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Articles de revues sur le sujet "Explicit Powertrain Consumption Model"
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Bou Nader, Wissam S., Charbel J. Mansour, Maroun G. Nemer et Olivier M. Guezet. « Exergo-technological explicit methodology for gas-turbine system optimization of series hybrid electric vehicles ». Proceedings of the Institution of Mechanical Engineers, Part D : Journal of Automobile Engineering 232, no 10 (6 octobre 2017) : 1323–38. http://dx.doi.org/10.1177/0954407017728849.
Texte intégralRésumé :
Significant research efforts have been invested in the automotive industry on hybrid electrified powertrains in order to reduce the dependence of passenger cars on oil. Electrification of powertrains resulted in a wide range of hybrid vehicle architectures. The fuel consumption of these powertrains strongly relies on the energy converter performance, as well as on the energy management strategy deployed on board. This paper investigates the potential of fuel consumption savings of a series hybrid electric vehicle using a gas turbine as an energy converter instead of the conventional internal-combustion engine. An exergo-technological explicit analysis is conducted to identify the best configuration of the gas-turbine system. An intercooled regenerative reheat cycle is prioritized, offering higher efficiency and higher power density than those of other investigated gas-turbine systems. A series hybrid electric vehicle model is developed and powertrain components are sized by considering the vehicle performance criteria. Energy consumption simulations are performed over the Worldwide Harmonized Light Vehicles Test Procedure driving cycle using dynamic programming as the global optimal energy management strategy. A sensitivity analysis is also carried out in order to evaluate the impact of the battery size on the fuel consumption, for self-sustaining and plug-in series hybrid electric vehicle configurations. The results show an improvement in the fuel consumption of 22–25% with the gas turbine as the auxiliary power unit in comparison with that of the internal-combustion engine. Consequently, the studied auxiliary power unit for the gas turbine presents a potential for implementation on series hybrid electric vehicles.
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Ou, Shiqi, Wan Li, Jie Li, Zhenhong Lin, Xin He, Jessey Bouchard et Steven Przesmitzki. « Relationships between Vehicle Pricing and Features : Data Driven Analysis of the Chinese Vehicle Market ». Energies 13, no 12 (15 juin 2020) : 3088. http://dx.doi.org/10.3390/en13123088.
Texte intégralRésumé :
A full-scale understanding of the dynamics of the Chinese vehicle market can benefit stakeholders with respect to rational decision-making and effective long-term investment. This study attempts to discover the common vehicle pricing patterns in the Chinese market by quantifying statistical correlations among critical vehicle features from intrinsic powertrain systems to extrinsic market positioning. The data samples involve almost all passenger vehicle models sold in 2013 to 2019. After comparing multiple statistical methodologies, a log-transformation variant of the multinomial linear regression model was found to be the best one, and the goodness of fit shows that this model can offer stable estimates, which were validated using 2019 market data. The insights achieved are: (1) The price and major performance features of SUVs/crossovers are similar to those of sedans; (2) If all other explicit features remain the same, the price of a Japanese midsize sedan is 62% higher than that of a Chinese midsize sedan, and European midsize vehicles have the highest prices overall. (3) The incremental price of fuel consumption varies by vehicle class and fuel economy. For example, from 30 to 50 MPG, the vehicle price increases by $119 for a Chinese brand sedan vehicle, by $69 for a Chinese brand SUV.
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Petr, Tomáš. « EVALUATING ELECTRICITY CONSUMPTION OF SPECIALISED BATTERY ELECTRIC VEHICLES USING SIMULATION MODEL ». ACC Journal 29, no 1 (2023) : 34–43. http://dx.doi.org/10.15240/tul/004/2023-1-003.
Texte intégralRésumé :
Battery Electric Vehicles (BEVs) are widely seen as one of the available options to combat increasing greenhouse gas emissions. However, these vehicles’ use is less widespread than conventional combustion engine vehicles. One reason for this is their still relatively short range and long charging times. For this reason, it is becoming increasingly crucial in BEV development to use the most accurate simulation models that allow the impact on electricity consumption to be analyzed based on changes made to individual powertrain components. To this end, the author’s dissertation deals with developing a simulation model for estimating the power consumption of a BEV powertrain, describing the definition of the efficiency parameters of the individual powertrain components. The results from the simulation model were then compared with measurements performed in a test facility. The maximum deviation of approximately 8% was measured depending on the driving cycle and parameters.
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Maddumage, W. U., K. Y. Abeyasighe, M. S. M. Perera, R. A. Attalage et P. Kelly. « Comparing Fuel Consumption and Emission Levels of Hybrid Powertrain Configurations and a Conventional Powertrain in Varied Drive Cycles and Degree of Hybridization ». Science & ; Technique 19, no 1 (5 février 2020) : 20–33. http://dx.doi.org/10.21122/2227-1031-2020-19-1-20-33.
Texte intégralRésumé :
Hybrid electric powertrains in automotive applications aim to improve emissions and fuel economy with respect to conventional internal combustion engine vehicles. Variety of design scenarios need to be addressed in designing a hybrid electric vehicle to achieve desired design objectives such as fuel consumption and exhaust gas emissions. The work in this paper presents an analysis of the design objectives for an automobile powertrain with respect to different design scenarios, i. e. target drive cycle and degree of hybridization. Toward these ends, four powertrain configuration models (i. e. internal combustion engine, series, parallel and complex hybrid powertrain configurations) of a small vehicle (motorized three wheeler) are developed using Model Advisor software and simulated with varied drive cycles and degrees of hybridization. Firstly, the impact of vehicle power control strategy and operational characteristics of the different powertrain configurations are investigated with respect to exhaust gas emissions and fuel consumption. Secondly, the drive cycles are scaled according to kinetic intensity and the relationship between fuel consumption and drive cycles is assessed. Thirdly, three fuel consumption models are developed so that fuel consumption values for a real-world drive cycle may be predicted in regard to each powertrain configuration. The results show that when compared with a conventional powertrain fuel consumption is lower in hybrid vehicles. This work led to the surprisingly result showing higher CO emission levels with hybrid vehicles. Furthermore, fuel consumption of all four powertrains showed a strong correlation with kinetic intensity values of selected drive cycles. It was found that with varied drive cycles the average fuel advantage for each was: series 23 %, parallel 21 %, and complex hybrids 33 %, compared to an IC engine powertrain. The study reveals that performance of hybrid configurations vary significantly with drive cycle and degree of hybridization. The paper also suggests future areas of study.
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Angerer, C., B. Mößner, M. Lüst, S. Büchner, F. Sträußl et M. Lienkamp. « Parameter-adaption for a vehicle dynamics model for the evaluation of powertrain concept designs ». MATEC Web of Conferences 272 (2019) : 01022. http://dx.doi.org/10.1051/matecconf/201927201022.
Texte intégralRésumé :
The powertrain design of multi-motor electric vehicles directly affects not only costs, consumption and acceleration, but also the handling of a vehicle. Therefore, a holistic powertrain design optimization needs to include a vehicle dynamics model in its objective function. While the parameters for the powertrain model result from the design variables that describe the powertrain, the parameters for the vehicle dynamics model must be adapted in a feasible way to ensure comparable results. Therefore, the authors present a method on how to adaptively parametrize a double-track vehicle dynamics model for the use in powertrain design optimization. Automated design calculations for all main chassis and suspension parts are used to determine the parameters for the model. A parameter variation proves the plausibility of the approach. The results show that an adaption of the suspension and chassis parameters due to changes in the powertrain make results more comparable but do not compensate for the effects on the vehicle handling. In particular, the steady state longitudinal load distribution still has major influences on the vehicle handling.
