Browse Topic: Weather and climate

Items (3,729)
This study investigates the correlation between moisture behavior and corrosion stiction mechanisms in NAO friction materials. While previous studies on corrosion stiction have primarily focused on electrochemical approaches, this study aims to elucidate the mechanism by examining moisture behavior within the friction material. Although recent research has investigated changes in pad properties in humid environments, most studies have primarily focused on variations in pad stiffness and the friction coefficient. To date, no studies have investigated the behavior of moisture within pads using Fick’s Second Law and its impact on corrosion stiction. In this study, Fick’s Second Law was applied to model moisture behavior in friction materials. The diffusion coefficient and maximum moisture content were quantified, revealing that moisture behavior in the friction material can be divided into two distinct stages: one following Fick’s Second Law and the other not. For NAO friction materials
Choi, NakcheonJu, JoungsuYoun, Deokki
Moisture is known to be a relevant factor during a friction material life, affecting tribological behaviors such as friction coefficient and torque variations. In this study we investigated the interaction between friction materials and water; employing various techniques such as contact angle measurements, water adsorption, and exposure to controlled environmental condition changes. Focusing on NAO friction material, mix modifications were studied to highlight differences and understand mechanisms, in particular, organic content and hydrophobic agents, were examined. Characterization results showed that brake pads hydrophobicity can be influenced by water interaction conditions; even low-wettability surfaces, such as those treated with hydrophobic modifiers, can still absorb water depending on internal factors (e.g., porosity) and external conditions (e.g., contact time, humidity). Additionally, we investigated the capacity of a friction material to adsorb water and desorb it back to
Iodice, ValentinaDurando, PietroBalestra, SimonePellerej, Diego
The third-generation Nissan Leaf represents the automaker's efforts to bring the world's first mass-market modern EV up to date. This meant making changes to the powertrain - better winter charging, new NACS connectors - while keeping some things the same. SAE Media spoke with Jeff Tessmer, senior manager, R&D engineer, technology planning and research at Nissan Technical Center North America, about these updates.
Blanco, Sebastian
Engineers from Australia and China have invented a sponge-like device that captures water from thin air and then releases it in a cup using the sun’s energy, even in low humidity where other technologies such as fog harvesting and radiative cooling have struggled.
This SAE Standard encompasses connectors between two cables or between a cable and an electrical component and focuses on the connectors external to the electrical component. This document provides environmental test requirements and acceptance criteria for the application of connectors for direct current electrical systems of 60 V or less in the majority of heavy-duty applications typically used in off-highway machinery. Severe applications can require higher test levels or field-testing on the intended application.
CTTC C2, Electrical Components and Systems
Hydroplaning contributes to approximately 20% of traffic accidents during adverse weather conditions, with factors such as velocity, water film thickness, tire inflation, and vehicle weight playing significant roles. This study aims to simulate the hydroplaning phenomenon using a fluid–structure interaction model based on the coupled Eulerian–Lagrangian (CEL) capabilities of ABAQUS. Results reveal that vehicle linear velocity is a key determinant of hydroplaning risk, with a positive correlation observed. The findings suggest maintaining speeds under 50 km/h to mitigate hydroplaning risk, contingent on well-maintained, properly inflated tires. Multiple linear regression analysis further demonstrates correlations among velocity, tire inflation, quarter vehicle load, and water film thickness in predicting the reaction force between the tire and roadway. The proposed scheme provides a predictive mechanism for hydroplaning risk under varying conditions, offering valuable insights into
Aboelsaoud, MostafaTaha, Ahmed AbdelsalamAbo Elazm, MohamedElgamal, Hassan Anwar
Low-cost jelly-like materials, developed by researchers at the University of Cambridge, can sense strain, temperature, and humidity. And unlike earlier self-healing robots, they can also partially repair themselves at room temperature.
Researchers have created a 98-milligram sensor system — about one tenth the weight of a jellybean or less than one-hundredth of an ounce — that can ride aboard a small drone or an insect, such as a moth, until it gets to its destination. Then, when a researcher sends a Bluetooth command, the sensor is released from its perch and can fall up to 72 feet — from about the sixth floor of a building — and land without breaking. Once on the ground, the sensor can collect data, such as temperature or humidity, for almost three years.
