D. Komnos, Jamil Nur, A. Tansini, M. Ktistakis, Jaime Suarez, J. Krause, G. Fontaras
In 2023, the European Union set more ambitious targets for reducing greenhouse gas emissions from passenger cars: the new fleet-wide average targets became 93.6 g/km for 2025, 49.5 g/km in 2030, going to 0 in 2035. One year away from the 2025 target, this study evaluates what contribution to CO2 reduction was achieved from new conventional vehicles and how to interpret forecasts for future efficiency gains. The European Commission’s vehicle efficiency cost-curves suggest that optimal technology adoption can guarantee up to 50% CO2 reduction by 2025 for conventional vehicles. Official registration data between 2013 and 2022, however, reveal only an average 14% increase in fuel efficiency in standard combustion vehicles, although reaching almost 23% for standard hybrids. The smallest gap between certified emissions and best-case scenarios is of 14 g/km, suggesting that some manufacturers’ declared values are approaching the optimum. Yet, the majority of vehicles do not appear to fully exploit the potential of the technological boundary. In 2022, gasoline vehicles’ mass, engine size and power alone explained 67% of CO2 variation, an increase of almost 20% from 2014. For diesels, wheelbase – a proxy for vehicle size – increased in explanatory power from 5% to 18%, to the detriment of engine size, which lost 6% variance points. Vehicle mass, power, capacity and size explain well the gap between current CO2 emissions and optimal targets and may add or subtract efficiency from other energy-saving technologies. These patterns should be read in combination with the evolution of the different vehicle segments’ market shares, which saw a 40% increase in Sport Utility Vehicles (SUVs), and a sharp decrease in diesel registrations. Finally, this paper offers a statistical analysis first attempt at disentangling over time changes in vehicle characteristics from actual improvements in vehicle efficiency.
{"title":"The Evolution of Conventional Vehicles’ Efficiency for Meeting Carbon Neutrality Ambition","authors":"D. Komnos, Jamil Nur, A. Tansini, M. Ktistakis, Jaime Suarez, J. Krause, G. Fontaras","doi":"10.4271/2024-37-0034","DOIUrl":"https://doi.org/10.4271/2024-37-0034","url":null,"abstract":"In 2023, the European Union set more ambitious targets for reducing greenhouse gas emissions from passenger cars: the new fleet-wide average targets became 93.6 g/km for 2025, 49.5 g/km in 2030, going to 0 in 2035. One year away from the 2025 target, this study evaluates what contribution to CO2 reduction was achieved from new conventional vehicles and how to interpret forecasts for future efficiency gains. The European Commission’s vehicle efficiency cost-curves suggest that optimal technology adoption can guarantee up to 50% CO2 reduction by 2025 for conventional vehicles. Official registration data between 2013 and 2022, however, reveal only an average 14% increase in fuel efficiency in standard combustion vehicles, although reaching almost 23% for standard hybrids. The smallest gap between certified emissions and best-case scenarios is of 14 g/km, suggesting that some manufacturers’ declared values are approaching the optimum. Yet, the majority of vehicles do not appear to fully exploit the potential of the technological boundary. In 2022, gasoline vehicles’ mass, engine size and power alone explained 67% of CO2 variation, an increase of almost 20% from 2014. For diesels, wheelbase – a proxy for vehicle size – increased in explanatory power from 5% to 18%, to the detriment of engine size, which lost 6% variance points. Vehicle mass, power, capacity and size explain well the gap between current CO2 emissions and optimal targets and may add or subtract efficiency from other energy-saving technologies. These patterns should be read in combination with the evolution of the different vehicle segments’ market shares, which saw a 40% increase in Sport Utility Vehicles (SUVs), and a sharp decrease in diesel registrations. Finally, this paper offers a statistical analysis first attempt at disentangling over time changes in vehicle characteristics from actual improvements in vehicle efficiency.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"130 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141351435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andre Paiva, Julien Verhaegen, G. Lielens, Benoit Van den Nieuwenhof
As vibration and noise regulations become more stringent, numerical models need to incorporate more detailed damping treatments. Commercial frameworks, such as Nastran and Actran, allow the representation of trim components as frequency-dependent reduced impedance matrices (RIM) in direct frequency response (DFR) analysis of fully trimmed models.The RIM is versatile enough to couple the trims to modal-based or physical components. If physical, the trim components are reduced on the physical coupling degrees of freedom (DOFs) for each connected interface. If modal, the RIMs are projected on the eigenmodes of the connected component. While a model size reduction is achieved compared to the original model, most numerical models possess an extensive number of interfaces DOFs, either modal or physical, resulting in large, dense RIMs that demand substantial memory and disk storage. Thus, the approach faces challenges related to storage capacities and efficiency, because of the demanding computational input/output (I/O) operations involved.This paper introduces a new robust and efficient methodology. It aims to further compress these RIMs when dealing with modal components. Instead of performing a conventional modal projection, the method reduces the global modes onto the coupling surfaces of each component to their most significant contributions. The paper demonstrates, on an industrial fully trimmed car body model, that if the truncation process eliminates low-effect contributions sufficiently, the coupling is adequately represented, resulting in a significant reduction in disk storage with minimal loss of accuracy. As an additional benefit, the computational time is reduced due to the I/O handling of much smaller matrices.
