scholarly journals Electric Bus Indoor Heat Balance in Cold Weather

2021 ◽  
Vol 11 (24) ◽  
pp. 11761
Author(s):  
Gabriel Chiriac ◽  
Dumitru Dorin Lucache ◽  
Costică Nițucă ◽  
Alin Dragomir ◽  
Seeram Ramakrishna

The use of electric buses is increasing all over the world; this is due to the aim of limiting pollution in heavily urbanized areas. Using electric buses is one element of the desire to drop local pollution to zero emissions. The necessary electricity can be generated through centralized production, and in the case of electric buses, the pollution level is directly proportional to the amount of electricity produced. Their limited onboard power needs optimization, both in terms of traction and in auxiliary energy consumption. Heating in electric buses consumes the most energy from the auxiliaries, which can reduce the range of the vehicle up to a half, or more in the coldest days of the winter months. In this context, a precise estimation of heat loss and of the energy necessary for heating electric buses is crucial. Using the heat transfer theory, the heat balance method, and the U-value estimation, this article estimates the heat loss for a typical 12 m electric bus for a harsh winter day. Thermal simulations were made in order to estimate the heat flux through the structure of the bus (windows, walls, roof, and floor). Heat loss components were calculated in order to determine the most affected zones of the bus. The calculated data for the energy necessary to heat the bus were compared with the heating system data from an electric bus. By optimizing the necessary auxiliary energy consumption, the emissions at the source of electricity production will be significantly reduced.

2009 ◽  
Vol 50 ◽  
pp. 316-321
Author(s):  
Antanas Mikuckas ◽  
Irena Mikuckienė ◽  
Egidijus Kazanavičius ◽  
Jonas Čeponis

Labai svarbu, kad šildymo sistema ne tik garantuotų komfortą, bet ir būtų ekonomiška. Šildymo sistemos ekonomiškumas priklauso ne tik nuo jos valdymo algoritmų, bet ir nuo radiatorių galingumo paskirstymo patalpose. Pasiūlytas pastato šiluminio balanso modelis, realizuotas naudojant MATLAB įrankį „Simulink“, leidžia analizuoti procesus šildymo sistemoje ir optimaliai paskirstyti šildymo elementų galingumą atskirose patalpose. Pateikiami modeliavimo rezultatai ir išvados.Smart House Heat Balance Modeling Using MATLABAntanas Mikuckas, Irena Mikuckienė, Egidijus Kazanavičius, Jonas Čeponis SummaryThe purpose of heating system is to create the best environment possible and to minimize energy consumption. Energy consumption in heating system depends not only on control algorithms of heating system, but also on power of heating units’ distribution. Heat balance model was developed using MATLAB. This model allows fi nding out optimal distribution of heating elements power. The results for residential house are shown. The heat consumption for a specifi ed time period was calculated.ight: 18px;"> 


2011 ◽  
Vol 110-116 ◽  
pp. 4636-4642 ◽  
Author(s):  
Vahid Golkarfard ◽  
Pouyan Talebizadeh ◽  
Mazyar Salmanzadeh

Buildings are one of the most important energy consumers in the world. High temperature gradients in heating systems can cause the increase of heat loss of the envelopes during the cold season and consequently increase the energy consumption. Floor heating systems has shown that they can generate lower temperature gradients in compare with other convective heating systems. In present study, the CFD simulation is done for a 3-D room and the required energy to achieve the thermal comfort in a room is calculated. The height of the room is changed and the energy loss of the room is calculated for both systems. Results showed that as the height doubles, the wall heat loss for radiator system almost doubles but for the floor heating system it was about 60 percent. This impressive result can recommend the floor heating systems for working areas with tall ceilings.


