Improving Cabin Thermal Comfort by Controlling Equivalent Temperature

Curran, Allen; Peck, S.D.; Schwenn, Tony; Hepokoski, Mark

doi:10.4271/2009-01-3265

Cited by 9 publications

(8 citation statements)

References 3 publications

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“…Intuitively, ET corresponds more closely to the human sensation of environmental temperature than air temperature alone. ET is an accurate predictor for thermal comfort (Mayer and Schwab, 1999), (Curran et al, 2010), (Mola et al, 2004), which integrates the effect of air temperature, mean radiant temperature and relative air velocity. However, its direct measurement can be intrusive, expensive and bulky.…”

Section: Related Workmentioning

confidence: 99%

“…In order to enable efficient control we need a better understanding of the relationships between environments and perceived comfort levels. Prior work established that Equivalent Temperature (ET) can be an accurate predictor for comfort (Mayer and Schwab, 1999), (Curran et al, 2010), (Mola et al, 2004). Dry heat loss transducers allow in-field calculation of ET (Madsen et al, 1986), however they are too large and costly to be used in a production car.…”

Section: Introductionmentioning

confidence: 99%

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Comfort in Cars - Estimating Equivalent Temperature for Comfort Driven Heating, Ventilation and Air Conditioning (HVAC) Control

Hintea¹,

Brusey²,

Gaura³

et al. 2013

Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics

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Equivalent Temperature is generally considered an accurate predictor for thermal comfort in car cabins. However, direct measurement of this parameter is impractical in fielded applications. The paper presents an empirical, multiple linear regression based approach for estimating body segment equivalent temperatures for car cabin occupants from different sensors within the car. Body part equivalent temperature at eight segments and cabin sensor data (air temperature, surface temperature, mean radiant temperature, humidity and solar load) was gathered in a variety of environmental and cabin conditions. 38 experimental hours of trials in a controlled environment and 26 experimental hours of realistic driving trials were used for training and evaluating the estimator's performance. The estimation errors were on average between 0.5°C and 1.9°C for different body parts for trials within a controlled environment, while for trials in realistic driving scenarios they ranged between 1°C and 2°C. This demonstrates that passenger body part equivalent temperature can be estimated using a multiple linear regression from environmental sensors and leads the way to comfort driven Heating, Ventilation and Air Conditioning control.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comfort in Cars - Estimating Equivalent Temperature for Comfort Driven Heating, Ventilation and Air Conditioning (HVAC) Control

Hintea¹,

Brusey²,

Gaura³

et al. 2013

Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics

View full text Add to dashboard Cite

show abstract

“…An approach used quite commonly in industry for passenger compartment transient simulations is to utilize MuSES to perform the transient simulation by extrapolating from a steady-state CFD solution (Curran et al 2010). This is typically done by importing convection coefficients and fluid film temperatures from a CFD model in a manually coupled manner.…”

Section: Cfd Coupling Literature Reviewmentioning

confidence: 99%

“…The state-of-the-art technique to solve transient cool-down simulations of the crew area is subvoluming and was first published by (Curran et al 2010). Subvoluming surpasses the aforementioned lumped technique by simplifying steady-state CFD solutions into multiple lumped control volumes that communicate by advection.…”

Section: Subvolumingmentioning

confidence: 99%

“…The fluid transport between subvolumes (nodes) is calculated by summing the volume flux across dividing planes that form the new lumped volumes. The method described by (Curran et al 2010) then uses commercial MuSES software to actually solve the subvolume network, solar loading, radiation, and surface temperatures. The authors then assume all convection from the walls to the subvolumes is 15 w/m2-k.…”

Section: Subvolumingmentioning

confidence: 99%

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