{"title":"Frequency Response Analysis of Fully Trimmed Models Using Compressed Reduced Impedance Matrix Methodology","authors":"Andre Paiva, Julien Verhaegen, G. Lielens, Benoit Van den Nieuwenhof","doi":"10.4271/2024-01-2947","DOIUrl":"https://doi.org/10.4271/2024-01-2947","url":null,"abstract":"As vibration and noise regulations become more stringent, numerical models need to incorporate more detailed damping treatments. Commercial frameworks, such as Nastran and Actran, allow the representation of trim components as frequency-dependent reduced impedance matrices (RIM) in direct frequency response (DFR) analysis of fully trimmed models.The RIM is versatile enough to couple the trims to modal-based or physical components. If physical, the trim components are reduced on the physical coupling degrees of freedom (DOFs) for each connected interface. If modal, the RIMs are projected on the eigenmodes of the connected component. While a model size reduction is achieved compared to the original model, most numerical models possess an extensive number of interfaces DOFs, either modal or physical, resulting in large, dense RIMs that demand substantial memory and disk storage. Thus, the approach faces challenges related to storage capacities and efficiency, because of the demanding computational input/output (I/O) operations involved.This paper introduces a new robust and efficient methodology. It aims to further compress these RIMs when dealing with modal components. Instead of performing a conventional modal projection, the method reduces the global modes onto the coupling surfaces of each component to their most significant contributions. The paper demonstrates, on an industrial fully trimmed car body model, that if the truncation process eliminates low-effect contributions sufficiently, the coupling is adequately represented, resulting in a significant reduction in disk storage with minimal loss of accuracy. As an additional benefit, the computational time is reduced due to the I/O handling of much smaller matrices.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"102 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141352491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Markus Wagner, G. Baumann, Lukas Lindbichler, Michael Klanner, Florian Feist
The production of Electric Vehicles (EVs) has a significant environmental impact, with up to 50 % of their lifetime greenhouse gas potential attributed to manufacturing processes. The use of sustainable materials in EV design is therefore crucial for reducing their overall carbon footprint. Wood laminates have emerged as a promising alternative due to their renewable nature. Additionally, wood-based materials offer unique damping properties that can contribute to improved Noise, Vibration, and Harshness (NVH) characteristics. Compared to conventional materials such as aluminium, wooden structures exhibit significantly higher damping properties.In this study, the potential of lightweight wood composites, specifically steel-wood hybrid structures, is investigated as a potential composite material for battery housings for electric vehicles. Experiments have been performed in order to determine the modal parameters, such as natural frequencies and damping ratios. These parameters where used to validate a free-free steel-wood hybrid beam simulation model. The numerical model was subsequently used to analyse the effect of the wood–steel adhesive on the natural frequencies and to compare a steel-wood hybrid battery housing to a aluminium based battery housing. The presented results in conjunction with literature data demonstrate that steel-wood hybrid structures can provide attractive stiffness properties at low weights while utilizing the excellent damping properties inherent in plywood. These properties can contribute to an improved noise and vibration behaviour, which could improve passenger comfort while reducing the life cycle greenhouse gas potential of the structural battery pack components by up to 50 %. The utilization of steel-wood hybrid structures within the battery pack of an EV may also contribute to a reduction in vibration-induced cell degradation, attributed to the higher damping characteristics inherent in these composite materials.This research contributes to the field of sustainable EV design by exploring the advantages of wood composites in the context of NVH optimization. The utilization of steel-wood hybrid structures represents a novel approach to exploit the unique properties of both materials, combining stiffness and damping characteristics. This study offers a pathway towards reducing the environmental impact of EV production while improving the NVH performance of electric vehicles, by incorporating sustainable materials like wood laminates into battery pack design.
