Relevant bibliographies by topics / Powertrain control

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Powertrain control'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Powertrain control"

1

Karlušić, Juraj, Mihael Cipek, Danijel Pavković, Željko Šitum, Juraj Benić, and Marijan Šušnjar. "Benefit Assessment of Skidder Powertrain Hybridization Utilizing a Novel Cascade Optimization Algorithm." Sustainability 12, no. 24 (December 12, 2020): 10396. http://dx.doi.org/10.3390/su122410396.

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Over the last decade, off-road vehicles have been increasingly hybridized through powertrain electrification in terms of additional electrical machine-based propulsion and battery energy storage, with the goal of achieving significant gains in fuel economy and reductions in greenhouse gases emissions. Since hybrid powertrains consist of two or more different energy sources and may be arranged in many different configurations, there are many open questions in their design and powertrain energy management control, which may have influence on the hybridized powertrain purchase cost and efficiency. This paper presents simple backward optimization models of conventional and hybrid cable skidder powertrains. These models are then used in the optimization of control variables over one forest path in order to find the minimum possible fuel consumption. The optimization results show that 15% fuel efficiency improvement in winching and skid trail driving can be achieved with the selected hybrid powertrain. With that improvement, main hybrid drive components can be paid off in 13 years.
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Arsie, Ivan, Alfonso Di Domenico, Cesare Pianese, and Marco Sorrentino. "Modeling and Analysis of Transient Behavior of Polymer Electrolyte Membrane Fuel Cell Hybrid Vehicles." Journal of Fuel Cell Science and Technology 4, no. 3 (September 9, 2006): 261–71. http://dx.doi.org/10.1115/1.2743071.

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The paper focuses on the simulation of a hybrid vehicle with proton exchange membrane fuel cell as the main energy conversion system. A modeling structure has been developed to perform accurate analysis for powertrain and control system design. The models simulate the dynamics of the main powertrain elements and fuel cell system to give a sufficient description of the complex interaction between each component under real operating conditions. A control system based on a multilevel scheme has also been introduced and the complexity of control issues for hybrid powertrains have been discussed. This study has been performed to analyze the energy flows among powertrain components. The results highlight that optimizing these systems is not a trivial task and the use of precise models can improve the powertrain development process. Furthermore, the behavior of system state variables and the influence of control actions on fuel cell operation have also been analyzed. In particular, the effect of introducing a rate limiter on the stack power has been investigated, evidencing that a 2kW∕s rate limiter increased the system efficiency by 10% while reducing the dynamic performance of the powertrain in terms of speed error.
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Wegener, Marius, Thorsten Plum, Markus Eisenbarth, and Jakob Andert. "Energy saving potentials of modern powertrains utilizing predictive driving algorithms in different traffic scenarios." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 234, no. 4 (August 8, 2019): 992–1005. http://dx.doi.org/10.1177/0954407019867172.

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In this article, we analyze the interaction between powertrain technology, predictive driving functionalities, and inner-city traffic conditions. A model predictive velocity control algorithm is developed that utilizes dynamic traffic data as well as static route information to optimize the future trajectory of the considered ego-vehicle. This controller is then integrated into a state-of-the-art simulation environment for automated driving functionalities to calculate energy saving potentials for vehicles with a conventional gasoline engine powertrain and a P3-hybrid powertrain configuration as well as for a battery electric vehicle based on real driving measurements. The comparison of these powertrains under various traffic conditions shows that all three technologies profit from predictive driving functionalities. The determined reduction in energy demand ranges from 15% to more than 40%, but it is highly dependent on the boundary conditions and the selected powertrain technology. Specifically, it is shown that electrified powertrains can profit the most when the time-gap to the preceding vehicle is maintained at a high level. For a conventional powertrain, this effect is less pronounced and can be attributed to the efficiency characteristics of gasoline engines. It can be concluded that the development of advanced predictive driving functionalities requires microscopic simulation of inner-city traffic to achieve optimum results with regard to energy consumption.
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Dorey, R. E., D. Maclay, T. Shenton, and Z. Shafiei. "Advanced Powertrain Control Strategies." IFAC Proceedings Volumes 28, no. 1 (March 1995): 151–56. http://dx.doi.org/10.1016/s1474-6670(17)45688-6.

