bluuebunny/crossref_metadata_2025 huggingface dataset:
Determinants of depression in Indian tribal adults: Evidence from the Longitudinal Ageing Study in India Wave-I survey
Authors: Deepani Vijit , Nayak Itishree , Rani Manju , Taneja N. K. , Sahu Damodar , Rao M. Vishnu Vardhana , Sharma Ravendra Kumar
Published: April 2024

Background & objectives:

The tribal populations are vulnerable to mental health issues owing to various reasons. However, limited research has been conducted to assess depression and related determinants among tribal adults aged ≥45 yr (45 years and older). The present study aimed to assess the prevalence and sociodemographic and health determinants of depressive symptoms among the scheduled tribe (ST) population aged ≥45 yr in India.

Methods:

The present study analyzed the Wave I data of the Longitudinal Ageing Study in India conducted between April 2017 to December 2018. The outcome variables in the present study were self-reported depressive symptoms. Two internationally recognised tools, the Centre for Epidemiologic Studies Depression scale (CES-D) and Composite International Diagnostic Interview-Short Form (CIDI-SF), were used to obtain the data, however, only the CES-D data are utilized in this study. The present study focused on 12,215 ST individuals aged ≥45 yr from whom information about depressive symptoms was collected and analyzed.

Results:

Nearly 25 per cent ST population aged 45 yr or older experienced depressive symptoms. The likelihood of experiencing depressive symptoms among the ST population aged ≥45 yr was negatively associated with 10 or more years of education and living with children and others and positively associated with experiencing multiple morbidity conditions.

Interpretation & conclusions:

Given the substantial burden of depression among the adult ST population, the present study lays emphasis on raising the awareness about depressive symptoms and strengthen the availability of mental health services among the ST community through intensive campaigns and engagement of ST individuals along with other key stakeholders. Higher education, living with spouse and children and a physically active lifestyle can play a crucial role in limiting depressive symptoms among the tribal adults (≥45 yr). It is paramount to regularly screen depressive symptoms and conduct more microlevel studies to evaluate socioeconomic and health determinants of depressive symptoms among ST communities living in different geographic regions.
Antibody Seroprevalence to Spotted Fever Group Rickettsiae in Miraflores, Colombia: A Cross-Sectional Study in Humans and Dogs
Authors: Gual-Gonzalez Lídia , Cantillo-Barraza Omar , Torres Myriam E. , Quintero-Vélez Juan C. , Medina Manuel , Self Stella C. W. , Nolan Melissa S.
Published: April 2024

Tick-borne disease burdens are increasing globally, impacting mostly rural and vulnerable communities. Among the most important emerging tick-borne pathogens are the Rickettsia species within the spotted fever group (SFGR) because of their genetic diversity and high lethality rate. Colombia is highly affected by SFGR despite not being reportable diseases; thus, research and clinical management are neglected. Although some departments have demonstrated high seroprevalence rates, in others, such as Boyacá Department, seroprevalence is unknown. Rickettsioses have not been described in Boyacá since 1943, and conversations with local physicians raised suspicions of recent undiagnosed disease compatible with rickettsiosis in some rural areas of the department, warranting epidemiological investigation. Using biobanked human and canine samples from a previous 2021 vector-borne disease study in Miraflores municipality, Boyacá, we had an opportunity to unearth SFGR’s exposure in the region. Samples were evaluated using IgG indirect fluorescent assays against SFGR and complemented by survey questionnaires evaluating associated factors. Findings yielded first-time SFGR serological evidence in Boyacá with a 26.5% seroprevalence among dogs and a 20.4% among humans. Human and dog seroprevalences were positively associated, suggesting the presence of domestic transmission. Owning a greater number of domestic animals (prevalence ratio adjusted for all measured factors [aPR], 1.52) and living near crop fields (aPR, 7.77) were associated with an increased likelihood of household seropositivity. Our findings are consistent with the literature in Colombia, uncovering a suspected region where the disease is endemic. Future studies are warranted to continue defining high-risk areas to determine public health intervention plans.
An Investigation of ADAS Camera Performance Degradation Using a Realistic Rain Simulation System in Wind Tunnel
Authors: Li Long , Pao Wing Yi , Howorth Joshua , Agelin-chaab Martin , Roy Langis , Komar John , Knutzen Julian , Baltazar Alex , Muenker Klaus
Published: April 2024

