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Статті в журналах з теми "Comprehensive powertrain and vehicle model"

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Wang, Yu, Enli Lü, Huazhong Lu, Nong Zhang, and Xingxing Zhou. "Comprehensive design and optimization of an electric vehicle powertrain equipped with a two-speed dual-clutch transmission." Advances in Mechanical Engineering 9, no. 1 (January 2017): 168781401668314. http://dx.doi.org/10.1177/1687814016683144.

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Анотація:
This article develops a systematic model to study electric vehicle powertrain system efficiency by combining a detailed model of two-speed dual-clutch transmission system efficiency losses with an electric vehicle powertrain system model. In this model, the design factors including selection of the electric machine, gear ratios’ change, multi-plate wet clutch design, and gear shift schedule design are considered. Meanwhile, the application of detailed model for drag torque losses in the gearbox is discussed. Furthermore, the proposed model, developed with the MATLAB/Simulink platform, is applied to optimize/maximize the efficiency of the electric vehicle powertrain system using genetic algorithms. The optimization results demonstrate that the optimal results are different between simulations via New Europe Drive Cycle and Urban Dynamometer Driving Schedule, and comprehensive design and optimization of the powertrain system are necessary.
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Salamone, Sara, Basilio Lenzo, Giovanni Lutzemberger, Francesco Bucchi, and Luca Sani. "On the Investigation of Energy Efficient Torque Distribution Strategies through a Comprehensive Powertrain Model." Sustainability 13, no. 8 (April 20, 2021): 4549. http://dx.doi.org/10.3390/su13084549.

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Анотація:
In electric vehicles with multiple motors, the torque at each wheel can be controlled independently, offering significant opportunities for enhancing vehicle dynamics behaviour and system efficiency. This paper investigates energy efficient torque distribution strategies for improving the operational efficiency of electric vehicles with multiple motors. The proposed strategies are based on the minimisation of power losses, considering the powertrain efficiency characteristics, and are easily implementable in real-time. A longitudinal dynamics vehicle model is developed in Simulink/Simscape environment, including energy models for the electrical machines, the converter, and the energy storage system. The energy efficient torque distribution strategies are compared with simple distribution schemes under different standardised driving cycles. The effect of the different strategies on the powertrain elements, such as the electric machine and the energy storage system, are analysed. Simulation results show that the optimal torque distribution strategies provide a reduction in energy consumption of up to 5.5% for the case-study vehicle compared to simple distribution strategies, also benefiting the battery state of charge.
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Wu, Jinglai, Bing Wang, and Xianqian Hong. "Driving Torque Control of Dual-Motor Powertrain for Electric Vehicles." Actuators 11, no. 11 (November 3, 2022): 320. http://dx.doi.org/10.3390/act11110320.

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Анотація:
This paper investigates the driving torque control method for the dual-motor powertrain in electric vehicles (EVs) to achieve the performance of accurate vehicle speed tracking, seamless driving mode shift, and high energy efficiency. The configuration of the dual-motor powertrain is based on the parallel axle transmission structure, which does not contain any clutch or synchronizer. The powertrain provides three driving modes that are two single-motor driving modes and one dual-motor combined driving mode. A detailed dynamic model of the dual-motor powertrain is built to simulate the dynamic response of an EV. An energy management strategy (EMS) is used to select the driving mode and determine the ideal driving torque of two motors. The dynamic control strategy tries to track the ideal vehicle speed when uncertain parameters existed and avoid power interruption or impact during the mode shift. Three dynamic control strategies are proposed, which are the backward dynamic control strategy (BDCS), combined forward and backward dynamic control strategy (CFBDCS), and nested forward and backward dynamic control strategy (NFBDCS). The simulation results demonstrate that the NFBDCS has the best comprehensive performance in vehicle speed tracking, seamless mode shift, and good system energy efficiency.
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Vora, Ashish P., Xing Jin, Vaidehi Hoshing, Gregory Shaver, Subbarao Varigonda, and Wallace E. Tyner. "Integrating battery degradation in a cost of ownership framework for hybrid electric vehicle design optimization." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 6 (October 21, 2018): 1507–23. http://dx.doi.org/10.1177/0954407018802663.

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Анотація:
Prior design optimization efforts do not capture the impact of battery degradation and replacement on the total cost of ownership, even though the battery is the most expensive and least robust powertrain component. A novel, comprehensive framework is presented for model-based parametric optimization of hybrid electric vehicle powertrains, while accounting for the degradation of the electric battery and its impact on fuel consumption and battery replacement. This is achieved by integrating a powertrain simulation model, an electrochemical battery model capable of predicting degradation, and a lifecycle economic analysis (including net present value, payback period, and internal rate of return). An example design study is presented here to optimize the sizing of the electric motor and battery pack for the North American transit bus application. The results show that the optimal design parameters depend on the metric of interest (i.e. net present value, payback period, etc.). Finally, it is also observed that the fuel consumption increases by up to 10% from “day 1” to the end of battery life. These results highlight the utility of the proposed framework in enabling better design decisions as compared to methods that do not capture the evolution of vehicle performance and fuel consumption as the battery degrades.
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Holjevac, Nikola, Federico Cheli, and Massimiliano Gobbi. "Multi-objective vehicle optimization: Comparison of combustion engine, hybrid and electric powertrains." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 234, no. 2-3 (July 4, 2019): 469–87. http://dx.doi.org/10.1177/0954407019860364.