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Deaconu, Sorin Ioan, Marcel Topor, Gabriel Nicolae Popa, and Feifei Bu. "Hybrid Electric Vehicle with Matrix Converter and Direct Torque Control in Powertrains Asynchronous Motor Drives." MATEC Web of Conferences 292 (2019): 01066. http://dx.doi.org/10.1051/matecconf/201929201066.

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Electric transportation has made rapid developments and significant steps toward the full electrical powertrain systems. With the increased use of electric vehicles energy conversion systems several technologies have been developed and reached a high degree of performance. Since electric vehicles and hybrid are the more cost competitive technology available today, the evolution toward a more reliable powertrain combining different electric powertrain systems is needed. Induction machine and permanent magnet generators/motors integrated powertrains have some significant advantages over other types of systems such as no need of excitation, low volume and weight, high precision, and no use of a complex gearbox for torque/speed conversion. A electric vehicle powertrain for EV propulsion with a induction motor and a matrix converter is proposed in this paper. The induction motor is controlled using the direct torque flux algorithm. The traditional power conversion stages consist of a rectifier followed by an inverter and bulky DC link capacitor. It involves 2 stages of power conversion and, subsequently, the efficiency of the overall EV is reduced because of power quality issues mainly based on total harmonic distortion. The proposed solution incorporates a matrix converter is mainly utilized to control the induction electric motor for propulsion. The matrix converter is a simple and compact direct AC-AC converter. The proposed EV with matrix converter is modeled using PSIM.
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Maddumage, W. U., K. Y. Abeyasighe, M. S. M. Perera, R. A. Attalage, and 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 (February 5, 2020): 20–33. http://dx.doi.org/10.21122/2227-1031-2020-19-1-20-33.

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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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Adegbohun, Feyijimi, Annette von Jouanne, Ben Phillips, Emmanuel Agamloh, and Alex Yokochi. "High Performance Electric Vehicle Powertrain Modeling, Simulation and Validation." Energies 14, no. 5 (March 9, 2021): 1493. http://dx.doi.org/10.3390/en14051493.

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Accurate electric vehicle (EV) powertrain modeling, simulation and validation is paramount for critical design and control decisions in high performance vehicle designs. Described in this paper is a methodology for the design and development of EV powertrain through modeling, simulation and validation on a real-world vehicle system with detailed analysis of the results. Although simulation of EV powertrains in software simulation environments plays a significant role in the design and development of EVs, validating these models on the real-world vehicle systems plays an equally important role in improving the overall vehicle reliability, safety and performance. This modeling approach leverages the use of MATLAB/Simulink software for the modeling and simulation of an EV powertrain, augmented by simultaneously validating the modeling results on a real-world vehicle which is performance tested on a chassis dynamometer. The combination of these modeling techniques and real-world validation demonstrates a methodology for a cost effective means of rapidly developing and validating high performance EV powertrains, filling the literature gaps in how these modeling methodologies can be carried out in a research framework.
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Xiong, Shaoping, Gabriel Wilfong, and John Lumkes. "Components Sizing and Performance Analysis of Hydro-Mechanical Power Split Transmission Applied to a Wheel Loader." Energies 12, no. 9 (April 28, 2019): 1613. http://dx.doi.org/10.3390/en12091613.