{"title":"Comparing the NVH Behaviour of an Innovative Steel-Wood Hybrid Battery Housing Design to an All Aluminium Design","authors":"Markus Wagner, G. Baumann, Lukas Lindbichler, Michael Klanner, Florian Feist","doi":"10.4271/2024-01-2949","DOIUrl":"https://doi.org/10.4271/2024-01-2949","url":null,"abstract":"The production of Electric Vehicles (EVs) has a significant environmental impact, with up to 50 % of their lifetime greenhouse gas potential attributed to manufacturing processes. The use of sustainable materials in EV design is therefore crucial for reducing their overall carbon footprint. Wood laminates have emerged as a promising alternative due to their renewable nature. Additionally, wood-based materials offer unique damping properties that can contribute to improved Noise, Vibration, and Harshness (NVH) characteristics. Compared to conventional materials such as aluminium, wooden structures exhibit significantly higher damping properties.In this study, the potential of lightweight wood composites, specifically steel-wood hybrid structures, is investigated as a potential composite material for battery housings for electric vehicles. Experiments have been performed in order to determine the modal parameters, such as natural frequencies and damping ratios. These parameters where used to validate a free-free steel-wood hybrid beam simulation model. The numerical model was subsequently used to analyse the effect of the wood–steel adhesive on the natural frequencies and to compare a steel-wood hybrid battery housing to a aluminium based battery housing. The presented results in conjunction with literature data demonstrate that steel-wood hybrid structures can provide attractive stiffness properties at low weights while utilizing the excellent damping properties inherent in plywood. These properties can contribute to an improved noise and vibration behaviour, which could improve passenger comfort while reducing the life cycle greenhouse gas potential of the structural battery pack components by up to 50 %. The utilization of steel-wood hybrid structures within the battery pack of an EV may also contribute to a reduction in vibration-induced cell degradation, attributed to the higher damping characteristics inherent in these composite materials.This research contributes to the field of sustainable EV design by exploring the advantages of wood composites in the context of NVH optimization. The utilization of steel-wood hybrid structures represents a novel approach to exploit the unique properties of both materials, combining stiffness and damping characteristics. This study offers a pathway towards reducing the environmental impact of EV production while improving the NVH performance of electric vehicles, by incorporating sustainable materials like wood laminates into battery pack design.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"41 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141353187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The axle system is a major contributor for road induced vehicle interior noise. However, it is challenging to characterize the NVH performance of the axle system because it is coupled with both the tire/wheel and the body structure. In this article, we introduce a global approach to control the NVH performance of the axle system. The force transmissibility based on the blocked force concept was defined as the indicator of NVH performance of the axle system. A hybrid method combining test and simulation was developed to assess the intrinsic NVH performance of the axle system.The force transmissibility of the axle system is the blocked force generated by the axle system at the body mounting points with a unit of input force on the wheel. It can be simulated easily by FEM with rigid boundary conditions. However, measuring the blocked forces of the axle system is much more complex because it requires very stiff boundary conditions, which are difficult to realize on a realistic test rig. Our approach involves measuring the forces at the train-body interfaces on a standard test bench with realistic boundary conditions and simulating the interface forces with models that include not only the axle parts but also the rig and mounting parts. The simulation results can be compared directly with those of measurement, making it possible to recalibrate the simulation models. Once the model of the axle system is recalibrated, it can be used to simulate the blocked forces by setting infinitely rigid boundary conditions. This hybrid method allows obtaining the blocked forces from the axle system using a standard test rig without the need to build expensive new rigs.Using this method, different axle systems can be measured and NVH performance compared. In general, the axle system has worse NVH behavior in the transverse direction than in the vertical and longitudinal directions. Consequently, to improve the NVH performance of the axle system, the priority is to treat the weakness and make improvements in the transverse direction. The definition of the force transmissibility of the axle system, together with the hybrid characterization method, allows us to control the axle NVH performance more efficiently and carry out the necessary improvements in the design at the early stage of vehicle development.