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Анотація:
The use of optimization techniques has been extensively adopted in vehicle design and with the increasing complexity of systems, especially with the introduction of new technologies, it plays an even more significant role. Market competition, stringent mandatory emission regulations and the need for a future sustainable mobility have raised questions over conventional vehicles and are pushing toward new cleaner and eco-friendly solutions. Fulfilling this target without sacrificing the other vehicle’s requirements leads to extremely challenging tasks for vehicle designers. The use of virtual prototyping emerges as a possible breakthrough allowing to rapidly assess the effect of design changes and the impact of new technologies. The study presented in this work provides a suitable approach to compare different vehicle powertrain architectures through optimization techniques and deploying model-based simulation to rapidly assess vehicle performances. The vehicle model is defined at the components level through scalable models obtained from based on detailed simulation. An optimal energy management is applied to the power sources and transmission gear shifting. The optimization technique consider the main design variables of the various components including vehicle chassis and extensively exploits the design space. The multi-objective optimization considers vehicle’s consumption, emission, range, longitudinal and lateral dynamics, costs and further performances to comprehensively assess the vehicle. The results allow to compare four different powertrain architectures: combustion engine vehicle, hybrid electric vehicle with parallel and series configuration, and battery electric vehicle. The results allows furthermore to identify technological limitations and conflicts among the different objectives. A critical analysis over the main design variables allows to identify the more suitable values and in particular, for combustion engine, gearbox and electric traction drive detailed comparisons are provided.
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Liu, Yanwei, Jiansheng Liang, Jiaqing Song, and Jie Ye. "Research on Energy Management Strategy of Fuel Cell Vehicle Based on Multi-Dimensional Dynamic Programming." Energies 15, no. 14 (July 18, 2022): 5190. http://dx.doi.org/10.3390/en15145190.

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Анотація:
The powertrain of a fuel cell vehicle typically consists of two energy sources: a proton electrolyte membrane fuel cell (PEMFC) stack and a battery package. In this paper, multi-dimensional dynamic programming (MDDP) is used to solve the energy management strategy (EMS) of fuel cell hybrid powertrain. This study built a fuel cell hybrid powertrain model, in which the battery model is built based on the Thevenin equivalent circuit. In order to improve the calculating efficiency and maintain the accuracy of the algorithm, the state variables in each stage are divided into primary and secondary. In the reverse solution process, the corresponding relationship between the multi state variables grid and the optimal cumulative function has been changed from three-dimensional to two-dimensional. The EMS based on MDDP is applied to component sizing of a commercial vehicle. Simulations were conducted using MATLAB under the C-WTVC working condition. By analyzing the fuel economy and system durability, the optimal component combination of comprehensive performance is obtained. Compared with the EMS based on dynamic programming (DP), the proposed method effectively improves the calculation accuracy: the hydrogen consumption can be reduced by 3.10%, and the durability of the fuel cell and battery can be improved by 1.08% and 0.13%, respectively.
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Decker, Lukas, Daniel Förster, Frank Gauterin, and Martin Doppelbauer. "Physics-Based and Data-Enhanced Model for Electric Drive Sizing during System Design of Electrified Powertrains." Vehicles 3, no. 3 (August 8, 2021): 512–32. http://dx.doi.org/10.3390/vehicles3030031.

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Анотація:
In multi-drive electrified powertrains, the control strategy strongly influences the component load collectives. Due to this interdependency, the component sizing becomes a difficult task. This paper comprehensively analyses different electric drive system sizing methods for multi-drive systems in the literature. Based on this analysis, a new data-enhanced sizing approach is proposed. While the characteristic is depicted with a physics-based polynomial model, a data-enhanced limiting function ensures the parameter variation stays within a physically feasible range. Its beneficial value is demonstrated by applying the new model to a powertrain system optimization. The new approach enables a detailed investigation of the correlations between the characteristic of electric drive systems and the overall vehicle energy consumption for varying topologies. The application results demonstrate the accuracy and benefit of the proposed model.
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Wu, Jianpeng, Biao Ma, Heyan Li, and Jikai Liu. "Creeping control strategy for Direct Shift Gearbox based on the investigation of temperature variation of the wet multi-plate clutch." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 14 (March 21, 2019): 3857–70. http://dx.doi.org/10.1177/0954407019836313.

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Анотація:
Proposing an appropriate control strategy is an effective and practical way to address the overheat problems of the wet multi-plate clutches in Direct Shift Gearbox under the long-time creeping condition. To do so, the temperature variation of the wet multi-plate clutch is investigated first by establishing a thermal resistance model for the gearbox cooling system. To calculate the generated heat flux and predict the clutch temperature precisely, the friction torque model is optimized by introducing an improved friction coefficient, which is related to the pressure, the relative speed and the temperature, before being demonstrated experimentally using a full scale powertrain test. After that, the verified heat transfer model and the reasonable friction torque model are employed by the vehicle powertrain model to construct a comprehensive co-simulation model for the Direct Shift Gearbox vehicle, capable of simulating the dynamic responses and predicting the temperature variations of two clutches. A creeping control strategy is then proposed and, to evaluate the vehicle performance, the safety temperature (250°C) is particularly adopted as an important metric. From the variations in torque and speed obtained from the simulation results, the vehicle can track the desired speed (1.5 km/h) satisfactorily, with only 3% fluctuation, and have good longitudinal dynamic performance (8.5 m/s3). But above all, during the entire 174 s creeping process, the temperature of two clutches is always under the safety value (250°C), which demonstrates the effectiveness of the proposed control strategy in avoiding the thermal failures of clutches.
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Qi, Xiaowei, Yiyong Yang, Xiangyu Wang, and Zaobei Zhu. "Analysis and optimization of the gear-shifting process for automated manual transmissions in electric vehicles." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 231, no. 13 (January 27, 2017): 1751–65. http://dx.doi.org/10.1177/0954407016685461.