Improving electric vehicles’ overall thermal management strategy can directly or indirectly improve battery efficiency and vehicle range [1]. In this study, the effect of the coolant type used in BTMS (battery thermal management system) units used for heating batteries in cold weather conditions was investigated in electric buses. In this investigation, tests were performed with two types of antifreeze, which have different characteristics. The study evaluated the impact of coolant flow, BTMS circulation pump performance, and battery heating using these two types of antifreeze in the BTMS coolant line. In addition to carrying out tests, 1D computational fluid dynamics models’ simulations were carried out for both types of antifreeze, and the results were validated with experimental findings. In this study, a 12-m EV Citivolt vehicle of Anadolu Isuzu was used for tests. As a result, it was observed that differences in the properties of the antifreeze that is used in BTMS coolant line
Çetir, ÖzgürBirgül, Çağrı Emre
The windscreen is one of the key elements to enhance passenger comfort of touring motorcycle. The clarity through the windscreen should not discomfort the rider. The discomfort we discuss here mainly refers to three factors: the “distortion,” the “blur,” and the “transparency.” Introduced in this paper is the technical measures to achieve sufficient clarity by the injection molding method. Firstly, with respect to the “distortion,” we determined the main cause was local unevenness of plate thickness. As the uneven thickness were related to the accuracy of the die, we clarified the tolerable zone and carried out higher precision machining of the die to satisfy the requirements. Regarding the “blur,” we analyzed the refractive power of the windscreen and found the main cause of blur is the microscopic roughness on the surface. As the microscopic roughness were attributable to the die surface, we clarified the tolerable zone and established the polishing conditions satisfactory for the
Yamada, AtsushiEndo, Sakae
The scope of the test method is to provide stakeholders including fluid manufacturers, airport operators, brake manufacturers, aircraft constructors, aircraft operators and airworthiness authorities with a relative assessment of the effect of deicing chemicals on carbon oxidation. This simple test is only designed to assess the relative effects of runway deicing chemicals by measuring mass change of contaminated and bare carbon samples tested under the same conditions. It is not possible to set a general acceptance threshold oxidation limit based on this test method because carbon brake stack oxidation is a function of heat sink design and the operating environment.
A-5A Wheels, Brakes and Skid Controls Committee
Hurricane evacuations generate high traffic demand with increased crash risk. To mitigate such risk, transportation agencies can adopt high-resolution vehicle data to predict real-time crash risks. Previous crash risk prediction models mainly used limited infrastructure sensor data without covering many road segments. In this article, we present methods to determine potential crash risks during hurricane evacuation from an emerging alternative data source known as connected vehicle data that contain vehicle speed and acceleration information collected at a high frequency (mean = 14.32, standard deviation = 6.82 s). The dataset was extracted from a database of connected vehicle data for the evacuation period of Hurricane Ida on Interstate-10 in Louisiana. Five machine learning models were trained considering weather features and different traffic characteristics extracted from the connected vehicle data. The results indicate that the Gaussian process boosting and extreme gradient
Syed, Zaheen E MuktadiHasan, Samiul
Plug-in hybrid electric vehicles (PHEVs) conceptually aim to offer the “best of both worlds” of battery-only electric vehicles (BEVs) in terms of utilizing grid electricity to power an appreciable portion of vehicle miles travelled (VMT), as well as long driving range, fast refueling while maintaining excellent fuel economy comparable to regular (non-plug-in) hybrid electric vehicles (HEVs) when travelling longer distances. However, theoretical estimates of greenhouse gas (GHG) emissions from PHEVs rely on several idealization assumptions, any/all of which may not necessarily be realized in the real world. With many real-world factors involved, including daily VMT profile, charging behavior, weather conditions and drive aggressiveness, all of which possibly having complex interactions, quantitative analysis of the contribution of each factor towards the real-world/attained Well-to-wheels (WtW) GHG could become a daunting task. This research proposes an approach for estimating the
Hamza, KarimLaberteaux, KennethChu, Kang-Ching
Improving the efficiency of Battery Electric Vehicles (BEVs) is crucial for enhancing their range and performance. This paper explores the use of virtual tools to integrate and optimise various systems, with a particular focus on thermal management. The study considers global legislative drive cycles and real-world scenarios, including hot and cold weather conditions, charging cycles, and towing. A virtual vehicle model is developed to include major contributors to range prediction and optimisation, such as thermal systems. Key components analysed include high voltage (HV) and low voltage (LV) consumers (compressors, pumps, fans), thermal system performance and behaviour (including cabin climate control), thermal controllers, and thermal plant models. The emergent behaviour resulting from the interaction between hardware and control systems is also examined. The methodology involves co-simulation of hardware and control models, encompassing thermal systems (coolant, refrigerant, cabin
