Search Results (23)

This paper introduces a methodology aimed at bridging the gap between building energy simulation and urban climate modeling. A coupling method was developed through the Building Control Virtual Test Bed (BCVTB) and applied to a case study in Taipei City, Taiwan, to address the microclimate factors of street trees crucial to cooling energy consumption. The use of the Urban Weather Generator for weather file modification revealed a 0.63 °C average air temperature disparity. The coupling method emphasized the importance of accurate wind speed and convective heat transfer coefficients (CHTCs) on building surfaces in determining cooling energy. The results indicated that elevated CHTC values amplify heat exchange, with higher wind velocities playing a crucial role in heat dissipation. The presence of street trees was found to significantly reduce heat flux penetration, leading to a reduction in building surface temperatures by as much as 9.5% during hot months. The cooling energy was lowered by 16.7% in the BCVTB simulations that included trees compared to those without trees. The EnergyPlus-only simulations underestimated the cooling energy needs by approximately 9.3% during summer months. This research offers valuable insights into the complex interactions between buildings and their environments. The results highlight the importance of trees and shading in mitigating the heat island effect and improving energy-efficient urban planning. Full article

In some scenarios, electric heavy-duty trucks with battery swapping mode (ETBSm) are more cost-effective than battery charging mode. The viability of battery swapping stations is contingent upon the operational requirements and range capabilities of the ETBSm. Low temperatures have the effect of reducing the range of the ETBSm, thereby creating difficulties for battery swapping. This article proposes the use of motor waste heat recovery (MWHR) to heat batteries, which would improve range. A number of subsystem models have been established, including the ETBSm, battery, motor, and thermal management system (TMS). The calibration of battery temperature and motor efficiency is achieved with a model error of less than 5%. Comparison of performance, such as temperature, energy consumption, and range, when using only positive temperature coefficient (PTC) heating and when using both PTC heating and motor waste heat. The results indicate a 15% increase in the rate of rise in battery temperature and a 10.64 kW·h reduction in energy consumption under Chinese heavy-duty vehicle commercial vehicle test cycle (CHTC) conditions. Then, the motor waste heat percentage, energy consumption, and range are analyzed at different ambient temperatures. At an ambient temperature of −20 °C, −10 °C, and 0 °C, the percentage of the motor waste heat is 32.1%, 35%, and 40.5%; when 75% of the state of charge (SOC) is consumed, the range is improved by 6.55%, 4.37%, and 4.49%. Additionally, the effect of the PTC heater on temperature characteristics and power consumption is investigated by changing the target temperature of the coolant at the battery inlet. In accordance with the stipulated conditions of an ambient temperature of −20 °C and a target coolant temperature of 40 °C at the battery inlet, the simulation results indicated a battery temperature rise rate of 0.85 °C/min, accompanied by a PTC power consumption of 15.6 kW·h. This study demonstrates that as the ambient temperature increases, the utilization of motor waste heat becomes more effective in reducing PTC heating power consumption. At the lowest ambient temperature tested, the greatest improvement in driving range is observed. It is important to note that while an increase in the target heating temperature of the PTC helps to raise the battery temperature more rapidly, this is accompanied by a higher energy consumption. This article provides a reference for the ETBSm with MWHR. Full article