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Анотація:
In recent years, it has been a trend for an automated manual transmission to be adopted as the powertrain for an electric vehicle. However, the strong degrees of jerk and power interruption during the gear-shifting process affect the shifting quality and restrict the application of automated manual transmissions. Therefore, it is a currently popular research topic to find an optimal method to improve the shifting qualities of automated manual transmissions. In this paper, the clutchless shifting process is analysed on the basis of a dynamics model of an automated manual transmission in an electric vehicle, and the parameters are optimized to improve the shifting quality using a defined comprehensive evaluation index. First, the dynamics model of the shifting process for an automated manual transmission is established by considering the stiffness, the damping and the non-linearity contact backlash of the gear mesh and the synchronizer. The whole shifting process is carried out in MATLAB/Simulink and compared with that in the Adams model and bench experiments to prove the accuracy of the dynamics model. Then, the factors of the shifting quality, which include the shifting force and the control accuracy of the speed of the driving motor, are quantified. With the comprehensive evaluation index, all the main factors are described in a cobweb model diagram to find the optimal parameters of the shifting process. The results show that the comprehensive evaluation index can be reduced by 23% by regulating the parameters of the shifting process. This study may be conducive to improving the shifting quality of automated manual transmissions in electric vehicles.
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Zhang, Zhe, Haitao Ding, Konghui Guo, and Niaona Zhang. "A Hierarchical Control Strategy for FWID-EVs Based on Multi-Agent with Consideration of Safety and Economy." Energies 15, no. 23 (December 1, 2022): 9112. http://dx.doi.org/10.3390/en15239112.

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Анотація:
In this study, a hierarchical chassis control strategy is designed to enhance vehicle economy and safety for four-wheel independent-drive electric vehicles (FWID-EVs). In the upper-level, a vehicle dynamics model based on multiple agents is proposed, and a distributed model predictive control (DMPC) method is designed to dimensionally solve the problem of tracking the center-of-mass torque of the demanded velocity trajectory and stability parameters. In the bottom-level, a multi-objective torque distribution strategy that weighs safety, dynamics and economy based on multi-agent theory is designed by comprehensively considering the motor efficiency and tire energy loss. Finally, a hardware-in-the-loop (HIL) simulation platform is built to verify the method formulated in this paper. The results show that the method in this paper is effective in tracking the desired trajectory and further enhancing the stability of the vehicle under various conditions. Compared with other algorithms, while guaranteeing safety and dynamics, the energy consumption of the powertrain is reduced by 9.51%.
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Дисертації з теми "Comprehensive powertrain and vehicle model"

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ZANELLI, ALESSANDRO. "Development of a Comprehensive 0-1D Powertrain and Vehicle Model for the Analysis of an Innovative 48 V Mild-Hybrid Diesel Passenger Car." Doctoral thesis, Politecnico di Torino, 2020. http://hdl.handle.net/11583/2842511.

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Gambhira, Ullekh Raghunatha. "Powertrain Optimization of an Autonomous Electric Vehicle." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1532039436244217.

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Zeng, Xiangrui. "Optimally-Personalized Hybrid Electric Vehicle Powertrain Control." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1471342105.

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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.

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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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Zetterlund, Olof. "Optimization of Vehicle Powertrain Model Complexity for Different Driving Tasks." Thesis, Linköpings universitet, Fordonssystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-122682.

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This master thesis has examined how the understanding of different driving tasks can be used to develop a suitable powertrain model to be used in the Sim III simulator at VTI. Studies performed in the simulator have been statistically analyzed using parameters commonly used to describe driving patterns in drive cycles. It has been shown that the studies can be divided into three driving tasks: "High constant velocity", "High velocity with evasive maneuver", and "Mixed driving". Furthermore, a powertrain model from a former master thesis has been further developed. The new model utilizes a 3D torque map that takes engine speed, accelerator pedal position and gear as input. Using measurements, from the chassis dynamometers laboratory at LiU, that resembles the derived driving tasks, it has been shown that the performance of the new model has significantly increased for high velocity driving and during maximum acceleration. However, when using the clutch at low speeds and gears the model still performs poorly and needs further development.
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Borkovec, Tomáš. "Design of Generalized Powertrain Model." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-220391.

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In this work is proposed the generalized powertrain of the parallel hybrid car. The powertrain is composed from the sub-models of the power sources. Each sub-model is described by the quasi-static modeling. For given routes is computed the power demand. Based on the derived power demand, three energy management systems are tested. First system is based on heuristic rules. The second one use more sophisticated control algorithms - the optimization method. Main idea is based on minimum principle, when the control algorithm tries to minimize the cost function (fuel use, emission). The last one is based on the equivalent consumption minimization strategy.
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Bin, Raja Ahsan Shah Raja Mazuir. "Development of a 4WD vehicle powertrain system model for driveability investigation." Thesis, University of Warwick, 2013. http://wrap.warwick.ac.uk/57723/.