Tourani, AbbasPrice, ChristopherDutta, NilabzaMoran Ruiz, Eduardo
The surge in electric vehicle usage has expanded the number of charging stations, intensifying demands on their operation and maintenance. Public charging stations, often exposed to harsh weather and unpredictable human factors, frequently encounter malfunctions requiring prompt attention. Current methods primarily employ data-driven approaches or rely on empirical expertise to establish warning thresholds for fault prediction. While these approaches are generally effective, the artificially fixed thresholds they employ for fault prediction limit adaptability and fall short in sensitivity to special scenarios, timings, locations, and types of faults, as well as in overall intelligence. This paper presents a novel fault prediction model for charging equipment that utilizes adaptive dynamic thresholds to enhance diagnostic accuracy and reliability. By integrating and quantifying Environmental Influence Factors (EF), Scenario Influence Factors (SF), Fault Severity Factors (FF), and
Wang, HaoWang, NingLi, YuanTang, Xinyue
Track testing methods are utilized in the automotive industry for emissions and fuel economy certification. These track tests are performed on smooth road surfaces which deteriorate over time due to wear and weather effects, hence warranting regular track repaves. The study focuses on the impact of repaving on track quality and surface degradation due to weather effects. 1D surface profiles and 2D surface images at different spatial frequencies were measured at different times over a span of two years using various devices to study the repave and degradation effects. Data from coastdown tests was also collected over a span of two years and is used to demonstrate the impact of track degradation and repaving on road load characterization parameters that are used for vehicle certification tests. Kernel density estimation and non-parametric spectral estimation methods are used to visualize the characteristic features of the track at different times. In the pre-processing stage, outliers
Singh, YuvrajJayakumar, AdithyaRizzoni, Giorgio
The low emission of carbon and minimum level of soot formation in combustion engines and turbines strategy is adopted by many countries to counteract global warming and climate change. The use of ammonia with hydrocarbon fuels can limit the formation of soot and carbon emissions due to non-carbon atoms. The current study explores the use of ammonia with air at coflow flame conditions, which was not tested before. It may give the choice for diesel cycle engines to use the ammonia either with air or fuel. The combustion and emission characteristics of methane coflow flame were studied at low pressure and air polluted by ammonia conditions. The results showed that a significant decline in carbon formation was observed when ammonia was boosted, 5-10%. The impact of sub-atmospheric pressure, 90-70 KPa, on COx development was higher than that of NH3 addition, 0-5%, thanks to the lower formation of hydroxymethylium, formaldehyde, and aldehyde radical. In the environment of lower pressure, the
Hina, AnamAkram, M ZuhaibShafa, AmnaAkram, M Waqar
Opening a tailgate can cause rain that has settled on its surfaces to run off onto the customer or into the rear loadspace, causing annoyance. Relatively small adjustments to tailgate seals and encapsulation can effectively mitigate these effects. However, these failure modes tend to be discovered relatively late in the design process as they, to date, need a representative physical system to test – including ensuring that any materials used on the surface flow paths elicit the same liquid flow behaviours (i.e. contact angles and velocity) as would be seen on the production vehicle surfaces. In this work we describe the development and validation of an early-stage simulation approach using a Smoothed Particle Hydrodynamics code (PreonLab). This includes its calibration against fundamental experiments to provide models for the flow of water over automotive surfaces and their subsequent application to a tailgate system simulation which includes fully detailed surrounding vehicle geometry
Gaylard, Adrian PhilipWeatherhead, Duncan
As automotive technology advances, the need for comprehensive environmental awareness becomes increasingly critical for vehicle safety and efficiency. This study introduces a novel integrated wind, weather, and motion sensor designed for moving objects, with a focus on automotive applications. The sensor’s potential to enhance vehicle performance by providing real-time data on local atmospheric conditions is investigated. The research employs a combination of sensor design, vehicle integration, and field-testing methodologies. Findings prove the sensor’s capability to accurately capture dynamic environmental parameters, including wind speed and direction, temperature, and humidity. The integration of this sensor system shows promise in improving vehicle stability, optimizing fuel efficiency through adaptive aerodynamics, and enhancing the performance of autonomous driving systems. Furthermore, the study explores the potential of this technology in contributing to connected vehicle