{"title":"A Hybrid Method for Characterization and Improvement of NVH Performance of Axle System","authors":"Shanjin Wang, Constantin Gagiu","doi":"10.4271/2024-01-2950","DOIUrl":"https://doi.org/10.4271/2024-01-2950","url":null,"abstract":"The axle system is a major contributor for road induced vehicle interior noise. However, it is challenging to characterize the NVH performance of the axle system because it is coupled with both the tire/wheel and the body structure. In this article, we introduce a global approach to control the NVH performance of the axle system. The force transmissibility based on the blocked force concept was defined as the indicator of NVH performance of the axle system. A hybrid method combining test and simulation was developed to assess the intrinsic NVH performance of the axle system.The force transmissibility of the axle system is the blocked force generated by the axle system at the body mounting points with a unit of input force on the wheel. It can be simulated easily by FEM with rigid boundary conditions. However, measuring the blocked forces of the axle system is much more complex because it requires very stiff boundary conditions, which are difficult to realize on a realistic test rig. Our approach involves measuring the forces at the train-body interfaces on a standard test bench with realistic boundary conditions and simulating the interface forces with models that include not only the axle parts but also the rig and mounting parts. The simulation results can be compared directly with those of measurement, making it possible to recalibrate the simulation models. Once the model of the axle system is recalibrated, it can be used to simulate the blocked forces by setting infinitely rigid boundary conditions. This hybrid method allows obtaining the blocked forces from the axle system using a standard test rig without the need to build expensive new rigs.Using this method, different axle systems can be measured and NVH performance compared. In general, the axle system has worse NVH behavior in the transverse direction than in the vertical and longitudinal directions. Consequently, to improve the NVH performance of the axle system, the priority is to treat the weakness and make improvements in the transverse direction. The definition of the force transmissibility of the axle system, together with the hybrid characterization method, allows us to control the axle NVH performance more efficiently and carry out the necessary improvements in the design at the early stage of vehicle development.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"4 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141353965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
When dealing with the structural behavior of a car body, analyzing the dynamic distortion in all body closure openings in a complete vehicle, provides a better understanding of the body characteristics compared to traditional static load cases such as static torsional body stiffness. This is particularly relevant for non-traditional vehicle layouts and electric vehicle architectures where mass distribution and in particular battery mass and stiffness play a completely different effect with respect to the internal combustion engine vehicles.A methodology typically adopted to measure the body response, e.g. when driving a vehicle on a rough pavé road, is the so-called Multi Stethoscope (MSS). The MSS is measuring the distortion in each body closure opening in two diagonals. During the virtual development, the distortion is described by the relative displacement in diagonal direction in time domain using a modal transient analysis. The results are shown as Opening Distortion Fingerprint ODF and used as assessment criteria within Solidity and Perceived Quality.By applying the Principal Component Analysis (PCA) on the time history of the distortion, a Dominant Distortion Pattern (DDP) can be identified. The DDP means that, for a given pavé time history, more than 50 % of the body deformation states are similar to each other. This paper presents a deeper analysis about the forces which are associated with this Dominant Distortion Pattern (DDP). The new aspect of this analysis is that all forces (54 in total) between the wheel suspension and the trimmed body are considered. Based on the results of this force analysis, a new procedure for creating an Equivalent Static Load (ESL) was developed. Finally, by automating this creation procedure it is shown how the new ESL can be integrated in the virtual vehicle development.