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Gim, Gwanghun. "Vehicle dynamic simulation with a comprehensive model for pneumatic tires." Diss., The University of Arizona, 1988. http://hdl.handle.net/10150/184478.

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Анотація:
This study presents an analytical approach for the mechanics of the pneumatic tires and the vehicle dynamic simulation. Most of tire dynamic parameters in this study are derived by using the tire geometry rather than experimental data. For the tire dynamic properties, explicit formulations are derived analytically as functions of slip ratio, slip angle, camber angle, and other tire dynamic parameters. These formulations can be efficiently used for the general vehicle simulations of braking/traction and steering maneuvers with a varying camber angle at irregular terrains. For on-highway vehicle simulations, a conceptual sports car is modeled as a twenty-six degrees of freedom multi-body system, while the military 1/4 ton truck M151-A2 is modeled as a fourteen degrees of freedom multi-body system for off-highway vehicle simulations. To study vehicle ride comfort, stability, and maneuverability, numerous vehicle simulations are performed using the comprehensive tire model, steering, braking, traction, nonlinear suspension, and realistic irregular terrains. For these simulations, a general-purpose multi-body dynamic analysis code (named MBOSS) has been developed.
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Kazemi, Omid. "Comprehensive Tire Model For Multibody Simulations." Diss., The University of Arizona, 2014. http://hdl.handle.net/10150/338760.

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Tires serve as important components of wheeled vehicles and their analytical modeling has drawn the attention of many researches in the past decades. A high-resolution finite element (FE) tire model contains detailed structural and material characteristics of a tire that exhibit degrees-of-freedom (DoF) in the order of 10⁵ or greater. However, such high-resolution models in their full detail are not practically applicable in multibody dynamic analysis of vehicles and a reduction in their order becomes necessary. In this research different formulations to construct condensed FE tire models suitable for multibody simulations are developed and their characteristics are discussed. In addition, two new and novel forms of substructuring are presented that aim at isolating the contact region of a tire without the need for keeping the boundary DoF which otherwise remain in the reduced system in the standard substructuring procedures. The new substructuring methods provide a great tool in constructing condensed FE tire models with much less total number of DoF compared to cases where a standard substructuring is used. In order to increase the computational efficiency of the condensed FE tire models even further, the possibility of model condensation in the contact region is studied. This research also addresses the applicability of available friction models into the condensed FE tire models. Different formulations of a condensed tire model presented in this research are used to construct several computational models. These models are utilized to simulate certain scenarios and the results are discussed.
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Xu, Ji. "Active Control of Vehicle Powertrain Noise using Adaptive Notch Filter with Inverse Model LMS Algorithm." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447689357.

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Книги з теми "Comprehensive powertrain and vehicle model"

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Dritev – Drivetrain for Vehicles 2020. VDI Verlag, 2020. http://dx.doi.org/10.51202/9783181023730.

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20th International VDI Congress „Dritev“ – The most important powertrain development trends now digital & Corona-safe! Even in the corona crisis, the world of powertrain development does not stand still. Mobility and how it is driven remains the central focus of the automotive industry. The aim is to find good solutions in the area of conflict between rising CO2 fleet consumption, an exploding number of drive variants and regulatory intervention by the state. Many questions are still open here. The companies are therefore pursuing multi-track drive strategies that follow a comprehensive electrification of the drive system in all vehicle classes in order to be well positioned for the future. Es laufen zwei Veranstaltungen in einer, denn parallel zur Dritec wird auch die EDrive stattfinden. Content (Dritev) Hier einige inhaltliche Stichworte zur Dritev (Auszüge): New series solution Ford MACH-E Primary Electric Drive Unit ….1 The front-axle drive of th...
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Частини книг з теми "Comprehensive powertrain and vehicle model"

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Mahajan, Shivam, Jai Prakash Sharma, K. Aditya, Himanshu Gupta, and Kunal Singh. "Comprehensive Review on Hybrid Vehicle Powertrain." In Lecture Notes in Mechanical Engineering, 493–501. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6469-3_46.

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Bonera, Emanuele, Marco Gadola, Daniel Chindamo, Stefano Morbioli, and Paolo Magri. "Integrated Design Tools for Model-Based Development of Innovative Vehicle Chassis and Powertrain Systems." In Lecture Notes in Mechanical Engineering, 118–28. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31154-4_11.

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Mulik, Rakesh V., Piyush P. Aware, and Senthil Kumar Arumugam. "Mathematical Modeling Techniques and Development of a Blended Model for Hybrid Electric Vehicle Powertrain." In Lecture Notes in Mechanical Engineering, 1007–18. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4795-3_93.

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Vignesh, S., Yogesh Krishan Bhateshvar, Mohammad Rafiq B. Agrewale, and K. C. Vora. "Comprehensive Design of Small Electric Vehicle for Powertrain Optimization for Optimum Range with Weight and Size Reduction." In Energy Systems in Electrical Engineering, 443–86. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0979-5_18.

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Salloum, Nicole, Serge Francis, and Charbel Mansour. "Energy-Based Approach to Model a Hybrid Electric Vehicle and Design Its Powertrain Controller and Energy Management Strategy." In CONAT 2016 International Congress of Automotive and Transport Engineering, 471–81. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45447-4_52.