2019 ◽  
Vol 50 (7) ◽  
pp. 659-670 ◽  
Author(s):  
Jieyuan Yang ◽  
Jinping Li ◽  
Rong Feng

2020 ◽  
Vol 1565 ◽  
pp. 012035
Author(s):  
T I Korotkova ◽  
S A Kolesnik ◽  
B A Garibyan ◽  
S Yu Luneva ◽  
Ya V Kuzmina

2021 ◽  
Vol 11 (6) ◽  
pp. 2772
Author(s):  
Bin Li ◽  
Zhiheng Zeng ◽  
Xuefeng Zhang ◽  
Ye Zhang

To realize energy-saving and efficient industrial grain drying, the present work studied the variable-temperature drying process of corn drying in a novel industrial corn-drying system with a heat recycling and self-adaptive control function. The drying kinetics, thermal performance, heat-loss characteristics and the heat-recycling performance of the drying system under different allocations between flue gas and hot air were investigated, and the optimized drying process was proposed and compared with two constant drying processes. The results showed that the optimized drying process exhibited better drying kinetic and thermal performance than the two constant drying processes. More specifically, the total heat loss, total energy consumption and specific energy consumption of the optimized drying process were ascertained to be 36,132.85 MJ, 48,803.99 MJ and 7290.27 kJ/kg, respectively, which were lower than those of the other two processes. On the other hand, the thermal efficiency of the drying chamber for the optimized drying process was ascertained to be varied within the range of 6.81–41.71%. Overall, the validation results showed that the optimized drying process can significantly improve the drying performance of the drying system.


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 997
Author(s):  
Davide Coraci ◽  
Silvio Brandi ◽  
Marco Savino Piscitelli ◽  
Alfonso Capozzoli

Recently, a growing interest has been observed in HVAC control systems based on Artificial Intelligence, to improve comfort conditions while avoiding unnecessary energy consumption. In this work, a model-free algorithm belonging to the Deep Reinforcement Learning (DRL) class, Soft Actor-Critic, was implemented to control the supply water temperature to radiant terminal units of a heating system serving an office building. The controller was trained online, and a preliminary sensitivity analysis on hyperparameters was performed to assess their influence on the agent performance. The DRL agent with the best performance was compared to a rule-based controller assumed as a baseline during a three-month heating season. The DRL controller outperformed the baseline after two weeks of deployment, with an overall performance improvement related to control of indoor temperature conditions. Moreover, the adaptability of the DRL agent was tested for various control scenarios, simulating changes of external weather conditions, indoor temperature setpoint, building envelope features and occupancy patterns. The agent dynamically deployed, despite a slight increase in energy consumption, led to an improvement of indoor temperature control, reducing the cumulative sum of temperature violations on average for all scenarios by 75% and 48% compared to the baseline and statically deployed agent respectively.


Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3350
Author(s):  
Theofanis Benakopoulos ◽  
William Vergo ◽  
Michele Tunzi ◽  
Robbe Salenbien ◽  
Svend Svendsen

The operation of typical domestic hot water (DHW) systems with a storage tank and circulation loop, according to the regulations for hygiene and comfort, results in a significant heat demand at high operating temperatures that leads to high return temperatures to the district heating system. This article presents the potential for the low-temperature operation of new DHW solutions based on energy balance calculations and some tests in real buildings. The main results are three recommended solutions depending on combinations of the following three criteria: district heating supply temperature, relative circulation heat loss due to the use of hot water, and the existence of a low-temperature space heating system. The first solution, based on a heating power limitation in DHW tanks, with a safety functionality, may secure the required DHW temperature at all times, resulting in the limited heating power of the tank, extended reheating periods, and a DH return temperature of below 30 °C. The second solution, based on the redirection of the return flow from the DHW system to the low-temperature space heating system, can cool the return temperature to the level of the space heating system return temperature below 35 °C. The third solution, based on the use of a micro-booster heat pump system, can deliver circulation heat loss and result in a low return temperature below 35 °C. These solutions can help in the transition to low-temperature district heating.


Energy ◽  
2021 ◽  
pp. 122555
Author(s):  
Wei Liao ◽  
Yimo Luo ◽  
Jinqing Peng ◽  
Dengjia Wang ◽  
Chenzhang Yuan ◽  
...  

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