scholarly journals Air Quality and Comfort Characterisation within an Electric Vehicle Cabin in Heating and Cooling Operations

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 543
Author(s):  
Luigi Russi ◽  
Paolo Guidorzi ◽  
Beatrice Pulvirenti ◽  
Davide Aguiari ◽  
Giovanni Pau ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Air Quality ◽  
Electric Vehicle ◽  
Low Cost ◽  
Hvac System ◽  
Vehicle Cabin ◽  
Heating And Cooling ◽  
Cost System ◽  
Pollutant Concentrations ◽  
Comfort Parameters

This work is aimed at the experimental characterisation of air quality and thermal profile within an electric vehicle cabin, measuring at the same time the HVAC system energy consumption. Pollutant concentrations in the vehicle cabin are measured by means of a low-cost system of sensors. The effects of the HVAC system configuration, such as fresh-air and recirculation mode, on cabin air quality, are discussed. It is shown that the PM concentrations observed in recirculation mode are lower than those in fresh-air mode, while VOC concentrations are generally higher in recirculation than in fresh-air mode. The energy consumption is compared in different configurations of the HVAC system. The novelty of this work is the combined measurement of important comfort parameters such as air temperature distribution and air quality within the vehicle, together with the real time energy consumption of the HVAC system. A wider concept of comfort is enabled, based on the use of low-cost sensors in the automotive field.

scholarly journals Full IoT Lora School Building Management System

2019 ◽  
Author(s):  
Bruno Mataloto ◽  
Joao C. Ferreira ◽  
Nuno Cruz
Keyword(s):  
Energy Consumption ◽  
Low Cost ◽  
Development Phase ◽  
Total Energy Consumption ◽  
Cooling Systems ◽  
Flexible Approach ◽  
Heating And Cooling ◽  
Building Management ◽  
Building Management System ◽  
Communication Board

In this research paper we describe the development phase of a low-cost LoRa IoT solution applied to a kindergarten school with three years results. A set of sensors solution was developed in a LoRa communication board, battery powered, providing a simplified setup process. These sensors were used in order to measure temperature, humidity, luminosity, air quality and presence. Also, energy monitor solutions were integrated. The acquired data is transmitted and analysed for knowledge extraction, identifying savings and other related KPIs. From data, automatic saving actions were performed towards heating and cooling systems, lighting and a set of if-then actions were developed for automatic cost-saving actions, based on infrared signals to heating/cooling systems using some procedure of external command devices. This approach avoids the usage of proprietary vendor solutions in a flexible approach that can easily be deployed to any building facility. This is an important achievement since most of the building consumption is based on heating and cooling systems. In a three years test of the solution, the total energy consumption savings surpassed 20%

Air quality and comfort characterisation within an electric vehicle cabin

2021 ◽  
Author(s):  
Luigi Russi ◽  
Paolo Guidorzi ◽  
Beatrice Pulvirenti ◽  
Giovanni Semprini ◽  
Davide Aguiari ◽  
...  
Keyword(s):  
Air Quality ◽  
Electric Vehicle ◽  
Vehicle Cabin

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

2018 ◽  
Vol 37 (1) ◽  
pp. 519-543 ◽  
Author(s):  
Aisling Doyle ◽  
Tariq Muneer
Keyword(s):  
Control System ◽  
Energy Consumption ◽  
Electric Vehicle ◽  
Waste Heat ◽  
Cooling System ◽  
Weather Conditions ◽  
Mean Bias Error ◽  
Space Heating ◽  
Climate Control ◽  
Heating And Cooling

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.

An Online Low-Cost System for Air Quality Monitoring, Prediction, and Warning

2019 ◽  
pp. 311-324
Author(s):  
Rishi Sharma ◽  
Tushar Saini ◽  
Praveen Kumar ◽  
Ankush Pathania ◽  
Khyathi Chitineni ◽  
...  
Keyword(s):  
Air Quality ◽  
Low Cost ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Cost System

scholarly journals Comparative Analysis of Energy Consumption, Indoor Thermal–Hygrometric Conditions, and Air Quality for HVAC, LDAC, and RDAC Systems Used in Operating Rooms

2020 ◽  
Vol 10 (11) ◽  
pp. 3721
Author(s):  
Tsung-Yi Chien ◽  
Ching-Chieh Liang ◽  
Feng-Jen Wu ◽  
Chi-Tsung Chen ◽  
Ting-Hsin Pan ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Air Quality ◽  
Air Conditioning ◽  
Operating Rooms ◽  
Conventional Heating ◽  
Hvac System ◽  
Total Energy Consumption ◽  
System A ◽  
Air Conditioning Systems ◽  
Daily Total

