Recent Submissions

  • A privacy-preserving approach to effectively utilize distributed data for malaria image detection

    Kareem, Amer; Liu, Haiming; Velisavljevic, Vladan; University of Bedfordshire; University of Southampton (MDPI, 2024-03-18)
    Malaria is one of the life-threatening disease caused by the parasite knows as Plasmodium falciparum affecting the human red blood cells. Therefore, it is an important to have an effective computer aided system in place for early detection and treatment. As the visual heterogeneity of the malaria dataset is highly complex and dynamic, therefore higher number of images are needed to train the machine learning (ML) models effectively. However, hospitals as well as medical institutions do not share the medical image data for collaboration due to general data protection regulation (GDPR) and data protection act (DPA). To overcome this collaborative challenge, our research utilised real-time medical image data using framework of federated learning (FL) framework. We have used the state of the art ML models that include the Resnet50 and densenet in a federated learning framework. We have experimented both models in different settings on malaria dataset constituting 27,560 publicly available images and our preliminary results showed that the densenet model performed better in accuracy (75%) in contrast to resnet50 (72%) while considering 8 clients, while the trend is observed common in 4 clients with the similar accuracy of 94% and 6 client showed that the densenet model performed quite well with the accuracy of 92% while resnet50 achieving only 72%. The federated learning framework enhances the accuracy due to it’s decentralised nature, continuous learning, effective communication among clients as well as the efficient local adaptation. The use of federated learning architecture among the distinct clients for ensuring the data privacy and following the GDPR is the contribution of this research work.
  • From augmentation to inpainting: improving Visual SLAM with signal enhancement techniques and GAN-based image inpainting

    Theodorou, Charalambos; Velisavljevic, Vladan; Dyo, Vladimir; Nonyelu, Fredi; University of Bedfordshire; Briteyellow Ltd; Royal Holloway (IEEE, 2024-03-07)
    This paper undertakes a comprehensive investigation that surpasses the conventional examination of signal enhancement techniques and their effects on visual Simultaneous Localization and Mapping (vSLAM) performance across diverse scenarios. Going beyond the conventional scope, the study extends its focus towards the seamless integration of signal enhancement techniques, aiming to achieve a substantial enhancement in the overall vSLAM performance. The research not only delves into the assessment of existing methods but also actively contributes to the field by proposing innovative denoising techniques that can play a pivotal role in refining the accuracy and reliability of vSLAM systems. This multifaceted approach encompasses a thorough exploration of the intricate relationships between signal enhancement, denoising strategies, their cumulative impact on the performance of vSLAM in real-world applications and the innovative use of Generative Adversarial Networks (GANs) for image inpainting. The GANs effectively fill in missing spaces following object detection and removal, presenting a novel state-of-the-art approach that significantly enhances overall accuracy and execution speed of vSLAM. This paper aims to contribute to the advancement of vSLAM algorithms in real-world scenarios, demonstrating improved accuracy, robustness, and computational efficiency through the amalgamation of signal enhancement and advanced denoising techniques.
  • Fault detection and monitoring for electric pump motors

    Velisavljevic, Vladan; Dyo, Vladimir; Newton, J.; Newton, B.; Sunal, Cem Ekin (2024-02-29)
    Patent file GB2402869.8 Outcome of Innvoate KTP project.
  • 3D study of the vibrational behavior of lithic flint blades