Modern advances in the technical developments of Advanced Driver Assistance Systems (ADAS) have elevated autonomous vehicle (AV) operations to a new height. Vehicles equipped with sensor based ADAS have been positively contributing to safer roads. As the automotive industry strives for SAE Level 5 full driving autonomy, challenges inevitably arise to ensure ADAS performance and reliability in all driving scenarios, especially in adverse weather conditions, during which ADAS sensors such as optical cameras and LiDARs suffer performance degradation, leading to inaccuracy and inability to provide crucial environmental information for object detection. Currently, the difficulty to simulate realistic and dynamic adverse weather scenarios experienced by vehicles in a controlled environment becomes one of the challenges that hinders further ADAS development. While outdoor testing encounters unpredictable environmental variables, indoor testing methods, such as using spray nozzles in a wind tunnel, are often unrealistic due to the atomization of the spray droplets, causing the droplet size distributions to deviate from real-life conditions. A novel full-scale rain simulation system is developed and implemented into the ACE Climatic Aerodynamic Wind Tunnel at Ontario Tech University with the goal of quantifying ADAS sensor performance when driving in rain. The designed system is capable of recreating a wide range of dynamic rain intensity experienced by the vehicle at different driving speeds, along with the corresponding droplet size distributions. Proposed methods to evaluate optical cameras are discussed, with sample results of object detection performance and image evaluation metrics presented. Additionally, the rain simulation system showcases repeatable testing environments for soiling mitigation developments. It also demonstrates the potential to further broaden the scope of testing, such as training object detection datasets, as well as exploring the possibilities of using artificial intelligence to expand and predict the rain system control strategies and target rain conditions.
Developing an Automated Vehicle Research Platform by Integrating Autoware with the DataSpeed Drive-By-Wire System
Authors: Guo Hengcong , Li Jiangtao , Saravanan Nithish Kumar , Wishart Jeffrey , Zhao Junfeng
Published: April 2024

Over the past decade, significant progress has been made in developing algorithms and improving hardware for automated driving. However, conducting research and deploying advanced algorithms on automated vehicles for testing and validation remains costly, especially for academia. This paper presents the efforts of our research team to integrate the newest version of the open-source Autoware software with the commercially available DataSpeed Drive-by-Wire (DBW) system, resulting in the creation of a versatile and robust automated vehicle research platform. Autoware, an open-source software stack based on the 2nd generation Robot Operating System (ROS2), has gained prominence in the automated vehicle research community for its comprehensive suite of perception, planning, and control modules. The DataSpeed DBW system directly communicates with the vehicle's CAN bus and provides precise vehicle control capabilities. However, there was no existing software package to make the ROS2-based Autoware interact with the DataSpeed DBW kit. We have successfully developed the software module to translate Ackermann control commands from Autoware’s control module to the DBW system, enabling it to execute both longitudinal and lateral controls of the vehicle. The interface also provides comprehensive feedback signals on vehicle status to Autoware. Rigorous testing has been conducted to verify the interface's functionality. Our successful experience integrating Autoware and the DataSpeed DBW system can serve as a valuable resource for researchers aiming to develop similar research vehicle platforms and accelerate the development of safe and efficient automated vehicles. The source code is available at https://github.com/BELIV-ASU/BELIV_vehicle_interface.git .
A Study on Optimization Development of Cooling Fan Motor for EMC
Authors: Son Jiwan , Lim Taewoong , Kim Chang Hwan
Published: April 2024

With the trend of electrification and connectivity, more electrified parts and more integrated chips are being applied. Consequently, potential problems based on electro-magnetic could occur more easily, and interest on EMC performance has been rising according to the degree of electrification. In this paper, one of the most severe systems, cooling fan motor in terms of EMI, is analyzed and improvement methods are suggested for each type of cooling fan. Additionally, an optimized configuration of improvement method for EMC has been derived through analysis and study. Finally, verification and validation are implemented at the system and vehicle levels.

In this paper, the following effects were obtained by analyzing the cooling fan motor system and reviewing and optimizing the design factors from the EMC perspective.
(1)
Analyzing the impact of each EMC reduction device currently applied to the cooling fan motor according to specifications and optimizing the specification combination based on the results. The optimization was applied to the actual vehicle in mass production.

(2)
Checking the relationship between the frequency domain and the operating condition of the cooling fan in terms of the RE/CE performance regulation value for the cooling fan motor and suggesting mitigation of the regulation value by considering environmental condition of the cooling fan to optimize the noise reduction filter specifications. It allows improving profitability by reducing vehicle costs.

(3)
Analyzing all surge-influencing factors in the TE performance regulation of the cooling fan motor and devising a logic based on the results. The system was constructed to satisfy EMC performance without applying any improvement elements or devices, thereby improving profitability.

(4)
The EMC design specifications of other similar parts can refer to the optimization methodology presented in this paper for profitability improvement.
An Enhanced Obstacle Detection in ADAS Applications by Integrating C-V2X with a Stereo Camera Vision System
Authors: Amin Mohammad Hasan , Konjeti Haswanth Babu , Park Jungme , Wang Yunsheng
Published: April 2024

