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Mutual Information-Based Sensor Positioning for Car Cabin Comfort Control

  • Diana Hintea
  • James Brusey
  • Elena Gaura
  • Neil Beloe
  • David Bridge
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6883)

Abstract

Car cabins are transient, non-uniform thermal environments, both with respect to time and space. Identifying representative locations for the Heating, Ventilation and Air Conditioning (HVAC) system sensors is an open research problem. Common sensor positioning approaches are driven by considerations such as cost or aesthetics, which may impact on the performance/outputs of the HVAC system and thus occupants’ comfort. Based on experimental data, this paper quantifies the spacial-temporal variations in the cabin’s environment by using Mutual Information (MI) as a similarity measure. The overarching aim for the work is to find optimal (but practical) locations for sensors that: i) can produce accurate estimates of temperature at locations where sensors would be difficult to place, such as on an occupant’s face or abdomen and ii) thus, support the development of occupant rather than cabin focused HVAC control algorithms. When applied to experimental data from stable and hot/cold soaking scenarios, the method proposed successfully identified practical sensor locations which estimate face and abdomen temperatures of an occupant with less than 0.7°C and 0.5°C error, respectively.

Keywords

Mutual Information Thermal Comfort Sensor Location Fuzzy Neural Network Joint Entropy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Diana Hintea
    • 1
  • James Brusey
    • 1
  • Elena Gaura
    • 1
  • Neil Beloe
    • 2
  • David Bridge
    • 3
  1. 1.Coventry UniversityPriory LaneUK
  2. 2.Jaguar Land Rover Ltd.WhitleyUK
  3. 3.MIRA Ltd.NuneatonUK

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