Title page for etd-0719116-211611


URN etd-0719116-211611 Statistics This thesis had been viewed 342 times. Download 4 times.
Author YI-BIN CHEN
Author's Email Address corn429@gmail.com
Department Institute Of Mechanical Engineering
Year 2015 Semester 2
Degree Master Type of Document Master's Thesis
Language zh-TW.Big5 Chinese Page Count 74
Title The study on the air mixing damper lever control for vehicle A/C system
Keyword
  • temperature control.
  • mixing damper lever control
  • back-propagation neural network
  • Automotive air conditioning systems
  • Automotive air conditioning systems
  • back-propagation neural network
  • mixing damper lever control
  • temperature control.
  • Abstract This thesis study the opening of dampers control in the automotive air conditioning (A/C) system with tuning the fresh air rate, heating air rate and air flow rate to adjust the vehicle cabinet temperature automatically to the desired temperature.
    The state of moist air will changed when the mixing damper lever adjusting, it can derived by look-up the psychrometric chart, but it cannot be used in automatic operation, therefor the artificial neural network data fitting method is applied in this study this paper. Using the back propagation neural network to make data fit the air status as the psychrometric chart and calculate the value of the control parameters.
    By setting different environmental weather conditions, including high temperature (36¢J), medium temperature(26¢J), low temperature (16¢J) and three different relative humidity of 80%, 65% and 50%, the opening of dampers control and air flow rate tuning method proposed in this study is tested. With the computer simulation results, the temperature inside can 100% reach the range of the setting temperature 25„b0.5¢J, the relative humidity may be lower than the average while the adjustment process, it is uncontrollable in this study, it can be study for future research.
    Advisor Committee
  • Cheng-Kuang Huang - advisor
  • Hsiao-Chung Liu - co-chair
  • Ming-Huei Chu - co-chair
  • Files indicate in-campus access immediately and off-campus access at 5 years
    Date of Defense 2016-07-15 Date of Submission 2016-07-21

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