Recent advancements in 5G technology significantly advance Cellular Vehicle-to-Everything (C-V2X) technology. C-V2X can substantially improve road safety by providing vehicles on the road connectivity with other vehicles, roadside infrastructure, and networks. Integration of C-V2X with Autonomous Driving (AD) and Advanced Driver Assistance Systems (ADAS) enhances road safety by sharing safety warnings and traffic information that vehicle sensors may not identify. In this paper, we developed an enhanced obstacle detection system by integrating C-V2X and a state-of-the-art DNN algorithm. First, a C-V2X Roadside Unit (RSU) is installed on the utility pole. A stereo camera with a small computing unit is connected to RSU. The deployed object detection system with a stereo camera continuously monitors the intersection area and broadcasts the object detection results to the nearby vehicles equipped with a C-V2X On-Board Unit (OBU). Since the stereo camera is used, the proposed system is able to estimate the object distance from the camera using stereo cameras' depth perception capabilities. The power of 5G technology is utilized to facilitate the direct communication of environmental perception results. Real-time experiments are conducted on the testing track to assess the proposed system, including latency in vehicle-to-everything communication across diverse scenarios. The experimental results show the deployed enhanced object detection system on the RSU is able to broadcast critical traffic information with an average latency of 1 ms, enabling the swift sharing of crucial information concerning obstacles, pedestrians, and vehicles to the other cars equipped with OBUs. The 5G-enabled transmission offers remarkable attributes, including high data rates, minimal latency, and reliable connections, rendering it well-suited for applications within the C-V2X.
Impact of Vehicle-to-Grid (V2G) on Battery Degradation in a Plug-in Hybrid Electric Vehicle
Authors: Timilsina Laxman , Moghassemi Ali , Buraimoh Elutunji , Arsalan Ali , Chamarthi Phani Kumar , Ozkan Gokhan , Papari Behnaz , Edrington Christopher
Published: April 2024

Electric vehicles (EVs) are becoming increasingly recognized as an effective solution in the battle against climate change and reducing greenhouse gas emissions. Lithium-ion batteries have become the standard for energy storage in the automobile industry, widely used in EVs due to their superior characteristics compared to other batteries. The growing popularity of the Vehicle-to-grid (V2G) concept can be attributed to its surplus energy storage capacity, positive environmental impact, and the reliability and stability of the power grid. However, the increased utilization of the battery through these integrations can result in faster degradation and the need for replacement. As batteries are one of the most expensive components of EVs, the decision to deploy an EV in V2G operations may be uncertain due to the concerns of battery degradation from the owner’s perspective. This paper examines the degradation of the battery employed in Plug-in Hybrid Electric Vehicles (PHEVs) for both V2G connection and its typical operating schedule. For assessing the degradation in driving scenarios, the US06 drive cycle is employed. On the other hand, for the V2G scenario, a 10 kW bidirectional charger is utilized. The charger discharges the battery up to 20 kWh in 2 hours or up to 60% state of charge (SoC) and subsequently charges it back to 90% SoC at a constant 1C rate. This V2G setup simulates the discharging and charging patterns typically observed in real-world scenarios and allows for evaluating battery performance and degradation under such conditions. Finally, an economic analysis is conducted by considering the capacity loss of the battery resulting from the V2G connection. This study considers the incentives obtained through the V2G connection, providing an assessment of the economic viability and potential benefits associated with utilizing the vehicle in V2G applications.
“FEV’s ‘CogniSafe’: An Innovative Deep Learning-Based AI Driver Monitoring System for the Future of Mobility”
Authors: Wani Ankit , Singh Jyotsana , Kumari Deepa , Ithape Avinash , Rapanwad Govind
Published: April 2024

Driver state monitoring is a crucial technology for enhancing road safety and preventing human error-caused accidents in the era of autonomous vehicles. This paper presents CogniSafe, a comprehensive driver monitoring system that uses deep learning and computer vision methods to detect various types of driver distractions and fatigue. CogniSafe consists of four modules: Driver anomaly detection and classification: A novel two-phase network that proposes and recognizes driver anomalies, such as texting, drinking, and adjusting radios, using multimodal and multiview input. Gaze estimation: A video-based neural network that jointly learns head pose and gaze dynamics, achieving robust and efficient gaze estimation across different head poses. Eye state analysis: A multi-tasking CNN that encodes features from both eye and mouth regions, predicting the percentage of eye closure (PERCLOS) and the frequency of mouth opening (FOM). Head pose estimation: A CNN-based method that estimates the head pose from a single face image, providing additional information for driver attention assessment. CogniSafe integrates the outputs of each module into a specific driver status measurement and produces the driver's level of alertness on a scale from 0 to 5. The paper evaluates the performance of each module on benchmark datasets and discusses the practicality, technicality, and pivotal role of CogniSafe in the development and deployment of autonomous vehicles. The paper contributes to the field of driver monitoring by providing a novel and comprehensive system that covers the most common types of driver distractions and fatigue using deep learning and computer vision methods. The paper also provides a comprehensive overview of the current state-of-the-art and the future challenges of driver monitoring systems for a safer, more connected future of mobility.
Sensor-Fused Low Light Pedestrian Detection System with Transfer Learning
Authors: Thota Bharath kumar , Somashekar Karthik , Park Jungme
Published: April 2024