{"title":"A New Equivalent Static Load (ESL) Creation Procedure for Complete Vehicle","authors":"Jens Weber, Faria Ricardo Luiz Felipe, Jesper Bäcklund, M. Vignati, Federico Cheli","doi":"10.4271/2024-01-2944","DOIUrl":"https://doi.org/10.4271/2024-01-2944","url":null,"abstract":"When dealing with the structural behavior of a car body, analyzing the dynamic distortion in all body closure openings in a complete vehicle, provides a better understanding of the body characteristics compared to traditional static load cases such as static torsional body stiffness. This is particularly relevant for non-traditional vehicle layouts and electric vehicle architectures where mass distribution and in particular battery mass and stiffness play a completely different effect with respect to the internal combustion engine vehicles.A methodology typically adopted to measure the body response, e.g. when driving a vehicle on a rough pavé road, is the so-called Multi Stethoscope (MSS). The MSS is measuring the distortion in each body closure opening in two diagonals. During the virtual development, the distortion is described by the relative displacement in diagonal direction in time domain using a modal transient analysis. The results are shown as Opening Distortion Fingerprint ODF and used as assessment criteria within Solidity and Perceived Quality.By applying the Principal Component Analysis (PCA) on the time history of the distortion, a Dominant Distortion Pattern (DDP) can be identified. The DDP means that, for a given pavé time history, more than 50 % of the body deformation states are similar to each other. This paper presents a deeper analysis about the forces which are associated with this Dominant Distortion Pattern (DDP). The new aspect of this analysis is that all forces (54 in total) between the wheel suspension and the trimmed body are considered. Based on the results of this force analysis, a new procedure for creating an Equivalent Static Load (ESL) was developed. Finally, by automating this creation procedure it is shown how the new ESL can be integrated in the virtual vehicle development.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"86 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141352907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kyoungjin Noh, Dongchul Lee, Insoo Jung, Simon Tate, James Mullineux, Farraen Mohd Azmin
The high-frequency whining noise produced by motors in modern electric vehicles can cause a significant issue, which leads to passenger annoyance. This noise becomes even more noticeable due to the quiet nature of electric vehicles, which lack background noise sources to mask the high-frequency whining noise. To improve the noise caused by motors, it is essential to optimize various motor design parameters. However, this task requires expert knowledge and a considerable time investment. In this project, the application of artificial intelligence was applied to optimize the NVH performance of motors during the design phase. Firstly, three benchmark motor types were modelled using the Motor-CAD CAE tool. Machine learning models were trained using DoE methods to simulate batch runs of CAE inputs and outputs. By applying AI, a CatBoost-based regression model was developed to estimate motor performance, including NVH and torque, based on motor design parameters, achieving impressive R-squared values of 0.94 - 0.99. Additionally, further key design predictors were analysed through SHAP. Subsequently, various optimization algorithms were investigated, including particle swarm optimization, genetic algorithm, and reinforcement learning, to determine the optimal adjustments of motor design parameters for improved NVH performance. Throughout this process, improvements in NVH performance were achieved while applying constraints to maintain torque levels and motor cost. Finally, the AI model and optimization algorithms were integrated into a user interface dashboard, enabling motor design engineers to efficiently predict motor NVH performance by selecting input parameters, applying attribute balance constraints, and executing optimizations.
{"title":"AI-Based Optimization Method of Motor Design Parameters for Enhanced NVH Performance in Electric Vehicles","authors":"Kyoungjin Noh, Dongchul Lee, Insoo Jung, Simon Tate, James Mullineux, Farraen Mohd Azmin","doi":"10.4271/2024-01-2927","DOIUrl":"https://doi.org/10.4271/2024-01-2927","url":null,"abstract":"The high-frequency whining noise produced by motors in modern electric vehicles can cause a significant issue, which leads to passenger annoyance. This noise becomes even more noticeable due to the quiet nature of electric vehicles, which lack background noise sources to mask the high-frequency whining noise. To improve the noise caused by motors, it is essential to optimize various motor design parameters. However, this task requires expert knowledge and a considerable time investment. In this project, the application of artificial intelligence was applied to optimize the NVH performance of motors during the design phase. Firstly, three benchmark motor types were modelled using the Motor-CAD CAE tool. Machine learning models were trained using DoE methods to simulate batch runs of CAE inputs and outputs. By applying AI, a CatBoost-based regression model was developed to estimate motor performance, including NVH and torque, based on motor design parameters, achieving impressive R-squared values of 0.94 - 0.99. Additionally, further key design predictors were analysed through SHAP. Subsequently, various optimization algorithms were investigated, including particle swarm optimization, genetic algorithm, and reinforcement learning, to determine the optimal adjustments of motor design parameters for improved NVH performance. Throughout this process, improvements in NVH performance were achieved while applying constraints to maintain torque levels and motor cost. Finally, the AI model and optimization algorithms were integrated into a user interface dashboard, enabling motor design engineers to efficiently predict motor NVH performance by selecting input parameters, applying attribute balance constraints, and executing optimizations.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"17 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141354771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Combustion engines in hybrid vehicles start and shut off several times during a typical passenger car trip. Each engine restart may pose a risk of excessive tailpipe emissions in real-drive conditions if the after-treatment system fails to maintain an adequate temperature level during engine off mode. In view of the tightening worldwide tailpipe emissions standards and real-world conformity requirements, it is important to detect and resolve such risks via reliable and cost-effective engineering tools that can perform accurate analysis of the thermal and chemical behavior of exhaust systems. In this work, we present a catalyst model that predicts the 3D thermal and chemical behavior under normal and zero flow conditions. Particular emphasis is given to the phenomena of free convection and thermal radiation dominating the heat transfer at zero flow. Next, we examine the impact of zero-flow duration on the exhaust system temperature and subsequent emissions risk and we validate the obtained results with respective measurements from experimental tests. Overall, the model can accurately predict the temperature distribution inside the catalyst and tail pipe emissions, under a broad range of operating conditions. The model can subsequently be used to study several scenarios of vehicle hybridization schemes, as well as techniques to minimize the risk of zero flow operation by proper system design and control.