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Guerrini, Federica. "Data-Informed Models for the Coupled Dispersal of Microplastics and Related Pollutants Applied to the Mediterranean Sea." In Special Topics in Information Technology, 3–14. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15374-7_1.

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AbstractMicroplastic pollution is a ubiquitous environmental threat, in particular to the oceans. In the marine environment, microplastics are not just passively transported by sea currents, but often get contaminated with organic pollutants during the journey. The uptake of chemicals onto microplastics can worsen the adverse effects of microplastics to marine organisms; however, investigation on this urgent phenomenon is hampered by the impossibility of monitoring and tracking such small plastic fragments during their motion at sea. This work aims at addressing the need for an effective modelling of the advection–diffusion processes jointly involving microplastics and the pollutants they carry to further our understanding of their spatiotemporal patterns and ecological impacts, focusing on the Mediterranean Sea. Here we present the conceptual design, methodological settings, and modelling results of a novel, data-informed 2D Lagrangian–Eulerian modelling framework that simultaneously describes (i) the Lagrangian dispersal of microplastic on the sea surface, (ii) the Eulerian advection–diffusion of selected organic contaminants, and (iii) the gradient-driven chemical exchanges between microplastic particles and chemical pollutants in the marine environment in a simple, yet comprehensive way. Crucial to the realism of our model is exploiting the wide variety and abundance of data linked with drivers of Mediterranean marine pollution by microplastics and chemicals, ranging from national censuses to satellite data of surface water runoff and GPS ship tracking, other than the use of oceanographic reanalyses to inform microplastics’ motion at sea. The results of our method applied to a multi-year simulation contribute to a first basin-wide assessment of the role of microplastics as a vehicle of other pollutants of concern in the marine environment. The framework proposed here is intended as a flexible tool to help advance knowledge towards a comprehensive description of the multifaceted threat of marine plastic pollution and an informed support to targeted mitigation policies.
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Jose Chacko, Parag, Haneesh K. M., and Joseph X. Rodrigues. "Error-State Extended Kalman Filter-Based Sensor Fusion for Optimized Drive Train Regulation of an Autonomous PHEV." In Electric Vehicles and the Future of Energy Efficient Transportation, 56–74. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7626-7.ch003.

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An efficient state estimator is critical for the development of an autonomous plug-in hybrid electric vehicle (PHEV). To achieve effective autonomous regulation of the powertrain, the latency period and estimation error should be minimum. In this work, a novel error state extended kalman filter (ES-EKF)-based state estimator is developed to perform sensor fusion of data from light detection and ranging sensor (LIDAR), the inertial measurement unit sensor (IMU), and the global positioning system (GPS) sensors, and the estimation error is minimized to reduce latency. The estimator will provide information to an intelligent energy management system (IEMS) to regulate the powertrain for effective load sharing in the PHEV. The integration of the sensor fusion data with the vehicle model is simulated in MATLAB environment. The PHEV model is fed with the proposed state estimator output, and the response parameters of the PHEV are monitored.
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Yang, Ziyu, Xiaokui Yue, and Chuang Liu. "Attitude Stabilization of Flexible Spacecraft Using Output Feedback Controller." In Advanced Control of Flight Vehicle Maneuver and Operation, 127–54. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815050028123040007.

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Spacecraft in space may have some certain non-cooperative characteristics due to the service life limit, fuel exhaustion, component fault, structural fatigue damage, or after performing certain space tasks such as capturing non-cooperative targets. In modeling, these non-cooperative characteristics are often manifested in uncertain and unknown inertia, model parameters uncertainty, actuator faults, etc. In this paper, aiming at the attitude stability control problem of such flexible spacecraft, the attitude dynamics modeling is completed by introducing the nominal inertia to construct the comprehensive disturbance term including external disturbance, inertia uncertainty and actuator failure. Then, a static output feedback (SOF) controller is applied to model the closed-loop attitude control system a stable negative imaginary (NI) system with H∞ performance constraints according to NI theory. As long as the optimization variables approach zero, the LMI-based iterative algorithm can find such the static output feedback controller to stabilize the flexible spacecraft. It is worth mentioning that an event-trigger mechanism is introduced into the control scheme to reduce communication pressure. Finally, the numerical simulation is carried out in the presence of controller gain perturbations and model parameter uncertainty. The results of the simulation demonstrate the effectiveness, robustness and non-fragility of the control method.<br>
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9

Wang, Xulu, and Limin Chang. "Estimation of Dynamic Response Index Domain of High Speed Railway Vehicle System." In Advances in Transdisciplinary Engineering. IOS Press, 2020. http://dx.doi.org/10.3233/atde200230.