Objection detection using a camera sensor is essential for developing Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) vehicles. Due to the recent advancement in deep Convolution Neural Networks (CNNs), object detection based on CNNs has achieved state-of-the-art performance during daytime. However, using an RGB camera alone in object detection under poor lighting conditions, such as sun flare, snow, and foggy nights, causes the system's performance to drop and increases the likelihood of a crash. In addition, the object detection system based on an RGB camera performs poorly during nighttime because the camera sensors are susceptible to lighting conditions. This paper explores different pedestrian detection systems at low-lighting conditions and proposes a sensor-fused pedestrian detection system under low-lighting conditions, including nighttime. The proposed system fuses RGB and infrared (IR) thermal camera information. IR thermal cameras are used as they are capable of generating good quality images under low illumination and can help better object detection at nighttime. Utilizing the two sensors, a two-stream pedestrian detection system is developed using the YOLO (You Only Look Once) architecture and transfer learning technology. The RGB+ IR sensor fused system is evaluated with the available public data sets and compared with the systems developed with a single sensor, an IR camera-only system. The sensor-fused system is successfully deployed on the NVIDIA Jetson Orin. The overall detection results under low light conditions show that the proposed sensor fusion system significantly improves the overall performance in object detection under low lighting conditions.
Vehicle Control Development - Converting a Medium-Duty Commercial Truck into a Battery Electric Vehicle
Authors: Liu Xiaobing , Guo Chengyun , Rama Neeraj , Theunissen Frans , Olin Pete , Ling Gang , Pan Yang , Mohon Sara , Van Maanen Keith , Chen Wei
Published: April 2024

The transition towards electrification in commercial vehicles has received more attention in recent years. This paper details the conversion of a production Medium-Duty class-5 commercial truck, originally equipped with a gasoline engine and 10-speed automatic transmission, into a battery electric vehicle (BEV). The conversion process involved the removal of the internal combustion engine, transmission, and differential unit, followed by the integration of an ePropulsion system, including a newly developed dual-motor beam axle that propels the rear wheels. Other systems added include an 800V/99 kWh battery pack, advanced silicon carbide (SiC) inverters, an upgraded thermal management system, and a DC fast charging system.

A key part of the work was the development of the propulsion system controls, which prioritized drivability, NVH suppression, and energy optimization. The improvement of the electrified truck compared to the gasoline version in responsiveness and reduced noise emissions underscores the efficacy of the BEV's design. This enhanced performance was substantiated by a quantifiable reduction in brake use, resulting in improved energy efficiency.

This paper describes the development, implementation, and verification of the vehicle control systems, including the interface with the existing production vehicle controllers, the inverter control strategy, a one-pedal driving function, the management of the DC fast charging protocols, a thermal management system, fault diagnosis algorithms, and an intuitive in-vehicle display interface. Performance evaluations have demonstrated a remarkable 40%+ improvement in the BEV's 0-100 km/h acceleration compared to the gasoline-powered stock vehicle. The paper also addresses some obstacles encountered during the electrification process.
A Case Study of Planning and Analyzing the Implementation of an AGV System Using Discrete Event Simulation
Authors: Raza Mohsin , Bilberg Arne , Ilev Dimitar-Delyan
Published: April 2024

This article presents a case study that was conducted at a renowned Danish manufacturing company that desired to employ AGVs (automated-guided vehicles) in one of its production facilities. The main goal was to create an AGV (automated-guided vehicle) system that is well synchronized with the manufacturing facility so that intralogistics problems are avoided during manufacturing activities. AGV routing and scheduling, loading, and waiting periods, battery management, and failure management were all considered when developing the AGV logic. As a result, it was confirmed that the AGV system in place can support a production system to meet pulse time requirements. A hierarchically structured discrete event simulation model was created to examine the logic of AGVs and the interplay between AGVs and manufacturing operations. The simulation study confirmed that AGV implementation will not affect the production system's ability to meet the set pulse time requirements. Furthermore, the simulation study offered meaningful insights regarding the layout, quantity, and control logic of AGVs.
Numerical Study of an EGR Dilution in a Pre-Chamber Spark Ignited Engine Fuelled by Natural Gas
Authors: Dilber Viktor , Krajnovic Josip , Ugrinić Sara , Sjeric Momir , Tomic Rudolf , Kozarac Darko
Published: April 2024