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Geng, Stefan, Thomas Schulte et Jürgen Maas. « Model-Based Analysis of Different Equivalent Consumption Minimization Strategies for a Plug-In Hybrid Electric Vehicle ». Applied Sciences 12, no 6 (11 mars 2022) : 2905. http://dx.doi.org/10.3390/app12062905.
Texte intégralRésumé :
Plug-in hybrid electric vehicles (PHEVs) are developed to reduce fuel consumption and the emission of carbon dioxide. Common powertrain configurations of PHEVs (i.e., the configuration of the combustion engine, electric motor, and transmission) can be operated either in series, parallel, or power split hybrid mode, whereas powertrain configurations with multimode transmissions enable switching between those modes during vehicle operation. Hence, depending on the current operation state of the vehicle, the most appropriate mode in terms efficiency can be selected. This, however, requires an operating strategy, which controls the mode selection as well as the torque distribution between the combustion engine and electric motor with the aim of optimal battery depletion and minimal fuel consumption. A well-known approach is the equivalent consumption minimization strategy (ECMS). It can be applied by using optimizations based on a prediction of the future driving behavior. Since the outcome of the ECMS depends on the quality of this prediction, it is crucial to know how accurate the predictions must be in order to obtain acceptable results. In this contribution, various prediction methods and real-time capable ECMS implementations are analyzed and compared in terms of the achievable fuel economy. The basis for the analysis is a holistic model of a state-of-the-art PHEV powertrain configuration, comprising the multimode transmission, corresponding powertrain components, and representative real-world driving data.
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König, Adrian, Sebastian Mayer, Lorenzo Nicoletti, Stephan Tumphart et Markus Lienkamp. « The Impact of HVAC on the Development of Autonomous and Electric Vehicle Concepts ». Energies 15, no 2 (9 janvier 2022) : 441. http://dx.doi.org/10.3390/en15020441.
Texte intégralRésumé :
Automation and electrification are changing vehicles and mobility. Whereas electrification is mainly changing the powertrain, automation enables the rethinking of the vehicle and its applications. The actual driving range is an important requirement for the design of automated and electric vehicles, especially if they are part of a fleet. To size the battery accordingly, not only the consumption of the powertrain has to be estimated, but also that of the auxiliary users. Heating Ventilation and Air Conditioning (HVAC) is one of the biggest auxiliary consumers. Thus, a variable HVAC model for vehicles with electric powertrain was developed to estimate the consumption depending on vehicle size and weather scenario. After integrating the model into a tool for autonomous and electric vehicle concept development, various vehicle concepts were simulated in different weather scenarios and driving cycles with the HVAC consumption considered for battery sizing. The results indicate that the battery must be resized significantly depending on the weather scenario to achieve the same driving ranges. Furthermore, the percentage of HVAC consumption is in some cases higher than that of the powertrain for urban driving cycles, due to lower average speeds. Thus, the HVAC and its energy demand should especially be considered in the development of autonomous and electric vehicles that are primarily used in cities.
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Geng, Stefan, Andreas Meier et Thomas Schulte. « Model-Based Optimization of a Plug-In Hybrid Electric Powertrain with Multimode Transmission ». World Electric Vehicle Journal 9, no 1 (13 juin 2018) : 12. http://dx.doi.org/10.3390/wevj9010012.
Texte intégralRésumé :
Plug-in hybrid electric vehicles are developed in order to reduce the fuel consumption and the emission of carbon dioxide. Besides the series, parallel and power split configurations are commonly used for conventional hybrid electric vehicles, and multimode transmissions are used for plug-in hybrid electric vehicles, which are able to switch between different modes like parallel or series operation of the combustion engine and electric motor. Several concepts have already been discussed and presented. These concepts comprise novel structures and multi-speed operation for the combustion engine and the electric motor, respectively. For improving the fuel and energy consumption, model-based optimizations of multimode transmissions are performed. In the first step of the optimization, the optimal number of gears and transmission ratios, as well as the corresponding fuel and energy savings, are estimated. Based on these results, a new multimode transmission concept with two-speed transmissions for the combustion engine and the electric motor has been developed. The knowledge of the concrete concept enables the further optimizations of the transmission ratios and the transmission control. In order to prove the benefit of the new and optimized transmission concept, powertrain simulations have been carried out. The new powertrain concept is compared to a powertrain concept with single-speed transmissions for the internal combustion engine (ICE) and electric motor operation. The new transmission concept enables a significant improvement of the fuel consumption.
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Shen, Ye, Andreas Viehmann et Stephan Rinderknecht. « Investigation of the power losses of the hybrid transmission DE-REX based on modeling and measurement ». Proceedings of the Institution of Mechanical Engineers, Part D : Journal of Automobile Engineering 233, no 14 (18 février 2019) : 3646–57. http://dx.doi.org/10.1177/0954407019829655.
Texte intégralRésumé :
Electric and hybrid powertrains are developed to reduce the energy and fuel consumption of vehicles. Recently, multi-speed transmission systems were discussed for further reduction of the energy consumption of electric vehicles. Therefore, analyzing the power losses of such transmissions is of interest. In this paper, the novel powertrain concept DE-REX (Two-Drive-Transmission with Range-Extender) and the experimental investigation of its overall power losses is first introduced. A method is then developed to model and analyze the power losses of this hybrid transmission based on experimental data. After the validation of the method, the overall power loss model is eventually applied to estimate the power losses of the transmission at other driving modes, which were not measured on the test rig. The method is used to understand the characteristics of power losses inside the transmission in a hybrid powertrain and to optimize powertrain power losses in future.
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Sigle, Sebastian, et Robert Hahn. « Energy Assessment of Different Powertrain Options for Heavy-Duty Vehicles and Energy Implications of Autonomous Driving ». Energies 16, no 18 (9 septembre 2023) : 6512. http://dx.doi.org/10.3390/en16186512.
Texte intégralRésumé :
Heavy-duty vehicles (HDVs) are responsible for a significant amount of CO2 emissions in the transport sector. The share of these vehicles is still increasing in the European Union (EU); nevertheless, rigorous CO2 emission reduction schemes will apply in the near future. Different measures to decrease CO2 emissions are being already discussed, e.g., the electrification of the powertrain. Additionally, the impact of autonomous driving on energy consumption is being investigated. The most common types are fuel cell vehicles (FCEVs) and battery-only vehicles (BEVs). It is still unclear which type of powertrain will prevail in the future. Therefore, we developed a method to compare different powertrain options based on different scenarios in terms of primary energy consumption, CO2 emissions, and fuel costs. We compared the results with the internal combustion engine vehicle (ICEV). The model includes a model for the climatization of the driver’s cabin, which we used to investigate the impact of autonomous driving on energy consumption. It became clear that certain powertrains offer advantages for certain applications and that sensitivities exist with regard to primary energy and CO2 emissions. Overall, it became clear that electrified powertrains could reduce the CO2 emissions and the primary energy consumption of HDVs. Moreover, autonomous vehicles can save energy in most cases.
Thèses sur le sujet "Explicit Powertrain Consumption Model"
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Tamaro, Courtney Alex. « Vehicle powertrain model to predict energy consumption for ecorouting purposes ». Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/71635.
Texte intégralRésumé :
The automotive industry is facing some of the most difficult design challenges in industry history. Developing innovative methods to reduce fossil fuel dependence is imperative for maintaining compliance with government regulations and consumer demand. In addition to powertrain design, route selection contributes to vehicle environmental impact.
The objective of this thesis is to develop a methodology for evaluating the energy consumption of each route option for a specific vehicle. A 'backwards' energy tracking method determines tractive demand at the wheels from route requirements and vehicle characteristics. Next, this method tracks energy quantities at each powertrain component. Each component model is scalable such that different vehicle powertrains may be approximated. Using an 'ecorouting' process, the most ideal route is selected by weighting relative total energy consumption and travel time.