Feichtinger, Christoph Simon
Optimal control of battery electric vehicle thermal management systems is essential for maximizi ng the driving range in extreme weather conditions. Vehicles equipped with advanced heating, ventilation and air-conditioning (HVAC) systems based on heat pumps with secondary coolant loops are more challenging to control due to actuator redundancy and increased thermal inertia. This paper presents the dynamic programming (DP)-based offline control trajectory optimization of heat pump-based HVAC aimed at maximizing thermal comfort and energy efficiency. Besides deriving benchmark results, the goal of trajectory optimization is to gain insights for practical hierarchical control strategy modifications to further improve real-time controllers’ performance. DP optimizes cabin inlet air temperature and flow rate to set the trade-off between thermal comfort and energy efficiency while considering the nonlinear dynamics and operating limits of HVAC system in addition to typically considered cabin
Cvok, IvanDeur, Josko
Triply Periodic Minimal Surface (TPMS) structures offer the possibility of reinventing structural parts and heat exchangers to obtain higher efficiency and lighter or even multi-functional components. The crescent global climate concern has led to increasingly stringent emissions regulations and the adoption of TPMS represents a resourceful tool for OEMs to downsize and lighten mechanical parts, thereby reducing the overall vehicle weight and the fuel consumption. In particular, TPMS structures are gaining growing interest in the heat exchanger field as their morphology allows them to naturally house two separate fluids, thus ensuring heat transfer without mixing. Moreover, TPMS-based heat exchangers can offer countless possible design configurations. These structures are obtained by periodic repetitions in the three spatial dimensions of a specific unit cell with defined dimensions and wall thickness. By tuning their characteristic parameters, the structure can be tailored to obtain
Torri, FedericoBerni, FabioMartoccia, LorenzoMarini, AlessandroMerulla, AndreaGiacalone, MauroColombini, Giulia
With Rapid growth of Electric Vehicles (EVs) in the market challenges such as driving range, charging infrastructure, and reducing charging time needs to be addressed. Unlike traditional Internal combustion vehicles, EVs have limited heating sources and primarily uses electricity from the running battery, which reduces driving range. Additionally, during winter operation, it is necessary to prevent window fogging to ensure better visibility, which requires introducing cold outside air into the cabin. This significantly increases the energy consumption for heating and the driving range can be reduced to half of the normal range. This study introduces the Ceramic Humidity Regulator (CHR), a compact and energy-efficient device developed to address driving range improvement. The CHR uses a desiccant system to dehumidify the cabin, which can prevent window fogging without introducing cold outside air, thereby reducing heating energy consumption. A desiccant system typically consists of two
Hamada, TakafumiShinoda, NarimasaKonno, YoshikiIhara, YukioIto, Masaki
Lane-keeping is critical for SAE Level 3+ autonomous vehicles, requiring rigorous validation and end-to-end interpretability. All recently U.S.-approved level 3 vehicles are equipped with lidar, likely for accelerating active safety. Lidar offers direct distance measurements, allowing rule-based algorithms compared to camera-based methods, which rely on statistical methods for perception. Furthermore, lidar can support a more comprehensive and detailed approach to studying lane-keeping. This paper proposes a module perceiving oncoming vehicle behavior, as part of a larger behavior-tree structure for adaptive lane-keeping using data from a lidar sensor. The complete behavior tree would include road curvature, speed limits, road types (rural, urban, interstate), and the proximity of objects or humans to lane markings. It also accounts for the lane-keeping behavior, type of adjacent and opposing vehicles, lane occlusion, and weather conditions. The algorithm was evaluated using
Soloiu, ValentinMehrzed, ShaenKroeger, LukePierce, KodySutton, TimothyLange, Robin
A glow plug is generally used to assist the starting of diesel engines in cold weather condition. Low ambient temperature makes the starting of diesel engine difficult because the engine block acts as a heat sink by absorbing the heat of compression. Hence, the air-fuel mixture at the combustion chamber is not capable of self-ignition based on air compression only. Diesel engines do not need any starting aid in general but in such scenarios, glow plug ensures reliable starting in all weather conditions. Glow plug is actually a heating device with high electrical resistance, which heats up rapidly when electrified. The high surface temperature of glow plug generates a heat flux and helps in igniting the fuel even when the engine is insufficiently hot for normal operation. Durability concerns have been observed in ceramic glow plugs during testing phases because of crack formation. Root cause analysis is performed in this study to understand the probable reasons behind cracking of the
Karmakar, NilankanOrban, Hatem
This SAE Aerospace Standard (AS) establishes the minimum performance standards for equipment used as secondary alternating current (AC) electrical power sources in aerospace electric power systems.