Exhaust gas recirculation (EGR) is a proven strategy for the reduction of NOX emissions in spark ignited (SI) engines and compression ignition engines, especially in lean burn conditions where the increase of thermal efficiency is obtained. The dilution level of the mixture with EGR is in a conventional SI engine limited by the increase of combustion instability (CoV IMEP). A possible method to extend the EGR dilution level and ensure stable combustion is the implementation of an active pre-chamber combustion system. The pre-chamber spark ignited (PCSI) engine enables fast and stable combustion of lean mixtures in the main chamber by utilizing high ignition energy of multiple flame jets penetrating from the pre-chamber to the main chamber. In this paper, as an initial research step, a numerical analysis is performed by employing the 0D/1D simulation model, validated with the initial experimental and 3D-CFD results. The simulation model is used for the prediction of possible benefits of using EGR dilution in the methane fuelled PCSI engine, and to determine the possible operating window that will be experimentally investigated in the next phase. The obtained results indicate that the combined approach of diluting the mixture with both air and EGR can result with further increase of indicated efficiency when compared to the air dilution only approach. While it is not possible to reduce the NOX emissions under the regulation limit when targeting MBT optimized spark timings, it can be achieved by retarding the spark timing at the expanse of efficiency. The resulting efficiency at such operation is still higher than that obtained with the air dilution approach at MBT optimized spark timings, proving the potential of the investigated approach.
Development and Validation of a Reduced Chemical Kinetic Mechanism of Dimethyl Carbonate and Ethylene Carbonate
Authors: Zhang Kuiwen , Puduppakkam Karthik , Shelburn Anthony
Published: April 2024

With the rapid development of electric vehicles, the demands for lithium-ion batteries and advanced battery technologies are growing. Today, lithium-ion batteries mainly use liquid electrolytes, containing organic compounds such as dimethyl carbonate and ethylene carbonate as solvents for the lithium salts. However, when thermal runaway occurs, the electrolyte decomposes, venting combustible gases that could readily be ignited when mixed with air and leading to pronounced heat release from the combustion of the mixture. So far, the chemical behavior of electrolytes during thermal runaway in lithium-ion batteries is not comprehensively understood. Well-validated compact chemical kinetic mechanisms of the electrolyte components are required to describe this process in CFD simulations. In this work, submechanisms of dimethyl carbonate and ethylene carbonate were developed and adopted in the Ansys Model Fuel Library (MFL). Further improvements were made to enhance the kinetic consistency between these submechanisms and the base mechanism of the MFL. These mechanisms were validated using recently published experimental datasets over a wide range of conditions and show satisfactory performance. Analysis of the simulated results has revealed the important reaction pathways in the decomposition of dimethyl carbonate and ethylene carbonate. The species involved in the most critical pathways were selected as key species in the subsequent mechanism reduction using Ansys Reaction Workbench. Multiple mechanism reduction approaches were applied in combination to reduce the mechanism described here to 38 species and 177 reactions. This mechanism is ready to be used in CFD simulation.
Combustion Development and Efficiency Improvement for Hybrid Engines
Authors: Xu Zheng , Qiu Jie , Zhang ZiQing , Cheng Chuanhui , Zhang YaJun , Yang Yang , Wang Yingzhen , Lu Yuan , Zhou Zhou , Li XiaoYang
Published: April 2024

In the pursuit of carbon emission reduction, hybridization has emerged as a significant trend in powertrain electrification. As a crucial aspect of hybrid powertrain system development, achieving high brake thermal efficiency (BTE) and a wide operating range with high efficiency are essential for hybrid engines to effectively integrate with the hybrid system.

When developing dedicated hybrid engines (DHE), several design considerations come into play. First, in order to make efficient use of available resources and enable engine production on the same assembly line as conventional engines, it is crucial to maintain consistency in key design parameters of the cylinder head and block, thus extending the platform-based design approach. Among the key measures to achieve high BTE, cooled exhaust gas recirculation (EGR) has been extensively explored and proven effective in improving efficiency by mitigating knocking and reducing engine cooling heat loss. Fast combustion, acting as a facilitator, becomes crucial for the system to handle high EGR rates. Therefore, a high-tumble combustion system design is required as an integral part of the hybrid engine to promote rapid combustion.

Optimizing the gas exchange system is another crucial aspect in achieving high brake thermal efficiency. Investigation results indicate that through system optimization and trade-offs, optimal matches can be found among EGR rate, cam duration, and compression ratio for a hybrid engine. Furthermore, by optimizing energy management strategy with the hybrid system, the engine operates under high-efficiency regions for the majority of the WLTC test cycle, resulting in reduced fuel consumption.

This paper describes the evolution of combustion system design from conventional engines to DHE at SAIC Motor, and presents investigations into the impact of key technical measures on brake thermal efficiency. It also explores the optimization of energy management strategies and their effect on engine operating conditions and fuel consumption of the hybrid vehicle in the WLTC cycle.
Experimental Comparison of Spark and Jet Ignition Engine Operation with Ammonia/Hydrogen Co-Fuelling
Authors: Ambalakatte Ajith , Cairns Alasdair , Geng Sikai , Varaei Amirata , Hegab Abdelrahman , Harrington Anthony , Hall Jonathan , Bassett Michael
Published: April 2024