    Tayong-Boumda, Rostand; Fushimi, Tatsuki; Grøn, Ole; Boldreel, Lars Ole; ; University of Bedfordshire; University of Bristol; University of Tsukuba; University of Copenhagen (Elsevier, 2023-11-09)
    Stone Age sites are well known to often contain many lithic flint blades and flakes, which may provide important information about early European Stone Age cultures and their environment. Understanding the mechanical behaviour of lithic flint blades represents an important problem for scientists in general and archaeologists in particular. In this study, the structural behaviour of lithic flint blades is studied. Ten specimens with different geometric shapes (tilted, curved, with bumping surfaces) were studied and tested. Their natural frequencies, damping ratios, and mode shapes (that is how the specimen deforms under any external excitation) are estimated using two models: an analytical model that accounts for the specimen's curvature and a 3D Finite Element (FE) method. Advanced experimental methods, including ultrasound techniques, were used to measure the mechanical properties of the specimens. The experimental set-up was built around a laser vibrometer that measured the specimen's displacement. The model predictions were compared with the experimental data to validate their effectiveness. A good agreement is observed between the models and the real data. It is particularly observed that despite their complicated geometries, the specimens still follow a structured pattern in their dynamic response. The presented study supports the use of acoustic methods as an effective tool to characterize and detect submerged prehistoric materials. This work contributes to the dynamic characterization of submerged Stone Age materials.
  • Ultrasonic metrics for large-area rapid wrinkle detection, classification and quantification in composites

    Smith, Robert A.; Tayong-Boumda, Rostand; Nelson, Luke J.; Wilcox, Paul D.; University of Bristol; University of Bedfordshire (2022-12-31)
    Due to their high strength-to-weight ratio, composite materials are now in use in many high-stress applications, particularly where light weight is also a requirement. In these situations, the detrimental knock-down in mechanical strength due to an out-of-plane wrinkle defect can have serious consequences and is the reason for a requirement to rapidly detect and quantify any such wrinkles at manufacture. Unfortunately, these wrinkles do not perturb the ultrasound currently used for quality control at manufacture in a way that can be readily detected above coherent structural noise variations. This paper exploits the ply resonance that is a characteristic of multi-layer structures to generate two new metrics for both detection and quantification of out-of-plane wrinkles, due to their effect on the ply spacing. These can be measured at every three-dimensional location in a structure using the instantaneous frequency, which is the rate of change of phase in the pulse-echo ultrasonic response. The proposed two new metrics for detection and quantification of wrinkles are: Mean Spacing and Spacing Difference. Use of an analytical model to predict the ultrasonic response of the structure has allowed an understanding of how these metrics will be affected by various wrinkle types and how they can not only detect but also classify and quantify the wrinkle extent and severity. Three main types of wrinkles are considered: classic wrinkles near the mid-plane of a structure, back-surface wrinkles forming from a resin bulge near the back of a structure, and folded wrinkles where several plies can be folded over completely in the bulk of the structure. Both simulations and experimental results demonstrate the effectiveness of these metrics on various types of structure including carbon-fibre and glass-fibre composites with a range of ply thicknesses and wrinkle types.
  • On the design and structural study of a rear swing arm for an electric bike

    Tayong-Boumda, Rostand; Henderson, Dave; Murray, Alex; University of Bedfordshire; Flit Bike Ltd (Elsevier, 2023-10-18)
    As electric bikes continue to grow in popularity, it is important to ensure that they are equipped with well-designed components. One such component is the rear swing arm (RSA). This study deals with the design and structural analysis of an RSA used for electric bikes. This RSA is composed of two swing arms (one on each side of the bikes), a yoke, a suspension block, and bolts or screws. First, an analytical approach was developed to calculate the initial values for the width and shape of the swing arm. Next, experimental data were used to analyze the response of the RSA and determine the final profile for the swing arms and yoke structure. Finally, the finite element approach was implemented to assess the stress, displacement, and fatigue responses of the RSA when subjected to realistic excitations and conditions. The initial results depicted the following characteristics for the RSA: C-channel profile, 43 mm height, and 2 mm wall thickness. These results implied that the maximum shear force would occur in a region representing approximately 15.5% of the total length of the RSA. Further analysis and calculations showed that this region would decrease to approximately 2.85% of the total length of the RSA. For the final design, the mechanical performance of the RSA was observed to remain acceptable despite the relatively high Von Mises stress values around these singularities. This study assumed the use of 7075 T651 aluminum alloy as the primary material for the RSA.
  • Aquaculture 4.0: hybrid neural network multivariate water quality parameters forecasting model