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Based on the dynamic simulation model, the dynamic response index of vehicle system under the action of track irregularity is divided into three areas: repair, deterioration and maintenance. The correlation between the track irregularity index and the dynamic response index domain of vehicle system components is calculated and statistically studied. The estimation model of dynamic response index domain of vehicle system and the domain boundaries of different dynamic response indexes are established and obtained Line. According to the principle of single variable method, the excitation source of vehicle track system is divided into track irregularity and other comprehensive factors (such as temperature load, material damage, etc.), and a simple inversion method of track foundation state is proposed based on the estimation model of dynamic response index domain. Its basic principle is: if the statistical characteristics of track irregularity remain unchanged and other influencing factors change, the estimation domain and measurement domain of dynamic response index will produce grade jump, so as to determine whether the basic state of the line is normal. The simulation results show that the accuracy of domain estimation of dynamic response index of vehicle system is more than 80%, and the accuracy of recognition is more than 70% for the damage condition of the line infrastructure, where the fastener is empty.
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Zenowicz, Kamil, and Wojciech Skarka. "Verification of Flutter Method for the Purposes of Building a Very Flexible Wing Generative Model." In Advances in Transdisciplinary Engineering. IOS Press, 2020. http://dx.doi.org/10.3233/atde200097.

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First step of aircraft design is calculation of initial parameters, based on assumptions determining flight parameters which designed aircraft should meet. During these calculations, it is possible to pre-detect structure instability called a flutter. These calculations are made based on the geometric parameters assumed in the first conceptual drawings of the flying vehicle. Assumed masses and speeds allow for preliminary analysis of forces acting on the structure. The next step is to determine the displacements and deformations occurring in the structure of the aircraft in different phases of flight and under different conditions. The article presents all the stages of wing analysis for a proposed stratospheric drone with a highly flexible wing structure. This analysis, after integration with CAD software, will allow for the preparation of a comprehensive generative model. The basic assumptions of the designed aircraft are: flight altitude, wings area, very extended or unlimited flight time, approximate flight speed, climbing time, hull parameters, rudder size and placement, wing profile and mass of the structure. These assumptions made it possible to carry out a preliminary analysis of loads, wing pressure distribution, lift force and total resistance force. The goal of the research is to develop a methodology of preliminary flutter analysis which can be easily integrated in the form of calculation backgound for generative model. This methodology has been developed to determine displacements, structure stability and critical vibration frequencies. CAD software after integration with constantly optimizing calculation software will allow the generation of optimal shape and structure rigidity for given initial assumptions.
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Тези доповідей конференцій з теми "Comprehensive powertrain and vehicle model"

1

Cervone, Davide, Bernardo Sessa, Ivan Arsie, Cesare Pianese, and Pierpaolo Polverino. "A Comprehensive Hybrid Vehicle Model for Energetic Analyses on Different Powertrain Architectures." In 14th International Conference on Engines & Vehicles. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2019. http://dx.doi.org/10.4271/2019-24-0064.

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2

Cook, Joshua T., Laura Ray, and James Lever. "Multi-Body Dynamics Model of a Tracked Vehicle Using a Towing Winch for Optimal Mobility Control and Terrain Identification." In ASME 2016 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/dscc2016-9626.

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This paper presents a generalized, multi-body dynamics model for a tracked vehicle equipped with a winch for towing operations. The modeling approach couples existing formulations in the literature for the powertrain components and the vehicle-terrain interaction to provide a comprehensive model that captures the salient features of terrain trafficability. This coupling is essential for making realistic predictions of the vehicle’s mobility capabilities due to the power-load relationship at the engine output. Simulation results are presented jointly with experimental data to validate these dynamics under conditions where no action is taken by the winch. Extended modeling includes dynamics of the hydraulic system that powers the winch so that the limitation of the winch as an actuator and the load it puts on the engine are realized. A second set of simulation results show that for a set of open loop control actions by the winch, the vehicle is able to maintain its mobility in low traction terrain by paying the towed load in and out.
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3

Docimo, Donald J., Herschel C. Pangborn, and Andrew G. Alleyne. "Hierarchical Control for Electro-Thermal Power Management of an Electric Vehicle Powertrain." In ASME 2018 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/dscc2018-9215.

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This paper develops a hierarchical control framework to manage both the electrical and thermal domains of an automotive electric vehicle (EV). Batteries, electric machines, and power electronics all have desired thermal operating ranges, with operation outside these limits leading to reduced component performance and lifespan. Previous studies present various component- and high-level energy management algorithms that seek to maintain desired temperatures. However, the literature contains limited efforts to develop comprehensive control approaches that coordinate the electrothermal dynamics within the vehicle, ensuring that electrical systems do not generate more thermal energy than can be managed within temperature constraints. To address this gap, this paper presents a hierarchical control framework that governs electrical and thermal states across multiple timescales while meeting operational requirements, such as tracking a desired vehicle velocity and cabin temperature. To develop this framework, a network of communicating model predictive controllers coordinates the system dynamics, with significant reduction in computational complexity over a centralized control approach. A graph-based model of the candidate EV powertrain is developed and then decomposed to generate models used in each controller of the hierarchical framework. Through the case study of this paper, it is demonstrated that the hierarchical controller can make important trade-offs between tracking desired operational references and maintaining temperatures within constraints.
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4

Polastri, Marco, Damiano Chiarabelli, Silvia Gessi, Massimo Martelli, Emiliano Mucchi, and Pietro Marani. "A Comprehensive Lumped Parameter Approach for the Dynamic Simulation of Agricultural Tractors in Real Operating Conditions." In 11th Asia-Pacific Regional Conference of the ISTVS. International Society for Terrain-Vehicle Systems, 2022. http://dx.doi.org/10.56884/zlty2074.