AE-7B Power Management, Distribution and Storage
This document establishes the minimum requirements for an environmental test chamber and test procedures to carry out anti-icing performance tests according to the current materials specification for aircraft deicing/anti-icing fluids. The primary purpose for such a test method is to determine the anti-icing performance under controlled laboratory conditions of AMS1424 Type I and AMS1428 Type II, III, and IV fluids.
G-12ADF Aircraft Deicing Fluids
This research investigates how distributed energy resources (DERs) and electric vehicles (EVs) affect distribution networks. With sensitivity analysis, the research focuses on how these integrations affect load profiles. The research focuses on sizing of various DERs and EV charging/discharging strategies to optimize the load profile, voltage stability, and network loss minimization. System parameters including load profile, EV charging pattern, weather conditions, DER sizes, and electricity pricing are analyzed to quantify their individual and combined impacts on load variability. However, with increased capacity of DERs, network losses increase. A mathematical model with system and operational constraints has been developed and simulated in MATLAB Simulink environment, validation of the proposed approach in improving the load profile, and reduction in network losses, with the intermittent power generation from DERs and EV integration. Simulation result shows that optimal capacity of
Khedar, Kamlesh KumarGoyal, Govind RaiSingh, Pushpendra
Rapid identification and cleanup of road debris are essential for enhancing traffic safety and ensuring unobstructed road conditions. Traditional detection methods often face challenges in accurately identifying debris in complex environments with varying light and weather conditions. To address these limitations, this study proposes a deep learning-based road debris detection method designed for improved accuracy and robustness. First, road images are processed using a semantic segmentation approach to remove background information, isolating only the drivable areas. This segmented region is then subjected to further object detection to filter out typical non-debris objects, such as vehicles, pedestrians, and non-motorized vehicles, thereby retaining a focused image that only contains potential debris or spill objects. Lastly, the processed image is compared to a baseline image to detect differences and identify road debris with high precision. Through these steps, the proposed method
Gao, Xiaofei
Storm surge disasters in the northern Indian Ocean and along the Bay of Bengal pose substantial risks to the safety of lives, property, and industrial trade within Myanmar's Ayeyarwady Region. The absence of long-term tidal data makes traditional frequency analysis methods inadequate for accurately predicting extreme water levels with high return periods. This study utilizes numerical simulations to forecast extreme water levels caused by recurrent cyclonic storm surges along Myanmar's coastline. A combined approach using the Monte Carlo stochastic model and the Delft3D hydrodynamic model was employed for these simulations. The results show that the Delft3D model is effective in predicting tidal levels in engineering contexts, addressing data deficiencies while identifying critical water levels. Model accuracy was validated through extensive simulations, confirming its suitability for forecasting extreme water levels. Although some discrepancies may arise due to limited data
Yin, KaiHe, LiyeLiu, KaofanLiu, ShuoXu, Sudong
Traffic prediction plays an important role in urban traffic management and signal control optimization. As research in this area advances, traffic prediction has become increasingly accurate. However, the complexity of the traffic system makes the quantification of uncertainty particularly important, as it is influenced by various factors such as weather changes, emergencies and road construction, which lead to the fluctuation and uncertainty of the traffic state. Although some progress has been made in traffic uncertainty quantification, most methods remain primarily focused on individual traffic observation points, with little exploration of the complex spatiotemporal dependencies at the road network level. In light of this situation, this paper proposes a spatiotemporal traffic prediction model based on Bayesian graph convolutional network, which can effectively capture the spatiotemporal dependence in traffic data, facilitating accurate predictions and comprehensive uncertainty
Li, LinfengLin, Limeng
There’s a lot of hype about generative AI, both pro and con. Researchers at the University of California, San Diego and the Allen Institute for Artificial Intelligence (Ai2) are on the pro side, demonstrating that it can have valuable global impact. They have developed a generative AI climate prediction model they call Spherical DYffusion, which is fast and agile enough to be used as a tool not just by scientists, but by anyone whose decisions are affected by climate trends.