Multi-axle distributed electric drive heavy-duty vehicles have the characteristics of high transmission efficiency, strong maneuverability, and good passability, making them widely used in large cargo transportation. However, the current driving torque control strategies of multi-axle distributed electric drive heavy-duty vehicles lack comprehensive consideration of their longitudinal and lateral dynamic characteristics, making it difficult to comprehensively optimize multiple performances such as power economy, comfort, and stability. In order to solve the above problems, This work focuses on a five-axle distributed electric drive heavy-duty vehicle. Firstly, given the differences in dynamics between two-axle vehicles and multi-axle vehicles, the dynamic model of the multi-axle distributed electric drive heavy-duty vehicle and its critical components is constructed. Then, by analyzing the characteristics of power economy, comfort, and stability of the multi-axle distributed electric drive heavy-duty vehicle, an optimal driving torque control strategy based on multiple performance coordination is proposed. Finally, on the hardware-in-the-loop (HiL) platform, the performance of the optimal driving torque control strategy proposed in this paper is verified by using the China Heavy-Duty Commercial Vehicle Test Cycle for Truck (CHTC-HT) and a straight-line acceleration driving condition on a split friction road. The simulation test results show that, compared with the traditional torque average distribution strategy, the proposed optimal driving torque control strategy can reduce the energy consumption rate by 3.45% in CHTC-HT. The strategy is attributed to the driving torque distribution based on the vehicle’s optimal instantaneous energy consumption, and vehicle comfort is also ensured by the driving mode switching frequency suppression. Subsequently, the vehicle’s stability on the split friction road is effectively improved by the torque coordination compensation strategy. This control strategy significantly improves the comprehensive performance of multi-axle distributed electric drive heavy-duty vehicles. Full article

Film cooling needs to be applied to serpentine nozzles due to an increase in thermal load. Adverse pressure gradients (APGs) near the upper wall of such nozzles hinder the forward flow of the coolant, and they may even induce a recirculation zone that complicates the cooling of the film in serpentine nozzles under different APGs. In this study, the film cooling characteristics of a serpentine nozzle under various APGs are investigated through numerical simulations. The studied pressure gradients include strong, moderate, and weak APGs. The results show that the APG weakened the adhesion of the coolant to the surface, thereby reducing the film cooling effectiveness (FCE) and the convective heat transfer coefficient (CHTC). The stronger the APG, the greater its obstructive effect. However, the recirculation zone induced by the strong APG was composed of the coolant, and it adhered tightly to the wall, thereby significantly strengthening the FCE and CHTC. The CHTC under the moderate APG significantly increased due to the convergence of two jets ejected from different holes. For the four blowing ratios, the area-averaged FCE under the strong APG was 29.8% and 24.5% higher than that under the moderate and weak APGs, while the area-averaged ratios of the CHTC under the moderate APG were 1.6% and 16.7% higher than those under the strong and weak APGs. Therefore, more holes should be arranged on the film in the zones of moderate and weak APGs. Full article

During the process of forming carbon fiber reinforced plastics (CFRP) in an autoclave, deeply understanding the global sensitivity of factors influencing mold surface temperature is of paramount importance for optimizing large frame-type mold thermally and enhancing curing quality. In this study, the convective heat transfer coefficient (CHTC), the thickness of composite laminates (TCL), the thickness of mold facesheet (TMF), the mold material type (MMT), and the thickness of the auxiliary materials layer (TAL) have been quantitatively assessed for the effects on the mold surface temperature. This assessment was conducted by building the thermal–chemical curing model of composite laminates and utilizing the Sobol global sensitivity analysis (GSA) method. Additionally, the interactions among these factors were investigated to gain a comprehensive understanding of their combined effects. The results show that the sensitivity order of these factors is as follows: CHTC > MMT > TMF > TCL > TAL. Moreover, CHTC, MMT, and TMF are the main factors influencing mold surface temperature, as the sum of their first-order sensitivity indices accounts for over 97.3%. The influence of a single factor is more significant than that of the interaction between factors since the sum of the first-order sensitivity indices of the factors is more than 78.1%. This study will support the development of science-based guidelines for the thermal design of molds and associated heating equipment design. Full article