Only limited powertrain characteristics are publicly available. As the future goal of this project is to apply the model to many vehicle powertrain types, the powertrain model must be reasonably accurate with minimal vehicle powertrain characteristics. Future work expands this model to constantly re-evaluate energy consumption with real-time traffic and terrain information.
While ecorouting has been applied to conventional vehicles in many publications, electrified vehicles are less studied. Hybrid vehicles are particularly complicated to model due to additional components, systems, and operation modes. This methodology has been validated to represent conventional, battery electric, and parallel hybrid electric vehicles. A sensitivity study demonstrates that the model is capable of differentiating powertrains with different parameters and routes with different characteristics.Master of Science
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Karlsson, Karl. « Validation of Bus Specific Powertrain Components in STARS ». Thesis, Linköping University, Department of Electrical Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-10525.
Texte intégralRésumé :
The possibilities to simulate fuel consumption and optimize a vehicle's powertrain to fit to the customer's needs are great strengths in the competitive bus industry where fuel consumption is one of the main sales arguments. In this master's thesis, bus specific powertrain component models, used to simulate and predict fuel consumption, are validated using measured data collected from buses.
Additionally, a sensitivity analysis is made where it is investigated how errors in the powertrain parameters affect fuel consumption. After model improvements it is concluded that the library components can be used to predict fuel consumption well.
During the work, possible model uncertainties which affect fuel consumption are identified. Hence, this study may serve as foundation for further investigation of these uncertainties.
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Carlos, Da Silva Daniel. « Development of a closed-form modeling methodology for the subsystems of electric vehicles : optimization of energy performance ». Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPAST014.
Texte intégralRésumé :
Pour maximiser la contribution des véhicules hybrides électriques (HEV) à la décarbonation du secteur des transports, il est essentiel de prendre en compte leur performance énergétique lors de la phase de conception. Cependant, les chemins supplémentaires de flux de puissance pour la propulsion agissent à la fois comme un avantage et comme une couche supplémentaire de complexité dans la conception du véhicule. En effet, évaluer la consommation d'un HEV nécessite la définition d'un contrôle de supervision, appelé Loi de Gestion d'Énergie (LGE). Ainsi, optimiser la conception exige la combinaison d'un problème d'optimisation statique (la structure du système) avec un problème dépendant du temps (son contrôle), qui doivent être pris en compte de manière conjointe.Cette co-optimisation structure/contrôle est généralement abordée soit en imbriquant des algorithmes de contrôle optimal dans un algorithme d'optimisation général pour la structure, soit en utilisant de l'optimisation convexe pour optimiser simultanément les deux niveaux. Cependant, la première approche est connue pour avoir des contraintes computationnelles, tandis que la seconde peut affecter la fidélité de la modélisation en raison de contraintes de convexité.Sous une nouvelle perspective, cette thèse introduit une méthodologie pour développer des modèles explicites pour estimer la consommation d'énergie de groupes motopropulseurs, nommés dans ce travail Modèle Explicite de Consommation du Groupe Motopropulseur (EPCM). Ils sont développés à l'aide de modèles de composants pour considérer les pertes de puissance, puis en introduisant un deuxième niveau de modélisation pour prendre en compte l'impact des variations de dimensionnement sur l'estimation des pertes. Une telle formulation peut être utilisée comme une fonction objectif efficace d'un problème d'optimisation qui reste statique, tout en permettant une analyse explicable par l'homme pour des problèmes réduits.La thèse présente le développement de la méthodologie en utilisant un véhicule hybride électrique à pile à combustible (FCHEV) comme véhicule de référence. Outre la modélisation des composants couramment présents dans les véhicules électriques, elle inclut un modèle pour le système de pile à combustible, tout en considérant également des modèles pour l'électronique de puissance, souvent négligée dans ce type d'études. Elle présente d'abord les modèles de composants pris en compte, puis les modèles de variation de dimensionnement (les modèles prédictifs), avant de développer les EPCMs et de les utiliser pour la co-optimisation.La validation des modèles de composants à l'aide d'une Toyota Mirai II sur un banc à rouleaux présente une erreur globale de moins de cinq pour cent, tandis que l'étude visant à évaluer l'impact des modèles prédictifs sur la consommation d'hydrogène a donné des erreurs inférieures à deux pour cent par rapport aux modèles de référence. Ensuite, une évaluation de l'utilisation des EPCM explore les hypothèses nécessaires pour garantir une formulation explicite, et la co-optimisation du groupe motopropulseur de la Mirai II montre qu'un EPCM utilisant une LGE affine est une approximation raisonnable pour la co-optimisation aux premières étapes de conception du véhicule, tout en réduisant le temps d'évaluation d'un facteur de 100. Cette étude est ensuite étendue avec des problèmes réduits pour observer l'impact du dimensionnement de l'EM uniquement, puis du niveau d'hybridation, aboutissant à des expressions linéaires et quadratiques pour la consommation de carburant et les contraintes d'optimisation, qui peuvent être utilisées pour dériver rapidement des analyses de la performance énergétique du véhicule.Bien que les résultats montrent que l'état actuel de la méthodologie peut être utilisé pour la co-optimisation des FCHEV, la thèse explore davantage les points d'amélioration de la méthodologie et suggère des applications alternatives pour consolider sa validité et sa pertinenceTo maximize the contribution of hybrid electric vehicles (HEV) to the decarbonization of the transportation sector, it is essential to maximize their energy performance during the design phase. However, the additional power pathways to propel the vehicle act both as an advantage and an added layer of complexity. Indeed, evaluating the consumption of an HEV requires defining a supervisory control, known as Energy Management Strategy (EMS). Therefore, optimizing the design entails combining a static optimization problem (system's plant) with a time-dependent problem (its control), both of which must be considered in tandem.This plant/control co-optimization is typically tackled through either nesting optimal control algorithms within each iteration of a general optimization algorithm for the plant, or employing convex optimization to simultaneously optimize both layers. However, the former approach is known to be limited by computational constraints, while the latter may impact modeling fidelity due to convexity constraints.As a different perspective, this thesis introduces a methodology for developing explicit models to estimate powertrain energy consumption, referred to in this work as the Explicit Powertrain Consumption Model (EPCM). They are developed using component models to account for power losses, then by introducing a second modeling level to consider the impact of sizing variations on loss estimation. Such a formulation can be used as a computationally efficient objective function of an optimization problem that remains static, while enabling human-explainable analysis for reduced problems.The thesis presents the methodology development while using a Fuel Cell Hybrid Electric Vehicle (FCHEV) as a reference vehicle. Besides modeling components commonly found in electric vehicles, it includes a model for the fuel cell system, while further considering models for the power electronics, often overlooked in vehicle design studies. It first introduces the considered component models, then the models for the sizing variation (i.e., the predictive models), before developing the EPCMs and using them for the co-optimization.The validation of the component models using a Toyota Mirai~II on a roller test bench presents an overall error of less than five percent, while the study to assess the impact of the predictive models on the hydrogen consumption resulted in errors below two percent when compared to reference models. Then, an assessment of the usage of EPCMs explores the assumptions required to ensure an explicit formulation; and the co-optimization of the Mirai~II powertrain shows that an EPCM using an affine EMS can be a fair approximation for the co-optimization at the vehicle's first design stages, while reducing the evaluation time by a factor of 100. This study is further extended with reduced problems to observe the impact of the EM sizing only, then of the hybridization level, resulting in linear and quadratic expressions for the fuel consumption and the optimization constraints, which can be used to quickly derive analyses of the vehicle's energy performance.Although the results show that the current state of the methodology can be used for the co-optimization of FCHEVs, the thesis further explores its improvement points and suggests alternative applications to solidify its validity and relevance
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Song, Guanqiao. « Analysis of the energy consumption of the powertrain and the auxiliary systems for battery-electric trucks ». Thesis, KTH, Fordonsdynamik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-286349.