Ammonia (NH3) is emerging as a potential fuel for longer range decarbonised heavy transport, predominantly due to favourable characteristics as an effective hydrogen carrier. This is despite generally unfavourable combustion and toxicity attributes, restricting end use to applications where robust health and safety protocols can always be upheld. In the currently reported work, a spark ignited thermodynamic single cylinder research engine was upgraded to include gaseous ammonia and hydrogen port injection fueling, with the aim of understanding maximum viable ammonia substitution ratios across the speed-load operating map. The work was conducted under stoichiometric conditions with the spark timing re-optimised for maximum brake torque at all stable logged sites. The experiments included industry standard measurements of combustion, performance and engine-out emissions. It was found possible to run the engine on pure ammonia at low engine speeds at low to moderate engine loads in a fully warmed up state. When progressively dropping down below this threshold load limit, an increasing amount of hydrogen co-fueling was required to avoid unstable combustion. All metrics of combustion, efficiency and emissions tend to improve when moving upwards from the threshold load line. A maximum net indicated efficiency of 40% was achieved at 1800rpm 16bar IMEPn, with efficiency tending to increase with speed and load. Furthermore, comparing spark ignition with active and passive jet ignition (with the former involving direct injection of hydrogen into the pre-chamber only and the main chamber port fueled with ammonia), at different loads it was found that active systems can significantly improve early burn phase and reduce engine-out NOx compared to passive jet ignition and SI. While both Jet ignition systems required supplementary hydrogen, it accounted for ~1% (active) of the total fuel energy at high loads increasing with reduction in engine load.
A Comparative Study of Knock Formation in Gasoline and Methanol Combustion Using a Multiple Spark Ignition Approach: An Optical Investigation
Authors: Uddeen Kalim , Tang Qinglong , Shi Hao , Almatrafi Fahad , Magnotti Gaetano , Turner James
Published: April 2024

Engine knock is a major challenge that limits the achievement of higher engine efficiency by increasing the compression ratio of the engine. To address this issue, using a higher octane number fuel can be a potential solution to reduce or eliminate the propensity for knock and so obtain better engine performance. Methanol, a promising alternative fuel, can be produced from conventional and non-conventional energy resources, which can help reduce pollutant emissions. Methanol has a higher octane number than typically gasolines, which makes it a viable option for reducing knock intensity. This study compared the combustion characteristics of gasoline and methanol fuels in an optical spark-ignition engine using multiple spark plugs. The experiment was carried out on a single-cylinder four-stroke optical engine. The researchers used a customized metal liner with four circumferential spark plugs to generate multiple flame kernels inside the combustion chamber. The results indicated that generating multiple flames inside the cylinder caused higher pressures and temperatures, which led to the production of more knocking cycles with higher knock intensities. Additionally, the study showed that methanol combustion produced significantly lower knock intensity with better engine power output compared to gasoline combustion due to its higher octane rating enabling more advanced ignition and its faster flame propagation. The researchers characterized various knock intensities obtained by multiple ignition sites and exhibited a transition from normal combustion to slight knock, medium knock, and high knock cases. Furthermore, the researchers performed high-speed natural-flame-luminosity (NFL) imaging to capture the multiple flame development and autoignition kernels inside the cylinder for various combustion cases. This study provides a detailed understanding of the combustion characteristics of gasoline and methanol fuels in a spark-ignition engine and can be used to further optimize engine performance by reducing knock intensity and increasing engine efficiency.
Effect of In-Cylinder Flow Motion on Fuel-Air Mixture Formation in a Medium-Duty DI-SI H2 Engine: An Experimentally Supported CFD Study
Authors: Mota Ferreira João , Oung Richard , Foucher Fabrice
Published: April 2024

The increased utilization of batteries and fuel-cells for powering electric applications, as well as bio- and e-fuels into internal combustion engines are seen as options to lower the carbon footprint of industry and transportation sectors. When high power outputs and fast refueling are requisites, H2 ICEs may be a relevant choice. Applications include electricity conversion within a genset or mechanical energy in a vehicle. Within this framework, a John Deere 4045 Diesel engine converted to a H2 single-cylinder is studied at relevant operating conditions for the mentioned use cases, which pose high torque and power output requirements. The modified engine integrates a Phinia DI-CHG 10 outward-opening H2 injector instead of the Diesel unit, as well as a spark-plug rather than the glow-plug. To explore the effects of in-cylinder air flow on the H2-air mixing, two piston designs are employed: one conserves the intake generated swirl; the other contains deflectors promoting a more complex flow and resulting in a lower swirl ratio. Tests concerning this work are performed at 1500 rpm, suitable for electricity generation at a frequency of 50 Hz, start of injection timing at -120 °CA aTDC, injection pressure of 41 bar and air-fuel equivalence ratio of 2.0. The in-cylinder mixing study is supported by 3D-CFD non-reactive simulations, performed with CONVERGE. The computational setup relies on a validation for the injection event within a constant volume chamber, as well as the agreement between experimental and numerical quantities of air and H2 into the cylinder. In-cylinder flow pattern and H2-air mixing are shown to be affected according to piston design. The trends of mixture distribution are consistent for different engine load cases, providing understanding for experimental results such as NOx emissions and combustion indicators.
Active Damping Control and Architecture within a Hybrid Supervisor Control Structure
Authors: Patel Nadirsh , Rostiti Cristian , Walsh McKenzie
Published: April 2024