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The powertrain efficiency deeply affects the performance of off-road vehicles like wheel loaders in terms of fuel economy, load capability, smooth control, etc. The hydrostatic transmission (HST) systems have been widely adopted in off-road vehicles for providing large power density and continuous variable control, yet using relatively low efficiency hydraulic components. This paper presents a hydrostatic-mechanical power split transmission (PST) solution for a 10-ton wheel loader for improving the fuel economy of a wheel loader. A directly-engine-coupled HST solution for the same wheel loader is also presented for comparison. This work introduced a sizing approach for both PST and HST, which helps to make proper selections of key powertrain components. Furthermore, this work also presented a multi-domain modeling approach for the powertrain of a wheel loader, that integrates the modeling of internal combustion (IC) engine, hydraulic systems, mechanical transmission, vehicle(wheel) dynamics, and relevant control systems. In this modeling, an engine torque evaluation method with a throttle position control system was developed to describe the engine dynamics; a method to express the hydraulic loss of the axial piston hydraulic pump/motor was developed for modeling the hydraulic transmission; and a vehicle velocity control system was developed based on altering the displacement of a hydraulic unit. Two powertrain models were developed, respectively, for the PST and HST systems of a wheel loader using MATLAB/Simulink. The simulation on a predefined wheel loader drive cycle was conducted on both powertrain models to evaluate and compare the performance of wheel loader using different systems, including vehicle velocity, hydraulic displacement control, hydraulic torque, powertrain efficiency, and engine power consumption. The simulation results indicate that the vehicle velocity controller developed functions well for both the PST and HST systems; a wheel loader using the proposed PST solution can overall save about 8% energy consumption compared using an HST solution in one drive cycle. The sizing method and simulation models developed in this work should facilitate the development of the powertrains for wheel loaders and other wheeled heavy vehicles.
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Cho, D., and J. K. Hedrick. "Automotive Powertrain Modeling for Control." Journal of Dynamic Systems, Measurement, and Control 111, no. 4 (December 1, 1989): 568–76. http://dx.doi.org/10.1115/1.3153093.

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A dynamic model of an automotive powertrain system is developed by the use of eight states and two time-delays in the continuous-time domain, with careful attention given to the dynamics and kinematics of a four-stroke spark-ignition engine, an automatic transmission, and rubber tires. The model is relatively simple, yet it predicts the important dynamics (including those during a shift) quite well when compared to experimental data. The model is well suited for developing powertrain controllers and can also be used for studying the dynamic behavior of a powertrain system. A great deal of effort was directed toward preserving the generic nature of modeling so that the developed techniques can be easily adapted to different vehicles with a minimum amount of bench tests for obtaining parameters.
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Cook, Jeffrey A., Jing Sun, Julia H. Buckland, Ilya V. Kolmanovsky, Huei Peng, and Jessy W. Grizzle. "Automotive Powertrain Control - A Survey." Asian Journal of Control 8, no. 3 (October 22, 2008): 237–60. http://dx.doi.org/10.1111/j.1934-6093.2006.tb00275.x.

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Dissertations / Theses on the topic "Powertrain control"

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Zhao, Shiyu. "Nonparametric robust control methods for powertrain control." Thesis, University of Liverpool, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.548802.

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Marciszko, Fredrik. "Torque Sensor based Powertrain Control." Thesis, Linköping University, Department of Electrical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2248.

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The transmission is probably the drivetrain component with the greatest impact on driveability of an automatic transmission equipped vehicle. Since the driver only has an indirect influence on the gear shift timing, except for situations like kick-down accelerations, it is desirable to improve shift quality as perceived by the driver. However, improving shift quality is a problem normally diametrically opposed to minimizing transmission clutch energy dissipation. The latter has a great impact on transmission lifetime, and has to be defined and taken into consideration along with the notion of shift quality. The main focus of this thesis is the modeling of a drivetrain of an automatic transmission vehicle, and the implementation in MatLab/Simulink, including the first to second gear upshift. The resulting plant based on the derived equations is validated using data from a test vehicle equipped with a torque sensor located at the transmission output shaft. The shaft torque is more or less proportional to the driveline jerk, and hence of great interest for control purposes. Control strategies are discussed and a PID controller structure is developed to control the first to second gear upshift, as opposed to the traditional open-loop upshift control. Furthermore, the proposed controller structure uses the transmission output torque and the differential speed of the engaging clutch as inputs, to control the clutch pressure and the engine output torque, respectively. The structure is unsophisticated and transparent compared to other approaches, but shows great theoretical results in terms of improved shift quality and decreased clutch wear.