{"title":"Experimental and Simulation Study of Zero Flow Impact on Hybrid Vehicle Emissions","authors":"Valesia Emmanouil, Grigorios Koltsakis, Costas Kotoulas","doi":"10.4271/2024-37-0036","DOIUrl":"https://doi.org/10.4271/2024-37-0036","url":null,"abstract":"Combustion engines in hybrid vehicles start and shut off several times during a typical passenger car trip. Each engine restart may pose a risk of excessive tailpipe emissions in real-drive conditions if the after-treatment system fails to maintain an adequate temperature level during engine off mode. In view of the tightening worldwide tailpipe emissions standards and real-world conformity requirements, it is important to detect and resolve such risks via reliable and cost-effective engineering tools that can perform accurate analysis of the thermal and chemical behavior of exhaust systems. In this work, we present a catalyst model that predicts the 3D thermal and chemical behavior under normal and zero flow conditions. Particular emphasis is given to the phenomena of free convection and thermal radiation dominating the heat transfer at zero flow. Next, we examine the impact of zero-flow duration on the exhaust system temperature and subsequent emissions risk and we validate the obtained results with respective measurements from experimental tests. Overall, the model can accurately predict the temperature distribution inside the catalyst and tail pipe emissions, under a broad range of operating conditions. The model can subsequently be used to study several scenarios of vehicle hybridization schemes, as well as techniques to minimize the risk of zero flow operation by proper system design and control.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"29 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141349772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kanghyun An, Doyeon Kim, Seong Yeol Kim, JunSeok Choi, Changik Lee, Howuk Kim, Sang Kwon Lee, Mingoo Im, Hyeon Seok Cho, Changseop An, Jeong Ho Kim
This paper presents the novel active vibration control (AVC) system that controls vehicle body vibration to reduce the structural borne road noise. As a result of vehicle noise testing in a test vehicle, the predominant frequency of vehicle body vibration that worsens interior noise is in the range under 500Hz. Such vibration in that frequency range, commonly masked in engine vibrations, are hard to neglect for motor driven vehicles. The vibration source of that frequency is the resonance of tire cavity mode. Resonator or absorption material has been applied inside the tire for the control of cavity noise as a passive method. They require an increment of weight and cost. Therefore, a novel method is necessary. The vibration amplified by resonance of cavity mode is transferred to the vehicle body throughout the suspension system. To reduce the vibration, AVC system is applied to the suspension mount. The AVC system consists of one actuator, two vibration sensors and one reference vibration sensor based on feed forward control and its technical validation is performed on the test rig of a car suspension system. As novel work for the successful control of the AVC system, firstly, ring-type piezoelectric stack actuator suitable for this AVC system was developed and mounted inside the suspension mount bolt. Secondly, the mount location of the reference accelerometer was selected based on the coherence method. Filter length of the adaptive filter used for the FxLMS algorithm was optimized based on concept on optimized filter length. The developed AVC system could suppress the vibration level (-6dB) caused by the tire resonance at the target frequency band. The proposed AVC system will provide a novel modality to enhance the quality of noise and vibration in motor driven vehicles by actively controlling tire-induced structural vibrations.