This paper focuses on an inherent problems of active damping control prevalent in contemporary hybrid torque controls. Oftentimes, a supervisory torque controller utilizes simplified system models with minimal system states representation within the optimization problem, often not accounting for nonlinearities and stiffness. This is motivated by enabling the generation of the optimum torque commands with minimum computational burden. When inherent lash and stiffness of the driveline are not considered, the resulting command can lead to vibrations and oscillations in the powertrain, reducing performance and comfort. The paper proposes a Linear Quadratic Integral (LQI)-based compensator to be integrated downstream the torque supervisory algorithm, which role is to shape transient electric machine torques, compensating for the stiffness and backlash present in the vehicle while delivering the driver-requested wheel torque. The main strategy includes algorithms to control the non-linearity of backlash and techniques to handle the system when operating in its linear region. The overall logic outputs a shaped driver-demanded torque at the vehicle level capable of balancing drivability metrics considering all stiffness in the system. Other model-based techniques are presented and compared to the proposed solution to highlight its benefits.
Development of a Dual Motor Beam eAxle for Medium Duty Commercial Vehicle Application
Authors: Guo Chengyun , Van Maanen Keith , Liu Xiaobing
Published: April 2024

Considering the current trend towards the electrification of commercial vehicles, the development of Beam eAxle solutions has become necessary. The utilization of an electric drive unit in heavy-duty solid axle-based commercial vehicles presents unique and demanding challenges. These include the necessity for elevated peak and continuous torque while meeting packaging constraints, structural integrity requirements, and extended service life. One such solution was developed by BorgWarner to address these challenges. This paper offers a comprehensive overview of the design and development process undertaken for this Dual Motor Beam eAxle system. This includes the initial comparison of various eAxle solutions, the specifications of components selected for this design, and the initial results from dyno and vehicle development.
Drive Cycle-Based Design Optimization of Traction Motor Drives for Battery Electric Vehicles Using Data-Driven Approaches
Authors: Mohammadi Hossain , Saini Sandeep , Nasirizarandi Reza , Balamurali Aiswarya
Published: April 2024

This paper demonstrates a data-driven methodology for the system-level design of high-power traction motor drives in modern battery electric vehicles. With the immense growth of battery electric vehicles in this transformative decade, the expected time to develop and market these powertrain components is becoming significantly shorter than for internal combustion engines. This rising demand is further complicated due to more stringent cost, efficiency and power density targets set by the U.S. Department of Energy. Hence, a system-level perspective is maintained in this data-driven methodology to identify the design requirements for traction motor drives by relying on a dynamic vehicle simulation toolchain and various drive cycles (e.g., EPA MCT, WLTC, US06, etc.). The proposed data-driven approach can be used across different battery electric vehicle platforms including passenger and commercial types. A case study for a future-proof high-voltage architecture is demonstrated here for a C-segment all-wheel-drive mass market battery electric vehicle. Simulation results in this case study, validated against real-world driving data, indicate improvement in the total energy loss for different drive cycles as well as reduction in the mass, volume, and current draw of the designed machine using system-level feedback, thereby enabling higher torque and power density. The simulation results indicate that the total energy losses for five drive cycles were reduced by at least 11% and at most 27%, while increasing the Tip-In (0–100 kph) acceleration time by 3 seconds; a compromise between vehicle performance and driving efficiency is expected. The operating points from various driving scenarios define the overall sizing requirements of the traction motor drive through statistical analysis in order to meet different optimization targets, such as extending the maximum efficiency region. These system-level requirements of the traction motor drive directly affect the co-design framework of multiphysics simulations along with the vehicle dynamics. The proposed data-driven methodology aids in effectively addressing the vehicle-level performance targets while downsizing the traction motor drive components to increase the overall range and reduce the system costs.
Influence of Working Conditions and Operating Parameters on the Energy Consumption of a Full-Electric Bus. Experimental Assessment
Authors: Belloni Mattia , Tarsitano Davide , Sabbioni Edoardo
Published: April 2024

Given the growing interest in improving the efficiency of the bus fleet in public transportation systems, this paper presents an analysis of the energy consumption of a battery electric bus. During the experimental campaign, a battery electric bus was loaded using sand payloads to simulate the passenger load on board and followed another bus during regular service. Data related to the energy consumed by various bus utilities were published on the vehicle’s CAN network using the FMS standard and sampled at a frequency of 1 Hz. The collected experimental data were initially analyzed on a daily basis and then on a per-route basis. The results reveal the breakdown of energy consumption among various utilities over the course of each day of the experiment, highlighting those responsible for the highest energy consumption. Subsequently, the relationship between the energy consumption of the traction motor and the climate control system was investigated concerning environmental parameters such as total distance traveled, time taken to complete the service, average speed, driver’s driving style, route characteristics, internal temperature, external temperature, and the air conditioning system’s reference temperature while the bus was in service.
Performance Analysis of Fuel Cells for High Altitude Long Flight Multi-rotor Drones
Authors: Huang Xing , Song Ke , Huang Lixin , Feng Yuqiang , Wang Zhaowei
Published: April 2024