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Zetterqvist, Carin. "Powertrain modelling and control algorithms for traction control." Thesis, Linköping University, Department of Electrical Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-10048.

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För att ett fordon ska kunna bromsa, accelerera och svänga är friktion mellan däcken och vägen ett måste. Vid för mycket gaspådrag under en acceleration kan det hända att hjulen förlorar fäste och börjar spinna loss, något som leder till både försämrad kontroll över fordonet och att däcken slits ut i förtid. Traction controlsystemet förhindrar hjulen från att spinna loss och försöker maximera friktionen.

Målet med detta examensarbete är att utvärdera olika reglerprinciper samt att undersöka olika möjligheter för att reglera friktionen mellan däck och väg. Det är ett svårt reglerproblem, dels på grund av dess olinjäritet, dels på grund av det faktum att friktionen är en okänd parameter.

För att kunna undersöka olika reglermöjligheter har en modell över hjuldynamiken och en modell över drivlinan tagits fram i Matlabs simuleringsprogram Simulink. Därutöver har tre regulatorer designats: en fuzzy-regulator, en fuzzy-P-regulator och en PI-regulator. Regulatorerna utvärderades i tre tester som bland annat testade deras robusthet.

Fuzzy-regulatorn och fuzzy-P-regulatorn lyckades reglera systemet bra. PI-regulatorn gjorde däremot inte ett tillfredsställande jobb, mest på grund av dess behov av ett börvärde.


Traction is necessary for a vehicle to be able to brake, accelerate and turn. When pushing the accelerator pedal too hard during an acceleration, the wheel can loose traction and start spinning, which leads to a worsen vehicle control and also wears out the tyres faster. The traction control system prevents the wheels from spinning and tries to make the tyres maintain maximum traction.

The purpose of this master’s thesis is to evaluate different control methods and to investigate possible ways to control the traction. This is a difficult control problem due to its nonlinearity and the fact that the friction is an unknown parameter.

For the investigation, a model of the wheel dynamics and a model of the powertrain have been developed in Matlab’s simulation program Simulink. Furthermore, three different controllers have been designed; a fuzzy controller, a fuzzy-P controller and a PI controller. The controllers were evaluated in three test cycles that among others tested their robustness.

The fuzzy controller and the fuzzy-P controller managed to control the system very well. The PI controller, however, did not work satisfactory, mainly because of its need of a desired value.

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Li, Xuchen Mr. "Driving Style Adaptive Electrified Powertrain Control." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524228128758252.

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Reig, Bernad Alberto. "Optimal Control for Automotive Powertrain Applications." Doctoral thesis, Universitat Politècnica de València, 2017. http://hdl.handle.net/10251/90624.