    Eze, Elias Chinedum; Kirby, Sam; Attridge, John; Ajmal, Tahmina; University of East London; University of Bedfordshire; Chelsea Technologies Ltd (Springer Nature, 2023-09-26)
    This study examined the efficiency of hybrid deep neural network and multivariate water quality forecasting model in aquaculture ecosystem. Accurate forecasting of critical water quality parameters can allow for timely identification of possible problem areas and enable decision-makers to take pre-emptive remedial actions that can significantly improve water quality management in aquaculture industry. A novel hybrid deep learning neural network multivariate water quality parameters forecasting model is developed with the aid of ensemble empirical mode decomposition (EEMD) method, deep learning long-short term memory (LSTM) neural network (NN), and multivariate linear regression (MLR) method. The presented water quality forecasting model (shortened as EEMD-MLR-LSTM NN model) is developed using multivariate time-series water quality sensor data collected from Loch Duart company, a Salmon offshore aquaculture farm based around Scourie, northwest Scotland. The performance of the novel hybrid water quality forecasting model is validated by comparing the forecast result with measured water quality parameters data and the real Phytoplankton data count from the aquaculture farm. The forecast accuracy of the results suggests that the novel hybrid water quality forecasting model can be used as a valuable support tool for water quality management in aquaculture industries.
  • Insights into the spray impingement process from a gasoline direct injection fuel system fuelled with gasoline and ethanol

    Li, Xiang; Zhang, Xuewen; Ni, Peiyong; Weerasinghe, Rohitha; Pei, Yiqiang; Peng, Zhijun; Nantong University; Tianjin University; University of Bedfordshire; University of Lincoln (Elsevier, 2023-06-27)
    Particulate Matter (PM) emissions have a negative impact on both climate change and human health. To control PM emissions emitted by vehicles with the Gasoline Direct Injection (GDI) fuel system, increasing fuel injection pressure is being developed as a practical approach. In this paper, an experimental and numerical study was presented to thoroughly explore the entire development process of gasoline and ethanol impingement spray from a GDI injector under injection pressure of 10 MPa and 50 MPa. The results demonstrate that more droplets are predicted to distribute in the splash region with the increase of injection pressure (𝑃𝐼 ) from 10 MPa to 50 MPa, which helps improve air-fuel mixing quality and reduce PM emissions. The splash probability of gasoline droplets is about two percent higher than ethanol. By increasing 𝑃𝐼 from 10 MPa to 50 MPa, droplets with higher absolute normal velocity would promote the growth of impingement spray. The probability curves of droplet diameter are more concentrated in the smaller size range. Besides, the probability of relatively large droplets of gasoline is slightly lower than that of ethanol. Regarding the fuel film distribution, more folds and bulges can be seen at the boundary of fuel film with the 𝑃𝐼 increase to 50 MPa. Meantime, the film distribution becomes more scattered, which would benefit the homogeneity of air-fuel mixture. The film distribution area and boundary irregularity of gasoline are greater than those of ethanol, further promoting a homogeneous air-fuel mixture.
  • Quantitative analysis of water injection mass and timing effects on oxy-fuel combustion characteristics in a GDI engine fuelled with E10