In recent years, the burgeoning applications of hydrogen fuel cells have ignited a growing trend in their integration within the transportation sector, with a particular focus on their potential use in multi-rotor drones. The heightened mass-based energy density of fuel cells positions them as promising alternatives to current lithium battery-powered drones, especially as the demand for extended flight durations increases. This article undertakes a comprehensive exploration, comparing the performance of lithium batteries against air-cooled fuel cells, specifically within the context of multi-rotor drones with a 3.5kW power requirement.

The study reveals that, for the specified power demand, air-cooled fuel cells outperform lithium batteries, establishing them as a more efficient solution. Recognizing the nuanced influence of altitude on the external environment, the research introduces models, including a power demand model and a thermal balance model, to systematically analyze altitude's impact on critical parameters such as fuel cell stack output, thermal management, and endurance range.

Furthermore, sensitivity analysis delves into the multifaceted effects of variables such as frame mass, payload, and temperature on the study's outcomes. This approach not only enriches our understanding but also provides theoretical guidance for optimizing multi-rotor drones across diverse environmental conditions. As drones emerge as potential game-changers in roles such as regional safety inspections and short-distance rapid transportation between cities, this research offers valuable insights aimed at enhancing the real-world performance and efficiency of hydrogen fuel cell-powered multi-rotor drones. The implications of this study extend beyond theoretical exploration, laying a foundation for future advancements in drone technology, especially in applications where endurance, payload capacity, and adaptability to varied environments are paramount.
Modeling and Analysis of the Hydrogen Production via Steam Reforming of Ethanol, Methanol, and Methane Fuels
Authors: Hariharan Deivanayagam , Chhatija Harish , Brown Jonathan , Gundlapally Santhosh
Published: April 2024

The global transition to alternative power sources, particularly fuel cells, hinges on the cost-effective production and distribution of hydrogen fuel. While green hydrogen produced through water electrolysis using renewable energy sources holds immense promise, it currently falls short of meeting the burgeoning demand for hydrogen. To address this challenge, alternative methods, such as steam reforming and partial oxidation of hydrocarbon fuels with integrated carbon capture, are poised to bridge the gap between supply and demand in the near to midterm. Steam reforming of methane is a well-established technology with a proven track record in the chemical industry, serving as a dependable source of hydrogen feedstock for decades. However, to meet the demand for efficient hydrogen storage, handling, and onboard reforming, researchers are increasingly exploring liquid hydrocarbon fuels at room temperature, such as methanol and ethanol. In this work, we have developed reformer models for ethanol, methanol, and methane within the GT-SUITE software, drawing on data from the existing body of research. We examine fuel conversion and hydrogen yield under varying conditions, including different feed temperatures, flow rates, and catalyst loadings. These reactor models hold the potential for seamless integration into system-level models, designed to investigate onboard fuel reforming, startup and shutdown procedures, carbon capture, and more.
Design and Optimization of a Centrifugal Compressor-Based Air Management System for HD Fuel Cell Applications
Authors: Peters Nathan , Pothuraju Subramanyam Sai , Bunce Mike , Taylor Alexander , Naik Pavan , Semmelroggen Jens , Nibler Simon
Published: April 2024

Fuel cell electric vehicles offer an attractive option for decarbonizing long-haul on-road transport. However, there are still several barriers to widespread adoption of hydrogen-fueled fuel cells for this application including system durability and total cost of ownership compared to traditional diesel engines. A primary contributor to fuel cell system costs and maintenance requirements is the air management system. It is common for heavy duty fuel cell electric vehicles to use light-duty automotive air management components which are ill-suited for the requirements of larger, long-haul vehicles. This study focuses on the development of a durable and efficient air management system for heavy duty vehicle applications as part of a cooperative research project funded by the Department of Energy’s Hydrogen and Fuel Cell Technologies Office1.

The proposed air management design incorporates a novel two stage filtration system, an innovative water-lubricated bearing and electrically-assisted variable turbine geometry turbocharger, charge air cooler, and humidifier. To achieve the ambitious Department of Energy project goals for efficiency and durability, a system-level optimization approach has been employed using a semi-empirical 1D model. Design optimization of the compressor and turbine wheel geometries yielded a large compressor wheel diameter and small trim to reduce mass flow capacity, resulting in a broad efficiency map and a relatively small turbine wheel diameter with non-radial inlet blade angle suitable for the low temperature exhaust. 1D simulations of the optimized system compared to a baseline e-compressor showed a >40% reduction in required e-motor power at steady-state conditions and a >30% reduction in e-motor energy consumption in a transient cycle.