Electric wheel-drive multi-axle heavy-duty vehicles have the characteristics of strong maneuverability and good passability, thereby they are widely used in heavy equipment transportation. However, current research on the composite braking of multi-axle heavy-duty vehicles is rare, which is not conducive to improving braking performance and braking energy utilization efficiency. This work proposes a multi-mode composite braking control strategy for the five-axle distributed electric wheel-drive heavy-duty vehicle. Firstly, given the differences in braking dynamics between two-axle vehicles and multi-axle vehicles, the brake dynamics characteristics of multi-axle vehicles are analyzed, and the vehicle dynamics model of multi-axle vehicles is constructed. Next, a multi-mode composite braking control strategy including a fully electric braking state and hybrid electro–hydraulic braking state is proposed in order to improve the braking energy recovery and braking stability. Finally, a hardware-in-the-loop simulation system is established, and the single-braking conditions and China heavy-duty commercial vehicle test cycle-heavy truck (abbreviated as CHTC-HT) are conducted to verify the performance of the braking control strategy. The results indicate that the recaptured braking energy and braking stability are significantly increased by applying the control strategy proposed in this work. Full article

Road slope is an essential parameter in the study of vehicle driving processes. In future traffic development, constructing road segments with slopes is indispensable. Furthermore, road slope is a fundamental parameter for realizing energy recovery during braking. Hence, research on road slope estimation is extremely crucial. This article proposes a combination of adaptive filtering and strong tracking filter factors for road slope estimation, followed by establishing case settings for verification. It was found that the proposed slope estimation algorithm has a high degree of accuracy in estimating the slope angle, with a mean absolute error (MAE) and a root mean square error (RMSE) of 0.0254 and 0.0359, respectively, at fixed slopes, and a MAE and a RMSE of 0.2799 and 0.3710, respectively, at varying slopes. By combining the slope angle with a braking force distribution optimization algorithm, an optimized braking distribution coefficient is obtained. In the Cruise2019 software, slope angles of 0° and 5° are set and combined with the braking force distribution strategy built in Matlab2021/Simulink for verification under China Heavy-duty Commercial Vehicle Test Cycle (CHTC-HT) and Worldwide Transient Vehicle Cycle (C-WTVC) conditions. The recovered energy increased by 7.24% and 4.99%, respectively, under CHTC-HT conditions, and by 6.42% and 1.73%, respectively, under C-WTVC. Full article

Controlling NOx and CO₂ emissions from heavy-duty diesel vehicles (HDDVs) is receiving increasing attention. Accurate measurement of HDDV NOx and CO₂ emissions is the prerequisite for HDDV emission control. Vehicle emission regulations srecommend the measurement of NOx and CO₂ emissions from vehicles using an emission analyzer, which is expensive and unsuitable to measure a large number of vehicles in a short time. The on-board diagnostics (OBD) data stream of HDDVs provides great convenience for calculating vehicle NOx and CO₂ emissions by providing the engine fuel flow rate, NOx sensor output, and air mass flow. The calculated vehicle NOx and CO₂ emissions based on the OBD data were validated by testing a heavy-duty truck’s emissions on the chassis dynamometer over the CHTC-HT driving cycle, showing that the calculated NOx and CO₂ emissions based on the OBD data are consistent with the measured results by the emission analyzer. The calculated vehicle fuel consumptions based on the OBD data were close to the calculated results based on the carbon balance method and the measured results by the fuel flowmeter. The experimental results show that accessing vehicle NOx and CO₂ emissions based on the OBD data is a convenient and applicable method. Full article

Applying rock-filled gabion to buildings in cold regions with mountainous climates has multiple potentials, such as utilizing rock resources, improving building sustainability and saving building energy. Therefore, it is necessary to analyze the thermal performance of gabion buildings. Based on the CFD method, this paper establishes a numerical model of buildings with gabion enclosure structures, analyzes the influence of the gabion structure on the external convective heat transfer coefficient (CHTC), wind pressure, air infiltration, room temperature and building load, and further uses the building energy consumption simulation method to analyze the heat load of gabion buildings. The results showed that the adverse impact of climate on the building thermal performance is significantly diminished by the gabion. Under different weather conditions, the CHTC, the maximum wind pressure difference on the exterior surface, and the air infiltration rate are reduced by different rates. Further, the room base temperature increases throughout the heating season, and the maximum heat load and the cumulative heat load of the building are, respectively, reduced by 10.6% and 24.8%. This work revealed that the gabion is an eco-friendly and adaptive measure to improve thermal performance and indoor thermal comfort. Full article