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Optimal Control (OC) is essentially a mathematical extremal problem. The procedure consists on the definition of a criterion to minimize (or maximize), some constraints that must be fulfilled and boundary conditions or disturbances affecting to the system behavior. The OC theory supplies methods to derive a control trajectory that minimizes (or maximizes) that criterion. This dissertation addresses the application of OC to automotive control problems at the powertrain level, with emphasis on the internal combustion engine. The necessary tools are an optimization method and a mathematical representation of the powertrain. Thus, the OC theory is reviewed with a quantitative analysis of the advantages and drawbacks of the three optimization methods available in literature: dynamic programming, Pontryagin minimum principle and direct methods. Implementation algorithms for these three methods are developed and described in detail. In addition to that, an experimentally validated dynamic powertrain model is developed, comprising longitudinal vehicle dynamics, electrical motor and battery models, and a mean value engine model. OC can be utilized for three different purposes: 1. Applied control, when all boundaries can be accurately defined. The engine control is addressed with this approach assuming that a the driving cycle is known in advance, translating into a large mathematical problem. Two specific cases are studied: the management of a dual-loop EGR system, and the full control of engine actuators, namely fueling rate, SOI, EGR and VGT settings. 2. Derivation of near-optimal control rules, to be used if some disturbances are unknown. In this context, cycle-specific engine calibrations calculation, and a stochastic feedback control for power-split management in hybrid vehicles are analyzed. 3. Use of OC trajectories as a benchmark or base line to improve the system design and efficiency with an objective criterion. OC is used to optimize the heat release law of a diesel engine and to size a hybrid powertrain with a further cost analysis. OC strategies have been applied experimentally in the works related to the internal combustion engine, showing significant improvements but non-negligible difficulties, which are analyzed and discussed. The methods developed in this dissertation are general and can be extended to other criteria if appropriate models are available.
El Control Óptimo (CO) es esencialmente un problema matemático de búsqueda de extremos, consistente en la definición de un criterio a minimizar (o maximizar), restricciones que deben satisfacerse y condiciones de contorno que afectan al sistema. La teoría de CO ofrece métodos para derivar una trayectoria de control que minimiza (o maximiza) ese criterio. Esta Tesis trata la aplicación del CO en automoción, y especialmente en el motor de combustión interna. Las herramientas necesarias son un método de optimización y una representación matemática de la planta motriz. Para ello, se realiza un análisis cuantitativo de las ventajas e inconvenientes de los tres métodos de optimización existentes en la literatura: programación dinámica, principio mínimo de Pontryagin y métodos directos. Se desarrollan y describen los algoritmos para implementar estos métodos así como un modelo de planta motriz, validado experimentalmente, que incluye la dinámica longitudinal del vehículo, modelos para el motor eléctrico y las baterías, y un modelo de motor de combustión de valores medios. El CO puede utilizarse para tres objetivos distintos: 1. Control aplicado, en caso de que las condiciones de contorno estén definidas. Puede aplicarse al control del motor de combustión para un ciclo de conducción dado, traduciéndose en un problema matemático de grandes dimensiones. Se estudian dos casos particulares: la gestión de un sistema de EGR de doble lazo, y el control completo del motor, en particular de las consignas de inyección, SOI, EGR y VGT. 2. Obtención de reglas de control cuasi-óptimas, aplicables en casos en los que no todas las perturbaciones se conocen. A este respecto, se analizan el cálculo de calibraciones de motor específicas para un ciclo, y la gestión energética de un vehículo híbrido mediante un control estocástico en bucle cerrado. 3. Empleo de trayectorias de CO como comparativa o referencia para tareas de diseño y mejora, ofreciendo un criterio objetivo. La ley de combustión así como el dimensionado de una planta motriz híbrida se optimizan mediante el uso de CO. Las estrategias de CO han sido aplicadas experimentalmente en los trabajos referentes al motor de combustión, poniendo de manifiesto sus ventajas sustanciales, pero también analizando dificultades y líneas de actuación para superarlas. Los métodos desarrollados en esta Tesis Doctoral son generales y aplicables a otros criterios si se dispone de los modelos adecuados.
El Control Òptim (CO) és essencialment un problema matemàtic de cerca d'extrems, que consisteix en la definició d'un criteri a minimitzar (o maximitzar), restriccions que es deuen satisfer i condicions de contorn que afecten el sistema. La teoria de CO ofereix mètodes per a derivar una trajectòria de control que minimitza (o maximitza) aquest criteri. Aquesta Tesi tracta l'aplicació del CO en automoció i especialment al motor de combustió interna. Les ferramentes necessàries són un mètode d'optimització i una representació matemàtica de la planta motriu. Per a això, es realitza una anàlisi quantitatiu dels avantatges i inconvenients dels tres mètodes d'optimització existents a la literatura: programació dinàmica, principi mínim de Pontryagin i mètodes directes. Es desenvolupen i descriuen els algoritmes per a implementar aquests mètodes així com un model de planta motriu, validat experimentalment, que inclou la dinàmica longitudinal del vehicle, models per al motor elèctric i les bateries, i un model de motor de combustió de valors mitjans. El CO es pot utilitzar per a tres objectius diferents: 1. Control aplicat, en cas que les condicions de contorn estiguen definides. Es pot aplicar al control del motor de combustió per a un cicle de conducció particular, traduint-se en un problema matemàtic de grans dimensions. S'estudien dos casos particulars: la gestió d'un sistema d'EGR de doble llaç, i el control complet del motor, particularment de les consignes d'injecció, SOI, EGR i VGT. 2. Obtenció de regles de control quasi-òptimes, aplicables als casos on no totes les pertorbacions són conegudes. A aquest respecte, s'analitzen el càlcul de calibratges específics de motor per a un cicle, i la gestió energètica d'un vehicle híbrid mitjançant un control estocàstic en bucle tancat. 3. Utilització de trajectòries de CO com comparativa o referència per a tasques de disseny i millora, oferint un criteri objectiu. La llei de combustió així com el dimensionament d'una planta motriu híbrida s'optimitzen mitjançant l'ús de CO. Les estratègies de CO han sigut aplicades experimentalment als treballs referents al motor de combustió, manifestant els seus substancials avantatges, però també analitzant dificultats i línies d'actuació per superar-les. Els mètodes desenvolupats a aquesta Tesi Doctoral són generals i aplicables a uns altres criteris si es disposen dels models adequats.
Reig Bernad, A. (2017). Optimal Control for Automotive Powertrain Applications [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90624
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Triantos, Georgios. "NARMAX modelling and control with powertrain applications." Thesis, University of Liverpool, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.428216.