{"title":"Active Vibration Control System for Attenuation of Structure Borne Road Noise by Tire Cavity Resonance Using Piezoelectric Stack Actuators","authors":"Kanghyun An, Doyeon Kim, Seong Yeol Kim, JunSeok Choi, Changik Lee, Howuk Kim, Sang Kwon Lee, Mingoo Im, Hyeon Seok Cho, Changseop An, Jeong Ho Kim","doi":"10.4271/2024-01-2953","DOIUrl":"https://doi.org/10.4271/2024-01-2953","url":null,"abstract":"This paper presents the novel active vibration control (AVC) system that controls vehicle body vibration to reduce the structural borne road noise. As a result of vehicle noise testing in a test vehicle, the predominant frequency of vehicle body vibration that worsens interior noise is in the range under 500Hz. Such vibration in that frequency range, commonly masked in engine vibrations, are hard to neglect for motor driven vehicles. The vibration source of that frequency is the resonance of tire cavity mode. Resonator or absorption material has been applied inside the tire for the control of cavity noise as a passive method. They require an increment of weight and cost. Therefore, a novel method is necessary. The vibration amplified by resonance of cavity mode is transferred to the vehicle body throughout the suspension system. To reduce the vibration, AVC system is applied to the suspension mount. The AVC system consists of one actuator, two vibration sensors and one reference vibration sensor based on feed forward control and its technical validation is performed on the test rig of a car suspension system. As novel work for the successful control of the AVC system, firstly, ring-type piezoelectric stack actuator suitable for this AVC system was developed and mounted inside the suspension mount bolt. Secondly, the mount location of the reference accelerometer was selected based on the coherence method. Filter length of the adaptive filter used for the FxLMS algorithm was optimized based on concept on optimized filter length. The developed AVC system could suppress the vibration level (-6dB) caused by the tire resonance at the target frequency band. The proposed AVC system will provide a novel modality to enhance the quality of noise and vibration in motor driven vehicles by actively controlling tire-induced structural vibrations.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"78 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141352877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Massimo Sicilia, Davide Cervone, P. Polverino, C. Pianese
Water management in PEMFC power generation systems is a key point to guarantee optimal performances and durability. It is known that a poor water management has a direct impact on PEMFC voltage, both in drying and flooding conditions: furthermore, water management entails phenomena from micro-scale, i.e., formation and water transport within membrane, to meso-scale, i.e., water capillary transport inside the GDL, up to the macro-scale, i.e., water droplet formation and removal from the GFC. Water transport mechanisms through the membrane are well known in literature, but typically a high computational burden is requested for their proper simulation. To deal with this issue, the authors have developed an analytical model for the water membrane content simulation as function of stack temperature and current density, for fast on-board monitoring and control purposes, with good fit with literature data. The water flow from the catalyst layer to the GFC through the GDL is modelled considering as main transport mechanism the capillary transport. The water coming from the GDL then emerges through the pores inside the channel forming water droplets that interact with the air flow. The authors have developed several papers on this topic: mathematical models have been developed for droplet’s emersion, oscillation, and detachment phases; furthermore, the coalescence between near droplets has been included into the modelling. The authors have also validated with experimental results the proposed models. The objective of this paper is to develop a mathematical model able to represent a typical fuel cell stack in order to predict the water membrane content and the water removal rate, that are fundamental to correctly control the PEMFC system in order to avoid the critical conditions mentioned before, ensuring the best performances of the stack reducing the hydrogen consumption. The model is validated with literature data, showing optimal fit and high correlation, making it suitable for further analyses.