The hybrid electric dump truck is equipped with multiple power sources, and each powertrain component is controlled by an energy management strategy (EMS) to split the demanded power. This study proposes an EMS based on deep reinforcement learning (DRL) algorithm to extend the battery life and reduced total usage cost for the vehicle, namely the twin delayed deep deterministic policy gradient (TD3) based EMS. Firstly, the vehicle model is constructed and the optimization objective function, including battery aging cost and fuel consumption cost, is designed. Secondly, the TD3-based EMS is used for continuous action control of ICE power based on vehicle state, and the action mask is applied to filter out invalid actions. Thirdly, the simulations of the EMSs are trained under the CHTC-D driving cycle and C-WTVC driving cycle. The results show that the action mask improves the convergence efficiency of the strategies, and the proposed TD3-based EMS outperforms the deep deterministic policy gradient (DDPG) based EMS. Meanwhile, the battery life is extended by 36.17% under CHTC-D and 35.49% under C-WTVC, and the total usage cost is reduced by 4.30% and 2.49% when the EMS considers battery aging. In summary, the proposed TD3-based EMS can extend the battery life and reduce usage cost, and provides a method to solve the optimization problem for the EMS of hybrid power systems. Full article

A radiator is used to remove a portion of the heat generated by a vehicle engine. It is challenging to efficiently maintain the heat transfer in an automotive cooling system even though both internal and external systems need enough time to keep pace with catching up with evolving engine technology advancements. The effectiveness of a unique hybrid’s heat transfer nanofluid was investigated in this study. The hybrid nanofluid was mainly composed of graphene nanoplatelets (GnP), and cellulose nanocrystals (CNC) nanoparticles suspended in a 40:60 ratio of distilled water and ethylene glycol. A counterflow radiator equipped with a test rig setup was used to evaluate the hybrid nano fluid’s thermal performance. According to the findings, the proposed GNP/CNC hybrid nanofluid performs better in relation to improving the efficiency of heat transfer of a vehicle radiator. The suggested hybrid nanofluid enhanced convective heat transfer coefficient by 51.91%, overall heat transfer coefficient by 46.72%, and pressure drop by 34.06% with respect to distilled water base fluid. Additionally, the radiator could reach a better CHTC with 0.01% hybrid nanofluid in the optimized radiator tube by the size reduction assessment using computational fluid analysis. In addition to downsizing the radiator tube and increasing cooling capacity over typical coolants, the radiator takes up less space and helps to lower the weight of a vehicle engine. As a result, the suggested unique hybrid graphene nanoplatelets/cellulose nanocrystal-based nanofluids perform better in heat transfer enhancement in automobiles. Full article

Aiming at the impact of heat generation and temperature rise on the driving performance of a permanent magnet (PM) motor, taking the PM in-wheel motor (IWM) for electric vehicles as an object, research is conducted into the temperature distribution of the electromagnetic–thermal effect and cooling structure optimization. Firstly, the electromagnetic–thermal coupling model considering electromagnetic harmonics is established using the subdomain model and Bertotti’s iron loss separation theory. Combined with the finite element (FE) simulation model established by Ansoft Maxwell software platform, the winding copper loss, stator core loss and PM eddy current loss under the action of complex magnetic flux are analyzed, and the transient temperature distribution of each component is obtained through coupling. Secondarily, the influence of the waterway structure parameters on the heat dissipation effect of the PM-IWM is analyzed by the thermal-fluid coupled relationship. On the basis, the optimization design of waterway structure parameters is carried out to improve the heat dissipation effect of the cooling system based on the proposed chaotic mapping ant colony algorithm with metropolis criterion. The comparison before and after optimization shows that the temperature of key components is significantly improved, the average convection heat transfer coefficient (CHTC) is increased by 23.57%, the peak temperature of stator is reduced from 95.47 °C to 82.73 °C, and the peak temperature of PM is decreased by 14.26%, thus the demagnetization risk in the PM is improved comprehensively. The research results can provide some theoretical and technical support for the structural optimization of water-cooled dissipation in the PM motor. Full article