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Cho, Dong-Il. "Nonlinear control methods for automotive powertrain systems." Thesis, Massachusetts Institute of Technology, 1987. http://hdl.handle.net/1721.1/14682.

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Guebeli, Markus. "Optimum efficiency control of the CTX powertrain." Thesis, University of Bath, 1993. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359851.

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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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Goetz, Manuel. "Integrated powertrain control for twin clutch transmissions." Thesis, University of Leeds, 2005. http://etheses.whiterose.ac.uk/2894/.

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In this thesis an integrated powertrain control for gearshifts on twin clutch transmissions is developed. First, a detailed model of an automotive powertrain featuring a twin clutch transmission is developed in Matlab/Simulink®. This model includes detailed friction models for the twin clutch that enable an investigation into the effects of different friction materials on the performance of the gearshift controller. The transmission model also includes detailed models of the synchronisers and thus allows a simulation of synchroniser-to-synchroniser shifts. A simplified phenomenological model, derived from a more complex non-linear model, is employed to model the hydraulic actuation of clutches and synchroniser. The thesis finds that the dependency of the friction coefficient on the sliding speed has an important influence on the gearshift quality and the performance of gearshift controller, while the absolute level of the friction coefficient is less important. Based on this powertrain model the key problems of gearshifts on twin clutch transmissions were identified and a control that overcomes these problems was developed. The first stage was to devise a gearshift control algorithm that handles single clutch-to-clutch shifts without a oneway (freewheeler-, overrunning-) clutch. This basic gearshift control algorithm featured a control of clutch slip for the engine torque transfer and a control of engine speed through engine torque manipulation (plus clutch pressure manipulation for downshifts). In a second stage, an optional transmission output torque control was developed that could be integrated in the basic control. The thesis shows that these control strategies are superior, in terms of shift quality, to conventional gearshift controls as used on planetary-type transmissions and are also robust against variations in the powertrain parameters (including friction coefficient) and sensor noise. The control strategies developed for single clutch-to-clutch shifts were extended to handle double and other multiple gearshifts that take place in the same transmission half. The thesis also investigates the other main part of gearshifts on twin clutch transmissions, the gear pre-selection. The thesis shows that, on power-on gearshifts, the torque reactions at the transmission output due to the gear pre-selection with conventional hydraulically actuated synchronisers can be effectively compensated for by a simple manipulation of engine torque.
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Books on the topic "Powertrain control"

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Garbett, K. S. Multi-objective scheduling and control of a nonlinear automotive powertrain. [s.l.]: typescript, 1991.