    Chen H, Hao; Wang, Chenxi; Li, Xiang; Li, Yongzhi; Zhang, Miao; Peng, Zhijun; Pei, Yiqiang; Ma, Zhihao; Zhang, Xuewen; Ni, Peiyong; et al. (MDPI, 2023-06-29)
    The climate change issue has become a growing concern due to the increasing greenhouse gas emissions. To achieve carbon neutrality for mitigating the climate problem, the oxy-fuel combustion (OFC) technique on internal combustion engines (ICEs) has attracted much attention. Furthermore, the water injection (WI) strategy was proven effective in improving the combustion process and thermal efficiency in engines under OFC mode. However, WI strategy effects on gasoline direct injection (GDI) engines fuelled with gasoline–alcohol blends have not been reported. This study quantitatively analysed WI mass and timing effects on oxy-fuel combustion performance from a GDI engine fuelled with E10 (10% ethanol and 90% gasoline in mass) by simulation. The results show that equivalent brake-specific fuel consumption (BSFCE) shows a monotonically decreasing trend with the increase in the water–fuel mass ratio (Rwf ) from 0 to 0.2. However, further increasing Rwf would cause a deterioration in BSFCE due to the enhanced cooling effects of water vaporisation. Moreover, an appropriate water injection timing (tWI ) could be explored for improving OFC performance, especially for large Rwf conditions. The difference in BSFCE between tWI = 􀀀100CA and tWI = 􀀀60CA can be up to around 6.3 g/kWh by increasing Rwf to 0.6.
  • 3D numerical analysis of the structural behaviour of a carbon fibre reinforced polymer drive shaft

    Samuel, Mosopefoluwa; Tayong-Boumda, Rostand; University of Bedfordshire (Elsevier, 2023-04-28)
    Due to their high strength and favourable mechanical behaviour, metals are used in a variety of applications within the automotive industry, including drive shafts. However, the use of metallic drive shafts in the automotive sector presents some disadvantages such as high inertial masses. This work investigates the mechanical benefits of using Carbon Fibre Reinforced Polymers (CFRP) for manufacturing drive shafts. A Formula Student car was used as a model for the present work design for the drive shaft. Drive shafts made of Steel AISI 4340, Aluminium, and CFRP are investigated when subjected to mechanical excitations. Simulation includes the use of Comsol Multiphysics software. The CFRP drive shaft was modelled using the layered material feature. Various stacking sequences are tested. Results show that [90°/0°/-45°/+45°] sequence presents the best mechanical behaviour. Analytical and numerical calculations for the natural frequencies are performed and compared. CFRP drive shaft is observed to give the highest fundamental natural frequency when compared to the metallic counterparts. Fatigue analysis are also studied and revealed that the drive shafts can sustain the applied load for its expected fatigue life, with the CFRP drive shaft having the highest fatigue usage factor. Critical buckling analysis showed that the drive shaft made of steel has the highest critical buckling torque. However, drive shafts made of carbon fibre reinforced polymer was found to be 40.7% lighter than the aluminium tube and 79.6% lighter than the steel tube.
  • Effect of intake charge temperature on oxy-fuel combustion in an HCCI diesel engine under different carbon dioxide dilutions

    Mobasheri, Raouf; Aitouche, Abdel; Mumputu, J.B.; Li, Xiang; Peng, Zhijun; University Lille; Junia, Smart Systems and Energies; University of Bedfordshire; University of Lincoln (American Society of Mechanical Engineers (ASME), 2022-10-20)
    Carbon dioxide is one of the leading contributors to global warming. Oxy-fuel combustion (OFC) integrated with carbon capture and storage (CCS) technology is an efficient way to reduce carbon dioxide emissions. In OFC, pure oxygen (O2) is used instead of air to react with hydrocarbon fuel. Consequently, the products of combustion mainly include carbon dioxide (CO2) and water vapor (H2O) under lean conditions. Meanwhile, due to the absence of N2 in the intake charge, nitrogen-related emissions such as NOx are greatly removed from the exhaust gases. In the present study, the effect of intake charge temperature on OFC has been investigated in a diesel engine under the homogeneous charge compression ignition (HCCI) mode. In order to control combustion temperature and avoid overheating problems caused by oxygen in OFC, a portion of the exhaust CO2 was added to the O2. For this purpose, different CO2 dilutions ranging from 79-85% have been employed. It has been found that OFC can significantly reduce CO and particulate matter (PM) emissions while eliminating NOx emissions. With a higher intake charge temperature, combustion occurs earlier with shorter main stages, reducing the indicated mean effective pressure (IMEP) and increasing the indicated specific fuel consumption (ISFC), whereas, with a lower intake charge temperature, combustion stability deteriorates leading to incomplete OFC. By raising the intake charge temperature from 140 C to 220 C and applying 21% O2 and 79% CO2 v/v, the indicated thermal efficiency (ITE) is reduced from 34.6% to 29.2% while ISFC is increased from 0.24 to 0.285 Kg/kWh.
  • Comparative investigation on macroscopic and microscopic characteristics of impingement spray of gasoline and ethanol from a GDI injector under injection pressure up to 50 MPa