Wet pavement conditions during rainfall present significant challenges to traffic safety by reducing tire–road friction and increasing the risk of hydroplaning. During high-intensity rain events, the roadway pavement tends to accumulate water, forming a film that can have serious implications for vehicle control. As the longitudinal speed of the vehicle increases, a water wedge forms in front of the tire, leading to partial loss of contact with the road. At critical hydroplaning speed, a complete water layer forms between the tire and the road. Although less common, dynamic hydroplaning poses severe risks when high-intensity rainfall coincides with high vehicle traveling speed, leading to a complete loss of control over vehicle steering capabilities. This study advances hydroplaning research by integrating real-world data from the Road Weather Information System (RWIS) with an existing hydroplaning model. This approach provides more accurate hydroplaning risk assessments, emphasizing
Vilsan, AlexandruSandu, CorinaAnghelache, Gabriel
In this article, a finite element analysis for the passenger car tire size 235/55R19 is performed to investigate the effect of temperature-dependent properties of the tire tread compound on the tire–road interaction characteristics for four seasons (all-season, winter, summer, and fall). The rubber-like parts of the tire were modeled using the hyperelastic Mooney–Rivlin material model and were meshed with the three-dimensional hybrid solid elements. The road is modeled using the rigid body dry hard surface and the contact between the tire and road is modeled using the non-symmetric node-to-segment contact with edge treatment. At first, the tire was verified based on the tire manufacturer’s data using numerical finite element analysis based on the static and dynamic domains. Then, the finite element analysis for the rolling resistance analysis was performed at three different longitudinal velocities (10 km/h, 40 km/h, and 80 km/h) under nominal loading conditions. Second, the steady
Fathi, HaniyehEl-Sayegh, ZeinabRen, Jing
The objective of this research is to present a novel variant of an Unmanned Aerial Vehicle (UAV) with an advanced flying wing configuration capable of detecting and rescuing individuals affected by avalanches. This leads to testing of the UAV, to identify if it can operate efficiently at the intended temperature and atmospheric conditions. Typically, UAVs can operate in a broad spectrum of temperatures. Regions prone to avalanches would experience near-cryogenic temperatures. The notion is investigated and tested in this specific scenario. The chosen location is Siachen, where temperatures can become as low as -25 degree Celsius (°C). It has been proven that a thermal camera aids the UAV to detect the distinct body heat signatures of individuals who are trapped under snow. The selection of wing, propeller, and vertical stabilizer airfoils is guided by standard analytical calculations, while the overall model is developed using 3D EXPERIENCE. The computational tests are conducted using
Veeraperumal Senthil Nathan, Janani PriyadharshiniPisharam, Akhila AjithSourirajan, LaxanaBaskar, SundharVinayagam, GopinathStanislaus Arputharaj, BeenaL, NatrayanSakthivel, PradeshRaja, Vijayanandh
The escalation of road infrastructure anomalies, such as speed breakers and potholes, presents a formidable challenge to vehicular safety, efficient traffic management, and road maintenance strategies worldwide. In addressing these pervasive issues, this paper proposes an advanced, integrated approach for the detection and classification of speed breakers and potholes. Utilizing a sophisticated blend of deep learning methodologies and enhanced image processing techniques, our solution leverages Object Detection to analyze and interpret real-time visual data captured through advanced vehicle-mounted camera systems. This research meticulously details the comprehensive process involved in the development of this system, including the acquisition and preprocessing of a vast, varied dataset representative of numerous road types, conditions, and environmental factors. Through rigorous training, testing, and validation phases, the model demonstrates remarkable proficiency in recognizing and
Thangaraju, ShanmuganathanNagarajan, MeenakshiGanesan, MaragathamRaja, SelvakumarSirotiya, AviralJasrotia, Bhargav
As part of the Nano4 EARTH initiative, a national challenge launched by the White House and the National Nanotechnology Initiative, researchers are exploring how innovations at the nanoscale can lead to groundbreaking solutions for a more sustainable future.
With the popularity of electric vehicles, the application development of heat pump type automobile air conditioning system has been focused. Meanwhile, the traditional R134a needs to be replaced by more environmentally-friendly refrigerants under the Kigali Amendment. In this paper, a novel direct expansion heat pump air conditioning system with three circuit switching (DXACS) was proposed, and three low GWP refrigerants R1234yf, R1234ze(E) and R290 were carried out to evaluate the system performance. The results show that the winter range attenuation ratio of DXACS is 26.9%, significantly lower than the prototype EV360 (57.5%); the DXACS with R290 shows the best heating performance, COPh and qcv are 2.3% and 57.3% higher than R134a in extremely cold conditions, respectively. This study provides valuable insights for the development of efficient and green thermal management technology of new energy vehicles.
Zhu, TengfeiLiu, YeChen, Qinghua
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