Texte intégralRésumé :
The electrification of the truck is crucial to meet the strategic vision of the European Union (EU) to contribute to net-zero greenhouse gas emissions for all sectors of the economy and society. The battery-electric truck is very efficient to reduce the emissions and has also a lower Total Cost of Ownership (TCO) compared to diesel trucks. Thus, the energy consumption of the battery-electric truck needs to be analysed in detail, and the differences in the conventional powertrain, recuperation by regenerative braking during driving and charging during standing, need to be considered. This master thesis aims to analyse the energy consumption of the battery-electric truck during driving and standing charging. For driving cycle simulation the Vehicle Energy Consumption calculation TOol (VECTO) and MATLAB are used. Different variations, such as payload, rolling resistance, air drag, and Power Take Off (PTO), are considered in the driving cycle simulation. The driving cycle simulation is verified by calculating the energy balance and compared with the on-road test results. For the standing charging simulation, MATLAB is used to analyse the charging loss with different battery packs and charging speeds. The results are shown with the Sankey diagram and other illustrative tools. Seen from the simulation results, the usable energy of the battery pack is enough for the truck to complete the designed driving cycle. The main loss in the powertrain is the Power Electronic Converter (PEC) and the electric machine. To increase the range and reduce energy loss, using a higher efficiency PEC and electric machine is an efficient method. For the charging simulation, the current Combined Charging System (CCS) standard charging station can charge the battery-electric truck with adequate voltage and reasonable charging time. The main loss during the charging comes from the charging station.Elektrificering av lastbilen är avgörande för att uppfylla Europeiska Unionens (EUs) strategiska vision att bidra till nettonollutsläpp av växthusgaser för alla sektorer i samhället. Den batterielektriska lastbilen är väldigt effektiv för att reducera utsläppen och är också mer ekonomisk med en lägre Total Cost of Ownership (TCO) jämfört med diesel lastbilar. Således behöver energiförbrukningen för den batterielektriska lastbilen analyseras i detalj, och skillnaderna i den konventionella drivlinan, återhämtning genom regenerativ bromsning under körning och laddning, måste övervägas. Detta examensarbete syftar till att analysera energiförbrukningen för den batterielektriska lastbilen under körning och laddning. För körcykelsimuleringar används the Vehicle Energy Consumption calculation TOol (VECTO) och MATLAB. Olika variationer, såsom nyttolast, rullmotstånd, luftmotstånd och Power Take Off (PTO), beaktas i körcykelsimuleringen. Körcykelsimuleringen verifieras genom att beräkna energibalansen som jämförs med experimentella testresultat utförda på väg. För laddningssimuleringen används MATLAB för att analysera laddningsförlusten med olika batteripaket och laddningshastigheter. Resultaten visas med Sankey diagram och andra illustrativa verktyg. Simuleringsresultaten visar att batteripaketets användbara energi är tillräckligt för att lastbilen ska kunna slutföra den planerade körcykeln. Den största förlusten i drivlinan är kopplat till the Power Electronic Converter (PEC) och den elektriska maskinen. För att öka räckvidden och minska energiförlusten är det ett effektivt sätt att en använda PEC och en elektrisk maskin med högre effektivitet. För laddningssimuleringen kan den nuvarande stationen med Combined Charging System (CCS) standard ladda batteriladdaren med tillräcklig spänning och med rimlig laddningstid. Huvudförlusten under laddningen kommer från laddstationen.
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Nordström, Erik. « Advanced Modelling and Energy Efficiency Prediction for Road Vehicles ». Thesis, Umeå universitet, Institutionen för fysik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-175358.
Texte intégralRésumé :
This thesis presents a first real world case-study of road transport operations that use the COVER format, in which the driver and the vehicle are regarded as separate entities. This format enables a complex representation of the transport operation that potentially better describe reality compared to the conventional representation used in today’s certification tools. The representation of operations treated in this thesis is called Operating Cycles and has been used to fully describe three representative transport missions from a case-study truck. Stochastically generated operating cycles have been used to create a large data set and thus prevent overfitting of specific cycles. The Operating Cycle-representation allowed for fair comparison between vehicle designs and ultimately manifested a vehicle composition that reduced the fuel consumption by nearly 10% for the same kind of transport operations.
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Manning, Peter Christopher. « Development of a Series Parallel Energy Management Strategy for Charge Sustaining PHEV Operation ». Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/49436.
Texte intégralRésumé :
The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2012-2014 EcoCAR 2: Plugging in to the Future Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM) and the U.S. Department of Energy (DOE). The goals of the competition are to reduce well-to-wheel (WTW) petroleum energy consumption (PEU), WTW greenhouse gas (GHG) and criteria emissions while maintaining vehicle performance, consumer acceptability and safety. Following the EcoCAR 2 Vehicle Development Process (VDP) of designing, building, and refining an advanced technology vehicle over the course of the three year competition using a 2013 Chevrolet Malibu donated by GM as a base vehicle, the selected powertrain is a Series-Parallel Plug-In Hybrid Electric Vehicle (PHEV) with P2 (between engine and transmission) and P4 (rear axle) motors, a lithium-ion battery pack, an internal combustion engine, and an automatic transmission.
Development of a charge sustaining control strategy for this vehicle involves coordination of controls for each of the main powertrain components through a distributed control strategy. This distributed control strategy includes component controllers for each individual component and a single supervisory controller responsible for interpreting driver demand and determining component commands to meet the driver demand safely and efficiently. For example, the algorithm accounts for a variety of system operating points and will penalize or reward certain operating points for other conditions. These conditions include but are not limited to rewards for discharging the battery when the state of charge (SOC) is above the target value or penalties for operating points with excessive emissions. Development of diagnostics and remedial actions is an important part of controlling the powertrain safely. In order to validate the control strategy prior to in-vehicle operation, simulations are run against a plant model of the vehicle systems. This plant model can be run in both controller Software- and controller Hardware-In-the-Loop (SIL and HIL) simulations.
This paper details the development of the controls for diagnostics, major selection algorithms, and execution of commands and its integration into the Series-Parallel PHEV through the supervisory controller. This paper also covers the plant model development and testing of the control algorithms using controller SIL and HIL methods. This paper details reasons for any changes to the control system, and describes improvements or tradeoffs that had to be made to the control system architecture for the vehicle to run reliably and meet its target specifications. Test results illustrate how changes to the plant model and control code properly affect operation of the control system in the actual vehicle. The VT Malibu is operational and projected to perform well at the final competition.Master of Science
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Tseng, Hsi-Peng, et 曾喜鵬. « An Explicit Model of Residential Mobility and Housing Choice : The Interpretation Based on Housing Consumption disequilibrium and Housing Adjustment ». Thesis, 2004. http://ndltd.ncl.edu.tw/handle/87840300027993043603.
