrigeration , 2011 .

[3]  Aihui Wang,et al.  Operator-Based Robust Nonlinear Control Design and Analysis of a Semiconductor Refrigeration Device , 2017, J. Robotics Mechatronics.

[4]  Zhihong Qian,et al.  Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID , 2018, Sensors.

[5]  Zhe Li,et al.  Applications in Medical Reagent Test Equipment of Semiconductor Refrigeration , 2013 .

[6]  Ching-Kuo Wu,et al.  Intelligent Process Control Using a Fuzzy Single Neuron Controller , 2007 .

[7]  Jun Wang,et al.  System design and simulation of constant temperature box using semiconductor refrigeration device , 2010, Int. J. Comput. Appl. Technol..

[8]  Wen Kai Dong.  Coolers Based on Semiconductor Refrigeration Technology for Electric Vehicle On-Board Chargers , 2014 .

[9]  Ye Tian,et al.  Statistical Information Based Single Neuron Adaptive Control for Non-Gaussian Stochastic Systems , 2012, Entropy.

[10]  Y F Pang.  The theoretical analysis and experimental research on the optimal condition of semiconductor refrigeration , 2016 .

[11]  Saffa Riffat,et al.  A novel thermoelectric refrigeration system employing heat pipes and a phase change material: an experimental investigation , 2001 .

[12]  Tian Zhi-feng.  Semiconductor Refrigeration Technology and Its Application , 2012 .

[13]  Min-Sen Chiu,et al.  Adaptive Single-Neuron Controller Design for Nonlinear Process Control , 2008 .

[14]  Paul Berdahl,et al.  Radiant refrigeration by semiconductor diodes , 1985 .

[15]  Petra S. Dittrich,et al.  One-Dimensional Nanostructures: Microfluidic-Based Synthesis, Alignment and Integration towards Functional Sensing Devices , 2018, Sensors.

[16]  Wei Wang,et al.  Neuron adaptive PID control for greenhouse environment , 2015 .

[17]  Huibin Lu,et al.  Numerical analysis of optothermionic refrigeration in semiconductor triple-well structure , 2007 .

[18]  Bin Chen,et al.  Single Neuron PID Control of Aircraft Deicing Fluids Rapid Heating System , 2013, J. Networks.

[19]  Junghui Chen,et al.  Single Neuron Stochastic Predictive PID Control Algorithm for Nonlinear and Non-Gaussian Systems Using the Survival Information Potential Criterion , 2016, Entropy.