Optimization of IAQ characteristics of an air-conditioned car using GRA and RSM

Thirumal, P.; Amirthagadeswaran, K. S.; Jayabal, S.

doi:10.1007/s12206-014-0337-6

Cited by 10 publications

(4 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The last three terms Q Heaters , Q humidification , Q ventilation (W m −2 ) correspond, respectively, to the heat gain from the heating system, the cooling effect from the humidifying system and the heat loss due to ventilation [20,21].…”

Section: Greenhouse Modelmentioning

confidence: 99%

Fuzzy Decoupling Control of Greenhouse Climate

et al. 2015

View full text Add to dashboard Cite

Greenhouses are complex and nonlinear systems in which the inside temperature and humidity are deterministic parameters for the optimal growth of the plants. Several control methods have been developed to get an optimized microclimate. Physically both parameters are strongly coupled; hence, this paper proposes a novel fuzzy controlling method considering the temperature and humidity's coupling effects; the controller is based on a validated greenhouse physical model and an evaluation of the correlation of both parameters. The results show the high performance of the decoupling method and the effectiveness of the fuzzy controller to manage the inside climate while saving energy.

show abstract

Section: Greenhouse Modelmentioning

confidence: 99%

Fuzzy Decoupling Control of Greenhouse Climate

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Furthermore, a similar indoor environment such as the vehicle cabin that has been equipped with a heater, ventilation, and air conditioning system (HVAC) can be categorized as an indoor space. HVAC systems use the recirculation mode (RC) that could mitigate the penetration of pollutants such as particulate matter and hazardous gases from the vehicle’s exhaust system [ 6 , 7 ]. Nonetheless, the human occupant inhales the oxygen then replaces it with carbon dioxide (CO 2 ) which acts as contamination known as the human bio-effluent.…”

Section: Introductionmentioning

confidence: 99%

Real-Time In-Vehicle Air Quality Monitoring System Using Machine Learning Prediction Algorithm

Kamarudin

Zakaria

Nishizaki

et al. 2021

Sensors

View full text Add to dashboard Cite

This paper presents the development of a real-time cloud-based in-vehicle air quality monitoring system that enables the prediction of the current and future cabin air quality. The designed system provides predictive analytics using machine learning algorithms that can measure the drivers’ drowsiness and fatigue based on the air quality presented in the cabin car. It consists of five sensors that measure the level of CO2, particulate matter, vehicle speed, temperature, and humidity. Data from these sensors were collected in real-time from the vehicle cabin and stored in the cloud database. A predictive model using multilayer perceptron, support vector regression, and linear regression was developed to analyze the data and predict the future condition of in-vehicle air quality. The performance of these models was evaluated using the Root Mean Square Error, Mean Squared Error, Mean Absolute Error, and coefficient of determination (R2). The results showed that the support vector regression achieved excellent performance with the highest linearity between the predicted and actual data with an R2 of 0.9981.

show abstract

“…Accordingly, Katarzyna 18 proposed a maximum cabin CO 2 concentration of 4500 ppm for small passenger vehicles and suggested the use of a full recirculation ventilation mode for CO 2 concentrations lower than this value, and a full fresh air delivery mode otherwise. Thirumal et al 19 used gray relational analysis and Response Surface Methodology techniques to develop mathematical models for optimizing the IAQ characteristics (temperature, CO 2 level and relative humidity) of an air-conditioned car cabin over a specified range of input conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Thirumal et al. 19 used gray relational analysis and Response Surface Methodology techniques to develop mathematical models for optimizing the IAQ characteristics (temperature, CO2 level and relative humidity) of an air-conditioned car cabin over a specified range of input conditions.…”

Section: Introductionmentioning

confidence: 99%

Vehicle air leakage ventilation and its effect on cabin indoor air quality

Chang

Sheu

Huang

2016

Proceedings of the Institution of Mechanical Engineers, Part E:

View full text Add to dashboard Cite

This study investigates the air leakage ventilation phenomenon in a passenger car and examines its effects on the concentration of carbon dioxide in the cabin. A theoretical general equation (Q AL ¼ f½A car ðv 2 car Þ m 1 2 þ ½A fan ðv 2 fan Þ m 2 2 g 1=2) is proposed for predicting the air leakage ventilation rate. The validity of the equation is demonstrated by means of real car on-road experiments. The results show that when the car is at rest, the effect of the fan-supplied air speed on the air leakage ventilation rate is more apparent. However, for a moving vehicle, the contribution of the fan-supplied air speed to the cabin indoor air quality reduces, while that of the car speed increases. Applying a curve-fitting technique to the experimental data, it is shown that parameters A car , m 1 , A fan and m 2 in the proposed theoretical equation have values of 1:15 Â 10 À4 , 0.725, 1:6 Â 10 À3 and 0.315, respectively, for the present experimental car (a Mitsubishi Galant). In general, the results obtained in this study suggest that a fractional fresh air ventilation mode should be employed to guarantee the ASHRAE standard for the minimum fresh air requirement of 2.5 l/s per individual at low driving speeds.

show abstract

Optimization of IAQ characteristics of an air-conditioned car using GRA and RSM

Cited by 10 publications

References 12 publications

Fuzzy Decoupling Control of Greenhouse Climate

Fuzzy Decoupling Control of Greenhouse Climate

Real-Time In-Vehicle Air Quality Monitoring System Using Machine Learning Prediction Algorithm

Vehicle air leakage ventilation and its effect on cabin indoor air quality

Contact Info

Product

Resources

About