Texte intégralRésumé :
博士國立臺北大學
都市計劃研究所
92
Residential mobility and home improvement are behaviors commonly seen in the housing market in Taiwan. Both are household’s strategies for adjusting housing consumption to improve the living quality. However, related researches on the topic are scant in Taiwan. This dissertation, by integrating researches on residential mobility and housing choice, established an analytical model from the perspective of housing consumption disequilibrium to explain the household’s housing adjustment behavior. The model begins by conducting a systematic framework to explain the shocks and channels of household’s disequilibrium in housing consumption, and two inferences were conducted subsequently as follows. The first is to discuss the decision made between moving, improving, and no adjustment by households experiencing different housing consumption disequilibrium; the second is to discuss why and how households move from one place to another within a specific metropolitan area when they have chosen moving as the way for adjusting their housing consumption. Three hypotheses were derived from the theoretical framework, and were tested by three empirical studies. The first empirical study was to estimate the factors that influence the household’s decision on housing adjustment strategies choice by using the multinomial logit model. More specifically, the logit model is used to estimate the household’s choice between moving, improving, and no adjustment. The second empirical study was the estimation of mobility flows and housing tenure choices. The movers within Taipei Metropolitan areas were selected as target for empirical test, and the Probit model was used to estimate and calculate the homeownership probabilities for movers of different moving directions, and the probabilities of moving into Taipei City for movers that changed their housing tenure. The third empirical study is to empirically estimate the effects of reasons for moving on the mover’s joint decisions on housing location and housing tenure choice. The joint decision nature was described within the discrete choice models. The effects of the reasons for moving were analyzed by dividing the movers into three groups according to the moving reasons and incorporated into the logit model structure. The results of three empirical studies proved the three hypotheses in some extent. In conclusion, this dissertation deemed the household’s decision on residential mobility and housing choice a continuous decision-making process with interconnected relationship, and established an analytical model that bridges up the above two on theoretical level. This analytical model not only extends the current research issues on residential mobility, some new viewpoints, for example, the effects of reasons for moving on housing demand, were also brought into the current housing studies. Moreover, the probability models were used to empirically estimate three decisions related to residential mobility and housing adjustment strategies choices in Taiwan. The results both from the establishment of analytical model and empirical studies provided further understanding of the housing consumption adjustment behavior in Taiwan, as well as foundations for future researches on residential mobility and housing choice.
Livres sur le sujet "Explicit Powertrain Consumption Model"
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Jappelli, Tullio, et Luigi Pistaferri. The Response of Consumption to Income Risk. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199383146.003.0010.
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Tests of the importance of precautionary saving follow several research strategies. One aims to find a variable (or set of variables) that can approximate the variance of the growth rate of consumption. A second strategy seeks to estimate a reduced form for the level of consumption and wealth with proxies for income risk. A third approach simulates the path of consumption and wealth in models with precautionary saving, matching simulations with the observed distribution of wealth and consumption. Other studies provide indirect evidence for or against the precautionary saving hypothesis. Finally, some papers test the null hypothesis of the precautionary saving model (or more generally, self-insurance), in which risks can only be insured via private savings, against specific alternatives in which researchers make the source of market incompleteness explicit (positing, for instance, that it is due to private information).
Chapitres de livres sur le sujet "Explicit Powertrain Consumption Model"
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Chang, Rui, Yang Liu, Yufeng Cao et Jianqiang Liu. « An Optimal Energy Management Strategy for a Hybrid Train ». Dans Proceedings of the 10th Hydrogen Technology Convention, Volume 1, 475–84. Singapore : Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8631-6_46.
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AbstractThe hybrid trains use hydrogen fuel cells and lithium-iron phosphate batteries as energy sources. The powertrain has the advantage of zero emissions and high energy efficiency due to optimizing the power distribution strategy and the recovery of braking energy. This paper proposes an energy management strategy based on the Dynamic Programming Algorithm (DPA) to optimize the power allocation of both power sources to guarantee the power performance of the train and achieve optimal operation at the cost. The method is based on a dynamic programming algorithm to determine the optimum output power of a hydrogen-fuelled engine. Based on the operating characteristics of the train and the characteristics of the respective power sources, the objective function and constraints are established, and the principles for selecting the parameters of the optimization algorithm are presented. Finally, as a driving condition, the train is operated on a specific line in a minimum time operation. The vehicle model and control strategy designed in Matlab/Simulink environment is jointly simulated and verified. Simulation results show that the proposed optimization strategy results in significant savings in hydrogen consumption for the hybrid train compared to the SOC equalization strategy and better meets the train power performance requirements.
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Ermini, Luigi. « Testing DHSY as a Restricted Conditional Model of a Trivariate Seasonally Cointegrated System ». Dans Cointigration, Causality, and forecating, 230–55. Oxford University PressOxford, 1999. http://dx.doi.org/10.1093/oso/9780198296836.003.0010.
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Abstract The UK consumption function has been analyzed in numerous studies, of which the model developed two decades ago by Davidson, Hendry, Srba and Yeo (1978), henceforth DHSY, is one of the best known and most successful (for a recent survey of these studies, see Muellbauer, 1994). Two main features of DHSY were the explicit modeling of the seasonal patterns present in the data. through fourth-differencing and the presence of an error-correction term, whose central role in the empirical success of DHSY would be better understood a decade later in light of the newly developed literature on cointegration (for example, Granger, 1986); particularly, in light of the Granger representation theorem which formalizes the link between cointegration and error-correction (Engle and Granger, 1987). The introduction of the error-correction term in DHSY was based on intuitive rather than formal arguments to explicitly model the presence of a self-regulating mechanism that would keep consumption and income aligned in the long run.
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Baranzini, Mauro. « The Accumulation of Capital in a Two-Class Life-Cycle Model in Continuous Time ». Dans A Theory of Wealth Distribution and Accumulation, 155–76. Oxford University PressOxford, 1991. http://dx.doi.org/10.1093/oso/9780198233138.003.0006.
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Abstract In the preceding chapter we considered a two-class life-cycle model in which we explicity derived the value of the equilibrium variables of the model, namely the optimal interest rate and rate of profit by which both a steady growth and individuals’ utility maximization are achieved. In order to obtain explicit analytical solutions we considered a very simple two-period model based on some restrictive assumptions which we proceed now to relax in order to observe the effects of the various parameters on a few relevant variables (like initial consumption-, saving-, and accumulation-rates) in a more generalized life-cycle model of income and wealth distribution. Additionally this analysis, with particular reference to the saving- and consumption-rates, will allow us to compare the results obtained in a deterministic life-cycle model with those valid for a corresponding stochastic model (see Chapter 7) in order to observe the effects of uncertainty in a life-cycle model under optimality.
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Rosolem, Letícia Alves dos Santos, Alexandre da Costa Castro, Fernando Deschamps et Edson Pinheiro de Lima. « Associative Data-Process Model in Manufacturing Systems : Application Case in Automotive Industry ». Dans Advances in Transdisciplinary Engineering. IOS Press, 2021. http://dx.doi.org/10.3233/atde210117.
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Considering the advent of Industry 4.0 and development of Cyber-Physical Systems, a large amount of data has been collected in production systems. Available business process recommendations, presented in Business Process Management Notation and Case Management Model Notation frameworks, have been enough to represent the systemic and relational characteristics of production systems and their components. Recommendations for data life-cycle management do not consider explicitly combining the elements of the modeled process and the representative data of the production system assets. In fact, process flows can represent data generated or consumed but do not have an explicit associated action to their data: generation, transformation and consumption. From a Performance Analytics perspective, approaching data and processes in an associated way can be an advantageous practice in management and decision-making. This study uses one investigative experience in the automotive industry, from two aspects: the As-Is mapping of a segment of the measurement system after the welding step, and the design and implementation of Big Data Analytics architecture related to the same process. The result is a proposal of an associative framework between processes and related data, which are following the recommendations of currently applied frameworks for Business Process Management and Big Data Analytics.
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Sánchez-López, Nuria, Andrew T. Hudak, Luigi Boschetti, Carlos A. Silva, Benjamin C. Bright et E. Louise Loudermilk. « A spatially explicit model of litter accumulation in fire maintained longleaf pine forest ecosystems of the Southeastern USA ». Dans Advances in Forest Fire Research 2022, 1383–89. Imprensa da Universidade de Coimbra, 2022. http://dx.doi.org/10.14195/978-989-26-2298-9_209.