    Li, Xiang; Li, Dayou; Dimitriou, Pavlos; Ajmal, Tahmina; Aitouche, Abdel; Mobasheri, Raouf; Rybdylova, Oyuna; Pei, Yiqiang; Peng, Zhijun; University of Bedfordshire; et al. (Elsevier Ltd, 2023-01-09)
    Particulate Matter (PM) emissions from passenger vehicles have attracted considerable interest over the last decade. In order to reduce PM emissions, improving maximum injection pressure has been a developing trend for new generation GDI engines. However, comparing gasoline and ethanol impingement spray characteristics from a GDI injector under high injection pressure is still unclear. In this paper, a comparative investigation on both the macroscopic and microscopic characteristics of impingement spray from a GDI injector fuelled with gasoline and ethanol was performed under injection pressure up to 50 MPa, providing new findings to promote a more homogeneous air–fuel mixture and reduce PM emissions. The experimental results show that under the same PI (injection pressure), rebound height of gasoline impingement spray is a bit higher than ethanol. AS (spray area) of gasoline is slightly higher than ethanol under PI=10MPa. However, under PI=30MPa and PI=50MPa, AS of gasoline is gradually exceeded by that of ethanol as time progresses. By increasing PI to 50 MPa, the difference in DN (diffusion distance of the near side) between gasoline and ethanol is greatly reduced, meantime DF (diffusion distance of the far side) becomes weaker than ethanol. For both gasoline and ethanol, with the increase PI from 10 MPa to 50 MPa, VN (average normal component of droplet velocity) and VT (average tangential component of droplet velocity) of incident droplets increase by around 1 m/s. Meantime, there is a slight decrease in the absolute value of VN and VT of reflected droplets. DSMD (Sauter mean diameter of droplets) presents a significant decreasing trend with the increase of PI. Besides, a smaller DSMD can be seen for the gasoline impingement spray compared to ethanol under the same PI.
  • Acoustic detection and mapping of submerged stone age sites with knapped flint

    Grøn, Ole; Boldreel, Lars Ole; Hermand; Tayong-Boumda, Rostand; Dell’Anno, Antonio; Cvikel, Deborah; Galili, Ehud; Madsen, Bo; Nørmark, Egon (Springer, 2022-01-25)
    This chapter presents a non-destructive survey technique under development: acoustic detection and mapping of submerged Stone Age sites. While it has been experimentally established that reasonable amounts of man-knapped flint pieces can be excited by and respond to specific acoustic signal through meters of sea floor sediment, it is not yet known how small assemblages of knapped flint pieces one can obtain a response from and how deep in the sea floor this will be possible. It also remains to check experimentally if other knapped materials than flint (obsidian, quartzite, basalt, etc.) respond in a similar way given that some of their basic characteristics potentially differ from those registered for flint. This technique will facilitate a much more effective and cheap detection and mapping of submerged Stone Age sites with knapped lithics compared to the techniques available at present. Especially the deep sites down to the approximately 120 m deep coastlines of the glaciations, which are very difficult to localize today, represent an important research potential. In general, the highly productive coast lines must be assumed to have played an important economic role of human society from the Palaeolithic onwards, which means that we miss an important part of the picture of the human cultural development. In spite of the promising perspective of methodological improvement, one must be aware of the limitations of the acoustic method. It will not be able to map Stone Age sites lacking knapped lithics. This chapter presents and discusses the method’s basic technological principles and the experimental results obtained so far, elucidating its potential.
  • On some problems related to the fabrication of a metallic micro-perforated panel for noise control applications

