Development of a CFD model for simulating vehicle cabin indoor air quality

Chang, Tong‐Bou; Sheu, Jer‐Jia; Huang, Jhong-Wei; Lin, Yu‐Sheng; Chang, Che-Cheng

doi:10.1016/j.trd.2018.03.018

Cited by 56 publications

(20 citation statements)

References 14 publications

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“…The thermal analysis of a cabin space can be used for various reasons. Chang et al (2018) present a thermal analysis to determine the air quality of a cabin space and the level of exposure a driver has to CO 2 as temperatures in the cabin increase. The aforementioned paper presents various ventilation solutions to reduce potential safety risks to road users.…”

Section: Introductionmentioning

confidence: 99%

Energy consumption and modelling of the climate control system in the electric vehicle

Doyle

Muneer

2018

Energy Exploration & Exploitation

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With the introduction of electric vehicles in the automobile market, limited information is available on how the battery's energy consumption is distributed. This paper focuses on the energy consumption of the vehicle when the heating and cooling system is in operation. On average, 18 and 14% for the battery's energy capacity is allocated to heating and cooling requirements, respectively. The conventional internal combustion engine vehicle uses waste heat from its engine to provide for passenger thermal requirements at no cost to the vehicle's propulsion energy demands. However, the electric vehicle cannot avail of this luxury to recycle waste heat. In order to reduce the energy consumed by the climate control system, an analysis of the temperature profile of a vehicle's cabin space under various weather conditions is required. The present study presents a temperature predicting algorithm to predict temperature under various weather conditions. Previous studies have limited consideration to the fluctuation of solar radiation space heating to a vehicle's cabin space. This model predicts solar space heating with a mean bias error and root mean square error of 0.26 and 0.57 C, respectively. This temperature predicting model can potentially be developed with further research to predict the energy required by the vehicle's primary lithium-ion battery to heat and cool the vehicle's cabin space. Thus, this model may be used in a route planning application to reduce range anxiety when drivers undertake a journey under various ambient weather conditions while optimising the energy consumption of the electric vehicle.

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Section: Introductionmentioning

confidence: 99%

Energy consumption and modelling of the climate control system in the electric vehicle

Doyle

Muneer

2018

Energy Exploration & Exploitation

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“…A previous computational fluid dynamics (CFD) study [ 30 ] has shown that, in theory, CO 2 concentration gradients [ppm] within the occupied vehicle do not vary by greater than an order of magnitude, in most cases and except at geometric boundary conditions. In our experimental conditions, the effects of mixing and the presence of concentration gradients were examined with the vehicle at rest, showing little variability.…”

Section: Methodsmentioning

confidence: 99%

An Unobstructive Sensing Method for Indoor Air Quality Optimization and Metabolic Assessment within Vehicles

Deng

Sprowls

Mora

et al. 2020

Sensors

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This work investigates the use of an intelligent and unobstructive sensing technique for maintaining vehicle cabin’s indoor air quality while simultaneously assessing the driver metabolic rate. CO2 accumulation patterns are of great interest because CO2 can have negative cognitive effects at higher concentrations and also since CO2 accumulation rate can potentially be used to determine a person’s metabolic rate. The management of the vehicle’s ventilation system was controlled by periodically alternating the air recirculation mode within the cabin, which was actuated based on the CO2 levels inside the vehicle’s cabin. The CO2 accumulation periods were used to assess the driver’s metabolic rate, using a model that considered the vehicle’s air exchange rate. In the process of the method optimization, it was found that the vehicle’s air exchange rate (λ [h−1]) depends on the vehicle speeds, following the relationship: λ = 0.060 × (speed) − 0.88 when driving faster than 17 MPH. An accuracy level of 95% was found between the new method to assess the driver’s metabolic rate (1620 ± 140 kcal/day) and the reference method of indirect calorimetry (1550 ± 150 kcal/day) for a total of N = 16 metabolic assessments at various vehicle speeds. The new sensing method represents a novel approach for unobstructive assessment of driver metabolic rate while maintaining indoor air quality within the vehicle cabin.

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“…For example, Liu et al simulated the aerosol transmission using nitrous oxide (N 2 O) as a trace gas, and Tsoukias et al established a human exhalation profile using N 2 O to represent the tiny droplet nuclei [27,28]. The volume fraction of (N 2 O) in the exhaled air is about 4 %, which is about the same volume fraction of CO 2 [27,29,30]. Therefore, in this study, N 2 O is used as the tracer gas to simulate the virus's distribution after being exhaled by the virus carrier in the A320 aircraft cabin model.…”

Section: Sars-cov-2 Mass Fraction Numerical Simulationmentioning

confidence: 99%

Numerical Simulation of the Novel Coronavirus Spread in Commercial Aircraft Cabin

Zhang¹,

Yu²,

Zhang³

et al. 2021

Processes

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Passengers carrying the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a commercial aircraft cabin may infect other passengers and the cabin crew. In this study, a cabin model of the seven-row Airbus A320 aircraft is constructed and meshed for simulating the SARS-CoV-2 spread in the cabin with a virus carrier using the Computational Fluid Dynamics (CFD) modeling tool. The passengers’ infection risk is also quantified with the susceptible exposure index (SEI) method. The results show that the virus spreads to the ceiling of the cabin within 50 s of the virus carrier’s normal breathing. Coughing makes the virus spread to the front three rows with a higher mass fraction. While the high mass fraction areas always stay on the same side of the aisle as the virus carrier, the adjacent passengers and the passengers in the back two rows are affected more than the others when the virus carrier breathes normally. Spread patterns under the carrier’s two breath conditions, normal breath and cough, were numerically simulated.

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Development of a CFD model for simulating vehicle cabin indoor air quality

Cited by 56 publications

References 14 publications

Energy consumption and modelling of the climate control system in the electric vehicle

Energy consumption and modelling of the climate control system in the electric vehicle

An Unobstructive Sensing Method for Indoor Air Quality Optimization and Metabolic Assessment within Vehicles

Numerical Simulation of the Novel Coronavirus Spread in Commercial Aircraft Cabin

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