Priority Factors for Estimating Comfort (May 2018)
Intermediate result from partners COV, CRF, IKA, TECNALIA, TME and VIF.
Result has been achieved on 21 May, 2018 in month 7 of the project.
Windshield and view mirrors fogging-up is a common safety issue experienced by every driver. Unless heating-up the surface, increasing the energy consumption of the heating ventilation and air conditioning (HVAC) system, water vapour condensate on cold surfaces. Surface tension causes the condensed water to form droplets on the windshield and view mirror surfaces, scattering the light and hazardously reducing the driver’s vision.
The objective of the DOMUS project is to reduce the overall energy consumption of future electric vehicles (EVs) in order to increase by 25% the electric range for different ambient conditions. This will be achieved by understanding in depth the comfort perception of EV users before developing reliable methods for designing and assessing the full vehicle context from a user-centric perspective, investigating radically new cabin designs and delivering innovative components, systems and control strategies to meet customer expectations.
The approach taken to identify priority factors is primarily literature based. We considered traditional models of thermal comfort, including Fanger’s PMV, the Berkeley Comfort Model, Standard effective temperature (SET), Equivalent Temperature, ISO and ASHRAE standards alongside more recent approaches from the built environment, such as the Adaptive Comfort models. Apart from thermal aspects, we also examined comfort associated with acoustics, lighting, scent, air quality, and task load. Four different operation points of a distillation column were simulated at MPI leading to four different product compositions.
The primary factor continues to be thermal and this may be encapsulated in a variety of measures and models. Acoustic factors clearly play a role and are likely to have a strong influence on overall holistic comfort. Cognitive factors play a part and it is important to understand these factors even if they are difficult to influence. Other important factors include: lighting, gender, temperature history, scent, physiology, thermal asymmetry, humidity and air quality.
What will it be used for
These results direct subsequent work on obtaining an overall holistic comfort model that includes thermal comfort alongside other, non-traditional, comfort factors.
By optimising holistic comfort, we might do a better job of making people comfortable in the car cabin. By optimising holistic comfort, we might use less energy than would be used by either optimising thermal comfort or merely trying to control cabin temperature within a few degrees.