As one of the most popular and important forms of massive transit, the public bus contributes to a healthier environment compared to private vehicles. Through the electrification of the public bus, energy consumption, carbon emission, and air pollution can be significantly reduced. However, the limited driving range and high battery replacement cost put significant barriers to its large-scale commercialization. Thanks to the development of wireless charging technology and opportunity charging strategy, the driving range can be improved. However, the battery has to suffer additional impulse current generated by opportunity wireless charging. In this paper, a hybrid energy storage system (HESS) that combines battery and supercapacitor and related energy control strategy is proposed to smoothen the impulse current and extend the battery lifespan. A comprehensive investigation of the combined impacts of the opportunity charging and HESS is carried out in terms of driving range extension and battery lifespan improvement. The detailed HESS model and powertrain model are built. A global optimizing method, dynamic programming, is adopted as the energy management strategy under the Chinese heavy-duty commercial vehicle test cycle-bus (CHTC-B). A battery degradation model is employed to evaluate its health with 60 kW wireless charging. The results demonstrate that the proposed energy control strategy for HESS could improve battery health and extend bus driving range concurrently via opportunity charging. Full article

With the rapid development of machine learning, deep reinforcement learning (DRL) algorithms have recently been widely used for energy management in hybrid electric urban buses (HEUBs). However, the current DRL-based strategies suffer from insufficient constraint capability, slow learning speed, and unstable convergence. In this study, a state-of-the-art continuous control DRL algorithm, softmax deep double deterministic policy gradients (SD3), is used to develop the energy management system of a power-split HEUB. In particular, an action masking (AM) technique that does not alter the SD3′s underlying principles is proposed to prevent the SD3-based strategy from outputting invalid actions that violate the system’s physical constraints. Additionally, the transfer learning (TL) method of the SD3-based strategy is explored to avoid repetitive training of neural networks in different driving cycles. The results demonstrate that the learning performance and learning stability of SD3 are unaffected by AM and that SD3 with AM achieves control performance that is highly comparable to dynamic planning for both the CHTC-B and WVUCITY driving cycles. Aside from that, TL contributes to the rapid development of SD3. TL can speed up SD3’s convergence by at least 67.61% without significantly affecting fuel economy. Full article

This paper investigates the combined effect of the kiln or brick surface roughness and the brick lattice setting density on the fluid flow and heat transfer characteristics in tunnel kilns. The flow uniformity, pressure drop, convective heat transfer coefficient (CHTC), and pumping power are studied. A high-density setting (HDS), which comprises 768 bricks, and a low-density setting (LDS), which comprises 512 bricks, are tested for kiln boundaries and brick surface roughness levels of 0, 1, 2, 3, and 4 mm. The investigation is conducted using a 3D-CFD model with the k-ω turbulence model. The surface roughness changes from 0 to 4 mm for either kiln walls or bricks while fixing the other. The results show that increasing the tunnel kiln surface roughness from 0 to 4 mm increases the pressure drop of both the HDS and LDS by about 13.5%. It also increases the established CHTC value of the LDS more than the HDS by about 23% for all tested roughness levels. Changing the brick surface roughness from 0 to 4 mm increases the pressure drop and CHTC value for the LDS more than for the HDS by about 10% and 12%, respectively. Additionally, the total heat transfer rate-to-pumping power ratio for the LDS is larger than for the HDS by 17.4% for smooth bricks and 23.1% for the brick roughness of 2 mm, i.e., the brick roughness provides a greater advantage to the LDS. The results confirm that the LDS for rough and smooth bricks loaded in tunnel kilns attains a better brick quality, a higher heat transfer rate, and a lower pumping power than the HDS. Full article