As controlling temperature and humidity is crucial for maintaining comfort and preventing microbial growth, operating rooms (ORs) are the most energy-intensive areas in hospitals. We aimed to evaluate the energy consumption of three dehumidification air conditioning systems used in ORs and their corresponding air quality for ORs at rest. This study selected three ORs using a conventional heating, ventilation, and air conditioning (HVAC) system; a liquid desiccant air conditioning (LDAC) system; and a rotary desiccant air conditioning (RDAC) system, respectively. The indoor thermal–hygrometric conditions, air quality, and energy consumption of the ORs were monitored in this study. The median levels of relative humidity (RH) were 66.7% in the OR using the conventional HVAC system, 60.8% in the OR using the LDAC system, and 60.5% in the OR using the RDAC system. The median daily total energy consumption of the RDAC system (10.1 kWh/m2) and LDAC system (11.8 kWh/m2) were 28.12% and 16.54% lower, respectively, than that of the conventional HVAC system (14.1 kWh/m2). The PM≥0.5 levels and airborne bacterial concentrations in the ORs met the ISO 14644-1 Class 7 standard and China’s GB50333-2013 standard, respectively. The RDAC system was clearly superior to the LDAC and conventional HVAC systems in terms of energy consumption.

scholarly journals 1D analysis of cool down simulation of vehicle HVAC system

2020 ◽  
pp. 99-99
Author(s):  
Gokhan Sevilgen ◽  
Halil Bayram ◽  
Muhsin Kilic
Keyword(s):  
Energy Consumption ◽  
Air Temperature ◽  
Thermal Performance ◽  
Thermal Conditions ◽  
Hvac System ◽  
Maximum Increase ◽  
Vehicle Cabin ◽  
1D Model ◽  
R 134A ◽  
Air Conditioning Systems

In this paper, a detailed combined 1D model of Heating, Ventilation and Air Conditioning systems of a vehicle were developed by using the LMS Imagine Lab Amesim software package. The numerical simulations were considered for soaking and cool down analysis under different environmental conditions. The thermal performance of different refrigerants as R-134a and R-1234yf were evaluated in terms of thermal performance and energy consumption. According to the soaking simulation results, the cabin air temperature values ranged from 49?C to 57?C in general. The maximum increase in cabin air temperature value was about 22?C obtained for 1000 15 W/m2 solar load. The total time until reaching the steady-state conditions for a target temperature value (23.5?C) was different for all simulations. The total time was calculated as 910 seconds for 1000 W/m2 solar load by using R134a refrigerant loop. The results also showed that although the thermal performance of R-134a was slightly better, R-1234yf can be used due to its environmental properties with acceptable performance. The calculated COP values during cooldown analysis were ranged from 1.71 to 4.52 in general. The minimum value was obtained for the cases which had a maximum solar load and higher cabin interior temperature values. The calculated temperature data for soaking and cool down analysis were in good agreement with the reference data presented in this study. These numerical results are very important for reducing the thermal load of the vehicle cabin considering energy consumption of the HVAC system for different thermal conditions.

scholarly journals Multisensor IoT Platform for Optimising IAQ Levels in Buildings through a Smart Ventilation System

2019 ◽  
Vol 11 (20) ◽  
pp. 5777 ◽  
Author(s):  
Giacomo Chiesa ◽  
Silvia Cesari ◽  
Miguel Garcia ◽  
Mohammad Issa ◽  
Shuyang Li
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Real Time ◽  
Indoor Air ◽  
Low Cost ◽  
Ventilation System ◽  
Mobile App ◽  
Sensor Data ◽  
Pollutant Concentrations ◽  
Indoor And Outdoor

Indoor Air Quality (IAQ) issues have a direct impact on the health and comfort of building occupants. In this paper, an experimental low-cost system has been developed to address IAQ issues by using a distributed internet of things platform to control and monitor the indoor environment in building spaces while adopting a data-driven approach. The system is based on several real-time sensor data to model the indoor air quality and accurately control the ventilation system through algorithms to maintain a comfortable level of IAQ by balancing indoor and outdoor pollutant concentrations using the Indoor Air Quality Index approach. This paper describes hardware and software details of the system as well as the algorithms, models, and control strategies of the proposed solution which can be integrated in detached ventilation systems. Furthermore, a mobile app has been developed to inform, in real time, different-expertise-user profiles showing indoor and outdoor IAQ conditions. The system is implemented in a small prototype box and early-validated with different test cases considering various pollutant concentrations, reaching a Technology Readiness Level (TRL) of 3–4.

Low-cost sensors and indoor air quality: A test study in three residential homes in Berlin, Germany/Kostengünstige Sensoren und Innenraumluftqualität: Eine Testuntersuchung in drei Privathaushalten in Berlin

Gefahrstoffe ◽  
2019 ◽  
Vol 79 (03) ◽  
pp. 87-92 ◽  
Author(s):  
A. Krause ◽  
J. Zhao ◽  
W. Birmili
Keyword(s):  
Air Quality ◽  
Low Cost ◽  
Data Sets ◽  
Indoor Environments ◽  
Long Term Stability ◽  
Test Study ◽  
Pollutant Concentrations ◽  
Inorganic Pollutant ◽  
Commercial Instrument ◽  
Private Homes

There are surprisingly few representative data sets available on particulate matter (PM) and inorganic pollutant gas concentrations for indoor environments. Meanwhile, there is an increasing trend to use low-cost sensors in air quality studies, which may introduce new kinds of investigations. It is, however, unclear whether low-cost instruments can provide enough precision and long-term stability to quantify the comparatively low pollutant concentrations encountered in office and residential indoor environments. This work reports test measurements of PM2,5, CO, NO, NO2 und O3 with a commercial instrument based on low cost sensors in three private homes in Berlin, Germany.

Sign in / Sign up

Export Citation Format

Share Document