    Tayong-Boumda, Rostand (International Journal of Engineering and Innovative Technology, 2014-05-31)
    Micro-Perforated Panels (MPP) are widely used nowadays as a noise control solution. Such materials present many interesting advantages and are considered to be among the latest innovative sound absorbing materials. For these reasons, many models are proposed in the literature to predict their acoustic behavior. However, the accuracy of these models depends on the assumptions under which they are derived and more often on the MPP samples built for their validation. Rigorous attention is therefore needed to insure convenient fabrication of samples for the MPP. This paper investigates some important problems related to the fabrication of metallic MPP samples used for noise control applications. Particular emphasis is given to the hole drilling effects. It is shown for instance that the presence of shavings inside the perforation may alter or change the MPP acoustic response. This work supports the design of optimum MPP for noise control applications such as duct mufflers, room acoustics, and transport domain and environment noise abatement.
  • Progress in non-destructive 3D characterization and modelling of aerospace composites

    Smith, Robert A.; Nelson, L.; Tayong-Boumda, Rostand; Xie, N.; Fraij, C.; Wilcox, P.; Hallett, S. (American Society for Nondestructive Testing, 2015-05-06)
    The route to lighter composite aerostructures requires advanced 3D non-destructive characterization methods to provide confidence that the as-built structures conform to the design expectations. Whilst X-ray Micro-CT imaging is an excellent non-destructive testing (NDT) method for 3D characterization, it can rarely be applied in production. In its place, ultrasound is an ideal vehicle for exploring the detailed local response of a composite structure, providing data that can be inverted to give 3D fiber direction, ply spacing, fiber volume fraction and 3D porosity distribution. The first material property that must be determined to enable full characterization and materials modelling of as-manufactured composite components is the vector field representing the fiber direction at every point. Inversion methods have been developed for converting 3D NDT data sets into 3D profiles of material properties. A study of ultrasonic analytic-signal propagation in composites has resulted in a novel method for tracking plies and ply drops, in ultrasonic full-waveform data sets. This paper presents methods for tracking the 3D orientation of fiber tows in the plies throughout a laminated composite structure and examples of finite-element models built directly from this NDT information.
  • Visual SLAM for dynamic environments based on object detection and optical flow for dynamic object removal

    Theodorou, Charalambos; Velisavljevic, Vladan; Dyo, Vladimir; University of Bedfordshire; Briteyellow Ltd (MDPI, 2022-10-05)
    In dynamic indoor environments and for a Visual Simultaneous Localization and Mapping (vSLAM) system to operate, moving objects should be considered because they could affect the system’s visual odometer stability and it is position estimation accuracy. vSLAM can use feature points or a sequence of images as it is only source of input in order to perform localization while simultaneously creating a map of the environment. A vSLAM system based on ORB-SLAM3 and on YOLOR was proposed in this paper. The newly proposed system in combination with an object detection model (YOLOX) applied on extracted feature points is capable of achieving 2-4% better accuracy as compared to VPS-SLAM and DS-SLAM. Static feature points such as signs and benches were used to calculate the camera position and dynamic moving objects were eliminated by using the tracking thread. A specific custom personal dataset that includes indoor and outdoor RGB-D pictures of train stations including dynamic objects and high density of people, ground truth data, sequence data, video recording with the train stations and X, Y, Z data was used to validate and evaluate the proposed method. The results show that ORB-SLAM3 with YOLOR as object detection achieves 89.54% of accuracy in dynamic indoor environments compared to previous systems such as VPS-SLAM.
  • Visual SLAM algorithms and their application for AR, mapping, localization and wayfinding