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Vehicle dynamics is of primary importance for the determination of the vertical load on wheels and consequently on their traction capability. This is even more true if the vehicle is travelling on an uncompacted soil and influenced by a variable load applied to the hitch, as it is for a ploughing tractor. In this framework, the authors present a comprehensive lumped parameter approach for performance assessment of agricultural tractors in real operating conditions. The proposed methodology integrates in a modular context different numerical models related to the main subsystems of a modern tractor, i.e. diesel engine, hydro-mechanical transmission, full multibody frame and tire mechanics. In particular, the engine and transmission modules reproduce powertrain characteristics and control strategy, the multibody module characterizes the dynamic behaviour of the vehicle detailing the interaction between the tractor rigid bodies, and the tire model predicts tractive capability and resistance to motion on soft soil. It also provides the possibility to properly reproduce real load cycles and their influence on the vehicle setup. The presented lumped parameter model is intended as a powerful simulation tool, capable of considering a large number of phenomena affecting tractor performance, both in terms of fuel consumption and longitudinal response due to load distribution. The predictive capabilities of the proposed modelling approach are presented by simulating a realistic ploughing operation, focusing on tire-soil interaction. Considering the cascade phenomena from the wheel-ground interaction to the engine, passing through the dynamic of vehicle bodies and their mass transfer, numerical results are presented in terms of tractive capability and its effect on fuel consumption.
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5

Montazeri-Gh, Morteza, Zeinab Pourbafarani, and Hassan Nehzati. "Optimal Gear Ratio and Gear Shift Strategy Design for a Parallel Hybrid Electric Vehicle Equipped With AMT." In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-24702.

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This paper presents an optimal approach for the design of gear ratios and gear shifting strategy for parallel hybrid electric vehicle (HEV) equipped with automated manual transmission (AMT). For this purpose, an AMT model is firstly provided and integrated with a pre-transmission parallel HEV model to develop a comprehensive simulation tool for vehicle powertrain performance evaluation. Using genetic algorithm (GA), an optimization problem is then formulated for the optimal design of the AMT variables including its gear ratios as well as the variables defined for the gear shifting strategy. A weighted aggregation of the HEV fuel consumption and emissions is also employed as the fitness function. In addition, the vehicle driving performance characteristics are considered as the optimization constraints. To optimize the gearshift strategy and gear ratios, GA optimization process is performed for several traffic conditions. The results show that the approach is quite effective. A considerable improvement is achieved at congested condition due to its sensitivity to the stop-start operation of the vehicle.
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6

Zhao, Junfeng, and Junmin Wang. "Model Predictive Control of Integrated Hybrid Electric Powertrains Coupled With Aftertreatment Systems." In 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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Danninger, Alois, and Uwe Martin. "CO2 reduction for long haul trucks by predictive control." In FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2020-adm-014.

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In the transport sector, the reduction of real driving emissions and fuel consumption in long haul traffic is one of the main societal challenges. Regulations e.g. Euro VI are a baseline with respect to targets in defined test environment conditions, while a clear need exist to have real driving efficiency measurements to promote the introduction of innovative solutions for fuel consumption and emission reductions. Reduction of CO2 and pollutant emissions interact with each other and vary with the specific vehicle application, operating conditions and mission. The overall objective of this work is the development of new means of predictive and comprehensive powertrain control in an optimal way, exploiting to the full potential of the individual systems for each vehicle application and mission. The pre-condition for predictive vehicle control is the knowledge on future velocity profile. A dynamic eHorizon system is developed and applied in 3 different trucks with a “look ahead” capability of delivering static and dynamic data with respect to the road ahead. Control strategy improvements are implemented in the following main technical clusters: - Global powertrain and vehicle supervisor, - Hybridization, - Engine and EAS control, - Thermal management The first improvement approach targets existing control strategies. This will mostly rely on migration from direct control strategies to model-based control strategies as well as on integration of existing strategies. The model-based control strategy approach relies on a mathematical model of the physics of parts of the system (e.g. combustion), which is running in real time on the computing platform and can provide more accurate information of the current state of the system. Furthermore, a mathematical (sub) system description is the base to use predictive control strategies. The integration of different control enables tighter synchronization between the (highly dependent) systems and, therefore, improved performance. The second improvement approach targets the introduction of extended and predictive input data. This additional data will provide predictive information of the vehicle mission and environment situation, therefore enabling predictive strategies that can control the systems according to events that will occur with high probability in the short-term future. Examples are the identification of hills or traffic jams and the resulting tailoring of the control strategies up to activation or deactivation of specific auxiliaries according to this information. The dependency on traffic directly leads to the problem of non-reproducible validation measurements on real roads. Therefore, a simulation – based validation strategy is developed. The simulation elements of the trucks are validated on various platforms like HiL, engine testbed and demonstrator trucks. Next the question of “representable traffic conditions” was solved by the analysis of European traffic routes and transfer of typical traffic scenarios on the VECTO CO2 Long-Haul cycle. The simulation platform enables interaction of the ego-vehicle with defined traffic scenarios for validation. This contribution presents selected outcomes and overall results of the EU-funded 3-year research program IMPERIUM with a fuel consumption reduction of -20% compared to model - year 2014 vehicle.
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Walker, Alan, Andy McGordon, Geoff Hannis, Alex Picarelli, Johnathan Breddy, Steve Carter, Adrian Vinsome, Paul Jennings, Mike Dempsey, and Mark Willows. "A Novel Structure for Comprehensive HEV Powertrain Modelling." In 2006 IEEE Vehicle Power and Propulsion Conference. IEEE, 2006. http://dx.doi.org/10.1109/vppc.2006.364299.