{"title":"Model-Based Algorithm for Water Management Diagnosis and Control of PEMFC Systems for Motive Applications","authors":"Massimo Sicilia, Davide Cervone, P. Polverino, C. Pianese","doi":"10.4271/2024-37-0004","DOIUrl":"https://doi.org/10.4271/2024-37-0004","url":null,"abstract":"Water management in PEMFC power generation systems is a key point to guarantee optimal performances and durability. It is known that a poor water management has a direct impact on PEMFC voltage, both in drying and flooding conditions: furthermore, water management entails phenomena from micro-scale, i.e., formation and water transport within membrane, to meso-scale, i.e., water capillary transport inside the GDL, up to the macro-scale, i.e., water droplet formation and removal from the GFC. Water transport mechanisms through the membrane are well known in literature, but typically a high computational burden is requested for their proper simulation. To deal with this issue, the authors have developed an analytical model for the water membrane content simulation as function of stack temperature and current density, for fast on-board monitoring and control purposes, with good fit with literature data. The water flow from the catalyst layer to the GFC through the GDL is modelled considering as main transport mechanism the capillary transport. The water coming from the GDL then emerges through the pores inside the channel forming water droplets that interact with the air flow. The authors have developed several papers on this topic: mathematical models have been developed for droplet’s emersion, oscillation, and detachment phases; furthermore, the coalescence between near droplets has been included into the modelling. The authors have also validated with experimental results the proposed models. The objective of this paper is to develop a mathematical model able to represent a typical fuel cell stack in order to predict the water membrane content and the water removal rate, that are fundamental to correctly control the PEMFC system in order to avoid the critical conditions mentioned before, ensuring the best performances of the stack reducing the hydrogen consumption. The model is validated with literature data, showing optimal fit and high correlation, making it suitable for further analyses.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"54 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141350463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Volza, A. Pisapia, S. Caprioli, C. Rinaldini, E. Mattarelli
Heavy duty engines for long-haul trucks are quite difficult to electrify, due to the large amount of energy that should be stored on-board to achieve a range comparable to that of conventional fuels. In particular, this paper considers a stock engine with a displacement of 12.9 L, developed by the manufacturer in two different versions. As a standard diesel, the engine is able to deliver about 420 kW at 1800 rpm, whereas in the compressed natural gas configuration the maximum power output is 330 kW, at the same speed. Three possible alternatives to these fossil fuels are considered in this study: biodiesel (HVOlution by Eni), bio-methane and green hydrogen.While the replacement of diesel and compressed natura gas with biofuels does not need significant hardware modifications, the implementation of a hydrogen spark ignition combustion system requires a deep revision of the engine concept. For a more straightforward comparison among the alternative fuels, the same engine platform has been considered.The hydrogen engine has been optimized with the support of CFD-1D simulation (GT-Power), using models calibrated with experimental data, obtained on the diesel and compressed natural gas versions. The numerical tool includes a predictive combustion model (SI-Turb), also calibrated with experimental data on a hydrogen prototype.The study shows that the implementation of a combustion system running on lean mixtures of hydrogen, permits to cancel the emissions of CO2, while maintaining the same power output of the compressed natural gas / bio-methane engine (but about 20% lower than the biodiesel). Moreover, the concentration of NOx is very low (<20 ppm) at all the operating conditions, enabling a strong simplification of the after-treatment system, at least in comparison to the original diesel/biodiesel version. Finally, the hydrogen solution exhibits an average increase of approximately 9% in efficiency respect to the compressed natural gas configuration, but it remains less efficient if compared to its biodiesel counterpart (-11%).
{"title":"Sustainable Fuels for Long-Haul Truck Engines: A 1D-CFD Analysis","authors":"A. Volza, A. Pisapia, S. Caprioli, C. Rinaldini, E. Mattarelli","doi":"10.4271/2024-37-0027","DOIUrl":"https://doi.org/10.4271/2024-37-0027","url":null,"abstract":"Heavy duty engines for long-haul trucks are quite difficult to electrify, due to the large amount of energy that should be stored on-board to achieve a range comparable to that of conventional fuels. In particular, this paper considers a stock engine with a displacement of 12.9 L, developed by the manufacturer in two different versions. As a standard diesel, the engine is able to deliver about 420 kW at 1800 rpm, whereas in the compressed natural gas configuration the maximum power output is 330 kW, at the same speed. Three possible alternatives to these fossil fuels are considered in this study: biodiesel (HVOlution by Eni), bio-methane and green hydrogen.While the replacement of diesel and compressed natura gas with biofuels does not need significant hardware modifications, the implementation of a hydrogen spark ignition combustion system requires a deep revision of the engine concept. For a more straightforward comparison among the alternative fuels, the same engine platform has been considered.The hydrogen engine has been optimized with the support of CFD-1D simulation (GT-Power), using models calibrated with experimental data, obtained on the diesel and compressed natural gas versions. The numerical tool includes a predictive combustion model (SI-Turb), also calibrated with experimental data on a hydrogen prototype.The study shows that the implementation of a combustion system running on lean mixtures of hydrogen, permits to cancel the emissions of CO2, while maintaining the same power output of the compressed natural gas / bio-methane engine (but about 20% lower than the biodiesel). Moreover, the concentration of NOx is very low (<20 ppm) at all the operating conditions, enabling a strong simplification of the after-treatment system, at least in comparison to the original diesel/biodiesel version. Finally, the hydrogen solution exhibits an average increase of approximately 9% in efficiency respect to the compressed natural gas configuration, but it remains less efficient if compared to its biodiesel counterpart (-11%).","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"84 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141352560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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