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The continuity and depth of the surface fuel layer (i.e., litter and duff) are major drivers of fire spread and fuel consumption. Nevertheless, its spatial explicit quantification over relatively large areas remains unresolved: local fuel heterogeneity introduces large uncertainties in estimates derived from field-based models and sparse data samples. Besides that, the sensitivity of remote sensors to surface litter loads is limited, particularly under canopy cover. In fire-maintained pine forests of the Southeastern US, surface fuel accumulation and its distribution over the forest floor are mainly driven by vegetation productivity, decomposition, and time since fire (TSF). Traditional ecological and stand-level models provide a means to equilibrate between opposing rates of deposition and decomposition as a function of TSF at the landscape level but don’t account for spatial heterogeneity. We developed a top-down, object-based approach for wall-to-wall estimation of surface litter loads using TSF records, the ecological-based Olson model, and tree crown objects derived from airborne laser scanning (ALS) data. The approach involves, first, the spatially explicit estimation of litter production through a tree crown production model, driven by tree crown attributes extracted from the ALS point clouds, and informed by tree inventory data and allometric equations, including vegetation leaf turnover rates. Second, litter accumulation is estimated using the fire-driven Olson equation, which models accumulation progressively with time until decomposition balances deposition and a steady state of accumulation is reached. The methodology is demonstrated at several fire-maintained longleaf pine forest locations in southeastern USA, where tree inventory data, surface litter loads, prescribed fire records, and ALS data are available for testing and validation of the methodology. Comparison between preliminary modeled estimates and observed litter loads shows a relatively good agreement (RMSE=0.21 [kg m-2]; BIAS 0.07 [kg m-2]). This suggests that the proposed approach to indirectly map patterns of litter production and litter accumulation can provide a realistic means to map the continuity of the litter layer, thus overcoming the limitation of traditional ecological landscape models to account for spatial heterogeneity. This high-resolution map of litter loads will be further valuable as input to physics-based fire behavior and spread models and to improve the spatially explicit characterization of the duff layer.
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Karaosman, Hakan, et Alessandro Brun. « The Myth of Sustainability in Fashion Supply Chains ». Dans Supply Chain and Logistics Management, 160–88. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0945-6.ch008.
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The global fashion market is expected to account for €1,512 billion by 2018. Yet, the fashion industry is associated with critical environmental and social impact due to extensive material use, energy consumption, and safety issues. Therefore, in contrast to traditional supply chain management (SCM), a more sustainable SCM must be introduced by the explicit integration of environmental and social objectives. This study attempts to synthesise both existing and new elements in comprehensive frameworks. The main contribution of this chapter is the application of an assessment tool to evaluate the impact of SC operations on sustainability. Subsequently, a performance measurement model is proposed to assess to what extent the level of sustainability could affect the operational performance areas. An adequate understanding of how SC of a fashion company could be configured toward sustainability, how sustainability must be assessed, and how SSCM performance could be measured is provided through this chapter.
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Kroncke, Jedidiah J. « Legal Innovation as a Global Public Good ». Dans The Global South and Comparative Constitutional Law, 110–38. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198850403.003.0005.
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How to promote broader adoption of rigorous comparative legal analysis among legal and non-legal scholars has been a traditional challenge for comparative lawyers. At the same time, historical legacies have ingrained cross-cultural presumptions about the global flows of comparative legal knowledge that warps productive learning on both sides of most traditional national asymmetries. Yet the use of legal comparison, either explicit or implicit, has only increased in recent decades, with forms of comparative legal analysis often carried out in multiple disciplines in which comparative law and comparative lawyers are, at best, incidental. This chapter confronts this issue by advancing the ideal of the comparative lawyer as indigenizer whose primary function is to make productive use of foreign legal innovation conceptualized as a global public good. The chapter first posits a thought experiment regarding ‘regulatory patents’ to consider the natural advantages of this self-interested model of comparative lawyering, and then proceeds to think through how it would work to create a more productive dialogue between countries traditionally see as being part of the Global ‘North’ and ‘South’. It then considers the individual imperatives this perspective places on comparative lawyers in their interactions with other scholars but also in their pedagogical roles in law schools which serve as key sites for reproducing unhealthy patterns regarding the production and consumption of comparative legal knowledge.
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Linn, Rodman, Scott Goodrick, Sara Brambilla, David Robinson, Michael Brown, Carolyn Sieg, Joseph O’Brien, Russell Parsons et John Kevin Hiers. « QUIC-Fire : Initial capabilities of a fast-running simulation tool for prescribed fire applications ». Dans Advances in Forest Fire Research 2022, 335–37. Imprensa da Universidade de Coimbra, 2022. http://dx.doi.org/10.14195/978-989-26-2298-9_53.
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Prescribed fire is increasingly being looked to as a tool that can support land and fire managers in their efforts towards ecological sustainability and wildfire risk management. As prescribed fire use is considered for treatment of more acres and in more complex settings, practitioners are having to work harder to meet their expanding treatment goals in a safe and environmentally responsible manner. In the context of a prescribed fire, the role of multiple ignitions and complex fire geometries depends heavily on feedbacks between the fire and atmosphere and accentuates the need for explicit representation of these processes in any modeling tools that are to be used to support prescribed fire managers. Computational fluid dynamics models like FIRETEC and WFDS are inherently capable of representing this interaction, but they are too computationally expensive for widespread uses by practitioners for exploration and analysis. We have developed a new simulation tool called QUIC-Fire to capture these fire/atmosphere feedbacks while being orders of magnitude less computationally expensive by coupling the fast-running 3-D rapid wind solver QUIC-URB to a physics-based cellular automata fire spread model Fire-CA. Here we describe some of the model basics and provide initial demonstration capabilities of a new fast-running modeling tool, QUIC-Fire, that can be applied to prescribed fire planning. QUIC-Fire provides a self-determining fire prediction capability that represents the critical coupled fire/atmosphere feedbacks at scales relevant for prescribed fire. Although, the development of this model is in the nascent stages, initial results show an encouraging capability to capture basic trends in fire behavior, response of fire spread to size of fire, consumption of canopy fuels in prescribed fire scenarios, interaction between multiple firelines and response to heterogeneity in vegetation. Its ability to model response to both ignition patterns and a temporally and spatially variable fire environment without computational expense of CFD solutions is encouraging.
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Franses, Philip Hans. « Are Seasons, Trends, and Cycles always Independent ? » Dans Periodicity and Stochastic Trends In Economic Time Series, 79–91. Oxford University PressOxford, 1996. http://dx.doi.org/10.1093/oso/9780198774532.003.0006.
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Abstract When an economic time series displays seasonal variation that seems to in crease with an increasing trend, we usually analyse the data after a natural log arithm transformation. An alternative strategy is to construct an explicit model for the increasing seasonal variation using, for example, seasonal dummy variables which interact with linear trends. (See Bowerman et al. (1990) for a comparison of the two approaches.) The use of logarithmic data seems particularly useful when an untransformed series y1can be decomposed There are however economic variables for which seasonal and nonseasonal variation may not be separated just by taking logs. (See Wisniewski (1934) for an early reference to the interdependence of cyclical and seasonal variation and Hylleberg (1994) for a recent discussion.) This may be caused by, say, eco nomic agents who can behave differently in recessions than in expansions, thereby establishing different seasonal patterns across these regimes. For ex ample, some retail sales variables may show peaks in the clearance sales sea sons, where the start and length of those seasons can depend on the current state of the economy. As another example, the growth in disposable income in several industrialized countries has created the possibility of people having more than one holiday per year, and this can have an effect on the seasonal pat tern in nondurables consumption. For some economic time series, therefore, it may not be easy (or even possible) strictly to isolate seasonal and nonseasonal components since the nonseasonal and seasonal fluctuations can interact.