    Theodorou, Charalambos; Velisavljevic, Vladan; Dyo, Vladimir; Nonyelu, Fredi; ; University of Bedfordshire; Briteyellow (Elsevier, 2022-08-03)
    Visual simultaneous localization and mapping (vSLAM) algorithms use device camera to estimate agent’s position and reconstruct structures in an unknown environment. As an essential part of augmented reality (AR) experience, vSLAM enhances the real-world environment through the addition of virtual objects, based on localization (location) and environment structure (mapping). From both technical and historical perspectives, this paper categorizes and summarizes some of the most recent visual SLAM algorithms proposed in research communities, while also discussing their applications in augmented reality, mapping, navigation, and localization.
  • Review of machine learning based fault detection for centrifugal pump induction motors

    Sunal, Cem Ekin; Dyo, Vladimir; Velisavljevic, Vladan; ; University of Bedfordshire (IEEE, 2022-07-01)
    Centrifugal pumps are an integral part of many industrial processes and are used extensively in water supply, sewage, heating and cooling systems. While there are several review papers on machine learning-based fault diagnosis on induction motors, its application to centrifugal pumps has received relatively little attention. This work attempts to summarize and review recent research and development in machine learning-based pump condition monitoring and fault diagnosis. The paper starts with a brief explanation of pump operation including common pump faults and the main principles of the motor current signature analysis (MCSA) method. This is followed by a detailed explanation of various machine learning-based methods including the types of detected faults, experimental details and reported accuracies. The performances of different approaches are then presented systematically in a unified table. Finally, the authors discuss practical aspects and challenges related to data collection, storage and real-world implementation.
  • A review of fuel cell technology for commercial vehicle applications

    Jokela, Tommi; Kim, Bill; Gao, Bo; Wellers, Matthias; Peng, Zhijun (Inderscience, 2021-12-31)
    The demanding energy storage requirements of many commercial vehicle applications are extremely difficult to meet for pure battery electric vehicles (BEVs) due to the limited energy density of batteries. Fuel cells appear to be the only viable propulsion technology that is able to meet commercial vehicle powertrain requirements with zero local greenhouse gas emissions. Since almost all fuel cell vehicles (FCVs) contain a high voltage battery, some additional complexity is introduced since the hybrid energy storage system must be sized and controlled appropriately. An understanding of the strengths and weaknesses of each system is therefore essential in FCV design. The aim of this technology review is to provide an overview of fuel cell technologies in commercial vehicle applications including assessments of alternative powertrain and fuel cell types, advantages and disadvantages of fuel cell and battery systems and the implications of these on the powertrain sizing as well as control considerations of FCVs.
  • Exploring the potential benefits of Ethanol Direct Injection (EDI) timing and pressure on particulate emission characteristics in a Dual-Fuel Spark Ignition (DFSI) engine

    Li, Xiang; Li, Dayou; Liu, Jingyin; Ajmal, Tahmina; Aitouche, Abdel; Mobasheri, Raouf; Rybdylova, Oyuna; Pei, Yiqiang; Peng, Zhijun; ; et al. (Elsevier, 2022-04-26)
    Nowadays, particulate matter emitted by vehicles severely impacts environmental quality and human health. In this paper, the potential benefits of Ethanol Direct Injection (EDI) timing and pressure on particulate emission characteristics in a Dual-Fuel Spark Ignition (DFSI) engine were initially and systematically explored. The experimental results illustrate that by delaying EDI timing from -340 ºCA to -300 ºCA, there is a significant benefit in both particulate number and mass concentration. Furthermore, the size distribution curve of particulate number changes from bimodal to unimodal, meantime size distribution curves of particulate mass consistently concentrate on the accumulation mode. By increasing EDI pressure from 5.5 MPa to 18 MPa, the droplet size of ethanol spray can be effectively reduced. The benefit of increasing EDI pressure is more apparent in reducing particulate number is than particulate mass. The concentration of number and mass for total particulates have a reduction of 51.15% and 22.64%, respectively. In summary, it was demonstrated that an appropriate EDI timing or high EDI pressure could be a practical and efficient way to reduce particulate emissions in a DFSI engine.

View more