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.
|Title of host publication||International Conference on Knowledge-Based and Intelligent Information and Engineering Systems|
|Number of pages||10|
|Publication status||Published - 2011|
|Event||International Conference on Knowledge-Based and Intelligent Information and Engineering Systems - Kaiserslautern, Germany|
Duration: 12 Sep 2011 → 14 Sep 2011
Conference number: 15
|Conference||International Conference on Knowledge-Based and Intelligent Information and Engineering Systems|
|Abbreviated title||KES 2011|
|Period||12/09/11 → 14/09/11|
Bibliographical noteThe full text of this article is not available from the repository.
- sensor positioning
- heating ventilation and air condition (HVAC)
- mutual information
Hintea, D., Brusey, J., Gaura, E., Beloe, N., & Bridge, D. (2011). Mutual information-based sensor positioning for car cabin comfort control. In International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (pp. 483-492) https://doi.org/10.1007%2F978-3-642-23854-3_51