Actes de conférences sur le sujet "Explicit Powertrain Consumption Model"
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Zhao, Junfeng, et Junmin Wang. « Model Predictive Control of Integrated Hybrid Electric Powertrains Coupled With Aftertreatment Systems ». Dans ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-5999.
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For hybrid electric vehicles (HEVs), especially for diesel-electric hybrid vehicles, the low exhaust gas temperature induced by the hybridization and fuel economy optimization will bring significant impact on the performance of the exhaust gas aftertreatment systems, and may consequently lead to violation of the tailpipe emission constraints. To investigate the influence of diesel powertrain hybridization on the aftertreatment system and tailpipe emissions, an integrated HEV model is established by incorporating the thermodynamics models of the aftertreatment systems. This comprehensive model is able to predict engine-out nitrogen oxides (NOx) concentration, exhaust gas temperature, and to describe the temperature dynamics in the aftertreatment systems. A static map of selective catalytic reduction (SCR) system temperature-dependent de-NOx efficiency is utilized, so that the tailpipe NOx can be predicted. To investigate the tradeoff between fuel consumption and emissions for diesel HEV with aftertreatment systems, a preliminary study is carried out on optimally balancing both aspects via a model predictive control scheme. This controller is designed with an explicit consideration of HEV tailpipe NOx emission constraint. The simulation results show that the HEV tailpipe NOx emissions can be regulated by slightly sacrificing the fuel economy.
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Fandakov, Alexander, Paul Tourlonias, Alexander Herzog, Emre Özkan, Ronny Kurt Mehnert et Marc Sens. « Model-Based Energy Consumption Optimization of a Twin Battery Concept Combining Liquid and Solid-State Electrolyte Cells ». Dans 16th International Conference on Engines & Vehicles. 400 Commonwealth Drive, Warrendale, PA, United States : SAE International, 2023. http://dx.doi.org/10.4271/2023-24-0154.
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<div class="section abstract"><div class="htmlview paragraph">The majority of powertrain types considered important contributors to achieving the CO<sub>2</sub> targets in the transportation sector employ a battery as an energy storage device. The need for batteries is hence expected to grow drastically with increasing market share of CO<sub>2</sub>-optimized powertrain concepts. The resulting huge pressure on the development of future electrochemical energy storage systems necessitates the application of advanced methodologies enabling a fast and cost-efficient concept definition and optimization process. This paper presents a model-based methodology for the optimization of BEV thermal management concept layouts and operation strategies targeting minimized energy consumption. Starting at the vehicle level, the proposed methodology combines appropriate representations of all primary powertrain components with 1D cooling and refrigerant circuit models and focuses on their interaction with the battery chemistry. To this end, the battery cells are thermally modeled in 3D, complemented by a P2D electro-physicochemical approach. Thanks to online coupling the cell representation with the 1D powertrain and thermal management models, heat transfer and cell temperatures can be calculated as a function of the boundary conditions at each simulation step. The model-based methodology is subsequently employed for the optimization of a novel Twin Battery concept combining sodium-ion and solid-state lithium-ion battery cells. The approach enables the cost-efficient adaption of both thermal management layout and operation strategy, resulting in reduced energy input and shorter time required for reaching operation temperature of the solid-state cells. Ultimately, a minimization of the overall powertrain energy consumption can be achieved while ensuring chemistry-specific optimal temperature levels and hence reduced battery aging.</div></div>
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Stockar, Stephanie, Cristian Rostiti, Marcello Canova et Michael Prucka. « A Model Predictive Approach for the Coordination of Powertrain Control Systems ». Dans ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/dscc2019-9146.
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Abstract The design, calibration and integration of powertrain control algorithms has become significantly more complex in recent years, as the automotive industry faces increasing challenges in meeting consumer requirements and government regulations. Traditionally, the powertrain control engineering design process develops the engine and transmission controllers independently and then integrates them after an initial calibration. This process can lead to suboptimal performance and requires additional calibration and verification steps to improve the coordination of the various subsystems. This paper proposes a novel approach to achieve a systematic, high-level coordination, and optimization of the control strategy in an automotive powertrain system that will reduce overall calibration effort. Optimized set-points for engine and transmission controls are generated based on joint optimization of fuel consumption and drivability using Model Predictive Control to manage both continuous and discrete control variables. Simulation results confirm the control decisions made by the proposed coordinator match a well-calibrated production ECU with little tuning effort.
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Goodenough, Bryant, Alexander Czarnecki, Darrell Robinette, Jeremy Worm, Phil Latendresse et John Westman. « Reducing Fuel Consumption on a Heavy-Duty Nonroad Vehicle : Conventional Powertrain Modifications ». Dans WCX SAE World Congress Experience. 400 Commonwealth Drive, Warrendale, PA, United States : SAE International, 2023. http://dx.doi.org/10.4271/2023-01-0466.
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<div class="section abstract"><div class="htmlview paragraph">This investigation focuses on conventional powertrain technologies that provide operational synergy based on customer utilization to reduce fuel consumption for a heavy-duty, nonroad (off-road) material handler. The vehicle of interest is a Pettibone Cary-Lift 204i, with a base weight of 50,000 lbs. and a lift capacity of 20,000 lbs. The conventional powertrain consists of a US Tier 4 Final diesel engine, a non-lockup torque converter, a four-speed powershift automatic transmission, and all-wheel drive. The paper will present a base vehicle energy/fuel consumption breakdown of propulsion, hydraulic and idle distribution based on a representative end-user drive cycle. The baseline vehicle test data was then used to develop a correlated lumped parameter model of the vehicle-powertrain-hydraulic system that can be used to explore technology integration that can reduce fuel consumption. Two conventional powertrain modifications are explored that provide potential pathways that significantly alter the base powertrain and include 1.) a torque converter disconnect clutch and 2.) a low voltage stop-start system that have the potential to reduce fuel consumption on the end user representative drive cycle by 10.3% and 9.8%, respectively. Details of how the powertrain modifications would be executed, physical hardware, and application to other heavy-duty nonroad vehicle applications are included in the discussion.</div></div>
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Aletras, Nikolaos, Dimitrios Besinas, Georgios Livitsanos, Grigorios Koltsakis, Zissis Samaras et Leonidas Ntziachristos. « Control Algorithms for xEV Powertrain Efficiency and Thermal Comfort ». Dans 16th International Conference on Engines & Vehicles. 400 Commonwealth Drive, Warrendale, PA, United States : SAE International, 2023. http://dx.doi.org/10.4271/2023-24-0142.
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<div class="section abstract"><div class="htmlview paragraph">This paper investigates how different on-board energy management system (EMS) algorithms can affect the total energy consumption considering propulsion, heating, ventilation, and air conditioning (HVAC) operation and thermal comfort requirements. Firstly, an integrated plug-in hybrid electric vehicle (PHEV) powertrain and HVAC model including vehicle cabin has been developed as a demonstrator. Two different EMS algorithms - namely a rule-based and an equivalent consumption minimization strategy (ECMS) one - are applied to the integrated PHEV model and evaluated under different environmental conditions. The results showed that the HVAC system operation affects the total energy consumption benefits when ECMS algorithm is used over the rule-based. ECMS reduces the total energy consumption by 2.5% compared to rule-based without HVAC operation, while the total energy consumption reduction changes to 5.3% and 6.3% when HVAC provides heating and cooling power respectively. Furthermore, the ECMS algorithm can reach the target of sufficient thermal comfort 1 minute earlier than rule-based in WLTC cycle. Based on the above findings we recommend evaluating the EMS algorithms with integrated propulsion and the HVAC system modeling. By applying it to real EMS unit energy consumption reduction of new vehicles under real-world operating conditions can be expected.</div></div>
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Huang, Wei, Yujun Zhang, Duode Qian et Biqian Hu. « An Operating Point Adjustment Model Using PMP-GWO-Bi-LSTM for RANGE Extended Electric Vehicle ». Dans SAE 2023 Vehicle Powertrain Diversification Technology Forum. 400 Commonwealth Drive, Warrendale, PA, United States : SAE International, 2023. http://dx.doi.org/10.4271/2023-01-7020.