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9

Kossioris, Theodoros, Joschka Schaub, Markus Ehrly, Johannes Maiterth, Ruben Keizer, and Dieter an der Put. "Evaluation of a Serial-parallel Hybrid Powertrain Concept for a Heavy Duty Truck." In FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2021-epv-078.

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Анотація:
According to latest European Union (EU) findings, CO2 emissions from heavy duty vehicles, including lorries, buses and coaches, account for about 6 % of the total CO2 emissions in the Union and to about 25 % of the total CO2 emissions from road transport. It is expected that without further measures, the share of CO2 emissions from heavy duty vehicles will increase by around 9 % between 2010 and 2030. The constant growth in demand for on-road transport underlines the urgency of cleaner and more fuel-efficient global on-road transport vehicles fleets. In February 2019, the EU finally decided to set CO2 limits for on-road commercial vehicles for the first time. Legislation requires a 15 % CO2 reduction scenario in 2025 and a 30 % CO2 reduction scenario in 2030 based on the 2019 baseline fleet. Most heavy-duty vehicles (HDVs) are nowadays powered by diesel engines. Diesel powertrain hybridization has demonstrated its ability to significantly reduce the fuel consumption and thus the CO2 emissions in various medium duty and heavy duty applications. This paper presents a comprehensive simulation study to evaluate the fuel savings potential of a serial-parallel hybrid heavy duty truck. The innovative configuration consists of a transmission with a reduced number of gears and parts designed to achieve a good compromise between system losses and weight. The two electric machines integrated into the dedicated hybrid transmission system enable three different driving modes, namely electric driving with one or two electric machines, serial driving and a parallel mode. The fuel economy results as well as the tailpipe pollutant emissions are compared with a conventional powertrain and a parallel hybrid (P2) configuration in different operating profiles. A future emissions legislation scenario is therefore introduced. Optimal sizing of the electrical components of the hybrid configurations (battery and electric machines) will be considered. Also, the total purely electric driving range of the electrified powertrains will be compared to current industrial benchmarks.
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Yamamoto, Kazusa, Matthieu Ponchant, Franck Sellier, Tommaso Favilli, Luca Pugi, and Lorenzo Berzi. "48V Electric Vehicle Powertrain Optimal Model-based Design Methodology." In 2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE). IEEE, 2020. http://dx.doi.org/10.23919/aeitautomotive50086.2020.9307407.

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Звіти організацій з теми "Comprehensive powertrain and vehicle model"

1

Cook, Joshua, Laura Ray, and James Lever. Dynamics modeling and robotic-assist, leader-follower control of tractor convoys. Engineer Research and Development Center (U.S.), February 2022. http://dx.doi.org/10.21079/11681/43202.

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This paper proposes a generalized dynamics model and a leader-follower control architecture for skid-steered tracked vehicles towing polar sleds. The model couples existing formulations in the literature for the powertrain components with the vehicle-terrain interaction to capture the salient features of terrain trafficability and predict the vehicles response. This coupling is essential for making realistic predictions of the vehicles traversing capabilities due to the power-load relationship at the engine output. The objective of the model is to capture adequate fidelity of the powertrain and off-road vehicle dynamics while minimizing the computational cost for model based design of leader-follower control algorithms. The leader-follower control architecture presented proposes maintaining a flexible formation by using a look-ahead technique along with a way point following strategy. Results simulate one leader-follower tractor pair where the leader is forced to take an abrupt turn and experiences large oscillations of its drawbar arm indicating potential payload instability. However, the follower tractor maintains the flexible formation but keeps its payload stable. This highlights the robustness of the proposed approach where the follower vehicle can reject errors in human leader driving.
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2

An Input Linearized Powertrain Model for the Optimal Control of Hybrid Electric Vehicles. SAE International, March 2022. http://dx.doi.org/10.4271/2022-01-0741.

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Анотація:
Models of hybrid powertrains are used to establish the best combination of conventional engine power and electric motor power for the current driving situation. The model is characteristic for having two control inputs and one output constraint: the total torque should be equal to the torque requested by the driver. To eliminate the constraint, several alternative formulations are used, considering engine power or motor power or even the ratio between them as a single control input. From this input and the constraint, both power levels can be deduced. There are different popular choices for this one control input. This paper presents a novel model based on an input linearizing transformation. It is demonstrably superior to alternative model forms, in that the core dynamics of the model (battery state of energy) are linear, and the non-linearities of the model are pushed into the inputs and outputs in a Wiener/Hammerstein form. The output non-linearities can be approximated using a quadratic model, which creates a problem in the linear-quadratic framework. This facilitates the direct application of linear control approaches such as LQR control, predictive control, or Model Predictive Control (MPC). The paper demonstrates the approach using the ELectrified Vehicle library for sImulation and Optimization (ELVIO). It is an open-source MATLAB/Simulink library designed for the quick and easy simulation and optimization of different powertrain and drivetrain architectures. It follows a modelling methodology that combines backward-facing and forward-facing signal path, which means that no driver model is required. The results show that the approximated solution provides a performance that is very close to the solution of the original problem except for extreme parts of the operating range (in which case the solution tends to be driven by constraints anyway).
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