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<div class="section abstract"><div class="htmlview paragraph">The increasingly severe energy problems and environmental pollution have imposed severe requirements on the fuel saving level of vehicles. The range extender configuration is a tandem structure that has attracted more and more researchers’ attention due to its architectural features and control methods. An intelligent APU operating point adjustment model based on PMP-GWO-Bi-LSTM is proposed in this paper to enhance adaptability to real driving conditions for the traditional optimal strategy. Firstly, a PMP model has been applied into a range extended electric vehicle model from which the optimized power distribution data under several standard driving cycles was recorded as the input to deep learning model. Secondly, a Bi-LSTM model fed by control parameters and power distribution data was established and trained using aforementioned datasets. The aim is to learning the nonlinear regression relationship model between APU control variables and power distribution. Furthermore, the GWO optimization algorithm is introduced to optimize the hyperparameter of Bi-LSTM to speed up the running speed of the model and improve accuracy. Finally, the experiment was conducted using real driving condition data to predict the power distributions. The simulation results show APU overall efficiency improvement by 15.87% whilst fuel consumption improved by 9.42%. The number of hyper parameters such as the iterations and hidden layer units using GWO optimization algorithm is 35.50% and 38.38% less and the training time decreases by 4.61 s, which proves that the model proposed in this paper can achieve good result in real driving conditions.</div></div>
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Wu, Haotian, et Haiyan Zhang. « Model-Based Design and Evaluation of Electric Vehicle Powertrain With Independent Driving Motors ». Dans ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47980.
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The transfer case based all-wheel drive electric vehicle (TCAWDEV) and dual-axle AWDEV have been investigated to balance concerns about energy consumption, drivability and stability of vehicles. An ideal AWDEV (IAWDEV) powertrain architecture is proposed by this research; the architecture has an independent driving motor at each wheel; in essence, the IAWDEV is a distributed powertrain that provides various combinations of torque vector control. This research also investigated the simplified methods to estimate the battery capacity and the operation envelope of motors, and employed model-based evaluation approaches to recursively identify the proper powertrain components. The model-based evaluation was conducted in LMS AMESim. The results show that the IAWDEV could reduce the complexity of drivetrain, and also can harvest more braking energy under poor road contact.
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Phlips, Patrick. « Simple Hybrid Electric Vehicle Operating and Fuel Consumption Model ». Dans WCX SAE World Congress Experience. 400 Commonwealth Drive, Warrendale, PA, United States : SAE International, 2024. http://dx.doi.org/10.4271/2024-01-2153.
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<div class="section abstract"><div class="htmlview paragraph">An analytic first-order fuel consumption model is developed for FWD 2-motor HEV vehicles which on average achieve 36% EPA Combined efficiency. The premise of this paper is that this is primarily the result of new functionality specific to HEV. Detailed benchmarking data show that in such an HEV the engine not only provides traction power but simultaneously charges the battery. This combined operation of engine and electric powertrain is unique to HEV and is studied using their linear transfer functions. Charging by the engine enables extended electric driving at low traction power, which reduces engine running time and the associated overhead. The analysis predicts an engine duty cycle proportional to the traction power and inversely proportional to the engine output power: the electric driving is limited by the engine’s ability to deliver the required traction work. The model equations in terms of the major functional parameters predict engine running time fractions of 15% for the EPA urban Bag 2 test and 54% on the EPA Highway test, versus observed values of 15% and 51%. As the small HEV High Voltage battery provides little net charge over a trip, the fuel consumption is proportional to the sum of the net engine work and the reduced, proportional overhead. On low power regulatory cycles, the fuel consumption changes from ‘constant overhead’ in classical ICEV to ‘constant high efficiency’ in HEV. Cycle efficiencies of 37 and 36% are predicted for the urban Bag 2 and Highway tests for a generic vehicle.</div></div>
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Angerer, Christian, Sebastian Krapf, Alexander Buß et Markus Lienkamp. « Holistic Modeling and Optimization of Electric Vehicle Powertrains Considering Longitudinal Performance, Vehicle Dynamics, Costs and Energy Consumption ». Dans ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-85430.
Texte intégralRésumé :
The authors provide a copious literate review on powertrain design optimization for electric vehicle (EV) powertrains. The review shows a gap in the state of science regarding the consideration of all customer relevant requirements. Existing approaches either focus on performance and energy consumption or concentrate on vehicle dynamics. Based on this insight, the authors analyze customer requirements and derive all vehicle properties that are influenced by the powertrain concept. They find that costs, longitudinal performance, lateral dynamics, off-road capabilities and energy consumption are key vehicle properties. The powertrain concept affects all these properties and thus determines the satisfaction of customer requirements. Subsequently the authors describe a vehicle simulation model that represents all predefined customer requirements in dependence on the powertrain concept design.
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Jiang, Y. T., Xinxin Zhao et J. G. Zhang. « Optimization of Energy Management Strategy for Multi-Mode Hybrid Transmission Based on Condition Prediction ». Dans SAE 2023 Vehicle Powertrain Diversification Technology Forum. 400 Commonwealth Drive, Warrendale, PA, United States : SAE International, 2023. http://dx.doi.org/10.4271/2023-01-7032.
Texte intégralRésumé :
<div class="section abstract"><div class="htmlview paragraph">Since there are no typical working conditions in the field of engineering vehicles, this paper implements the construction of driving conditions based on Markov stochastic model and energy management strategy of a multi-mode hybrid mine dump truck based on dynamic programming algorithm under this background. Firstly, on the basis of existing vehicle driving data, we calculate the velocity transfer probability matrix with the Markov stochastic model, and then construct the vehicle driving condition after predicting the velocity. The constructed working conditions are applied to the energy management strategy of dynamic programming algorithm to calculate the energy consumption of the hybrid mining truck. It is proved that this construction method can be applied to the hybrid electric mine dump truck, and the DP based energy management strategy has lower energy consumption.</div></div>
Rapports d'organisations sur le sujet "Explicit Powertrain Consumption Model"
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Golub, Alla, Benjamin Henderson, Thomas Hertel, Steven Rose, Misak Avetisyan et Brent Sohngen. Effects of GHG Mitigation Policies on Livestock Sectors. GTAP Working Paper, juillet 2010. http://dx.doi.org/10.21642/gtap.wp62.
Texte intégralRésumé :
In this paper we have investigated effects of GHG mitigation policies on livestock sectors. We used a global computable general equilibrium GTAP-AEZ-GHG model with explicit unique regional land types, land uses and related GHG emissions. The model is then augmented with cost and GHG response information from partial equilibrium approaches to abatement of land-based greenhouse gas emissions. With this framework we analyze changes in regional livestock output, sector competitiveness and regional food consumption under different climate change mitigation policy regimes. Scenarios we have considered differ by participation/exclusion of agricultural sectors and non-Annex I countries, as well as policy instruments. The imposition of carbon tax in agriculture has adverse affects on food consumption, especially in developing countries. The reductions in food consumption are smaller if the agricultural producer subsidy is introduced to compensate for carbon tax the producers pay. The global forest carbon sequestration subsidy effectively controls emission leakage when carbon tax is imposed only in Annex I regions. The sequestration subsidy bids land away from agriculture in non-Annex 1 regions and prevents expansion of agricultural sectors. Though the sequestration subsidy allows reduction of GHG emissions, if implemented, the policy may adversely affect food security and agricultural development in developing countries.