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Hu, Donghai, and Bifeng Yin. Stability Analysis and Control of Powertrain for New Energy Vehicles. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-5051-2.

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Institution of Mechanical Engineers. Automobile Division. and Institution of Mechanical Engineers. Combustion Engines Group., eds. International Seminar on Application of Powertrain and Fuel Technologies to Meet Emissions Standards: 24-26 June 1996. Bury St.Edmunds: Mechanical Engineering Publications for the Institution of Mechanical Engineers, London, 1996.

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International Conference on Integrated Powertrain Systems for a Better Environment (1999 Birmingham, England ). International Conference on Integrated Powertrain Systems for a Better Environment: 10-11 November 1999, National Exhibition Centre, Birmingham, UK. Bury St. Edmunds, England: Published by Professional Engineering Pub. for the Institution of Mechanical Engineers, 1999.

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CCI. Au: Electronic Powertrain Control Systems. Pearson Education, Limited, 2007.

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Noonan, Mike. How to Use and Upgrade to GM Gen III LS-Series Powertrain Control Systems. CarTech, Incorporated, 2013.

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Haynes, John Harold. Powertrain Codes and Oxygen Sensors 1990-99: 1995-99 (Chilton's Professional Series Quick-Reference Manuals). Haynes Manuals, Inc., 1999.

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8

Integrated Powertrains and Their Control. Wiley, 2001.

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Book chapters on the topic "Powertrain control"

1

Böhme, Thomas J., and Benjamin Frank. "Optimal Design of Hybrid Powertrain Configurations." In Advances in Industrial Control, 481–518. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51317-1_13.

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Powell, B. K. "Applied Mathematics and Systematic Automotive Powertrain Synthesis." In Control Problems in Industry, 271–99. Boston, MA: Birkhäuser Boston, 1995. http://dx.doi.org/10.1007/978-1-4612-2580-5_12.

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Rizzoni, Giorgio. "Powertrain Control for Hybrid-Electric and Electric Vehicles." In Encyclopedia of Systems and Control, 1090–99. London: Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-5058-9_75.

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Rizzoni, Giorgio. "Powertrain Control for Hybrid-Electric and Electric Vehicles." In Encyclopedia of Systems and Control, 1–10. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5102-9_75-1.

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Rizzoni, Giorgio. "Powertrain Control for Hybrid-Electric and Electric Vehicles." In Encyclopedia of Systems and Control, 1761–70. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-44184-5_75.

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Butts, Ken. "Hybrid Models for Automotive Powertrain Systems: Revisiting a Vision." In Hybrid Systems: Computation and Control, 1–2. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-46430-1_1.

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Beydoun, Ali, Le Yi Wang, Jing Sun, and Shiva Sivashanka. "Hybrid control of automotive powertrain systems: A case study." In Hybrid Systems: Computation and Control, 33–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-64358-3_30.

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Di Cairano, Stefano, Diana Yanakiev, Alberto Bemporad, Ilya Kolmanovsky, and Davor Hrovat. "Model Predictive Powertrain Control: An Application to Idle Speed Regulation." In Automotive Model Predictive Control, 183–94. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-071-7_12.

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Hu, Donghai, and Bifeng Yin. "Control Methodology of Stability Optimization for HEV Powertrain." In Key Technologies on New Energy Vehicles, 107–41. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5051-2_5.

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Hu, Donghai, and Bifeng Yin. "Control Methodology of Stability Optimization for EV Powertrain." In Key Technologies on New Energy Vehicles, 19–47. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5051-2_2.

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Conference papers on the topic "Powertrain control"

1

Yi, Chenyu, and Bogdan Epureanu. "Control and Design Optimization of a Novel Hybrid Electric Powertrain System." In ASME 2017 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dscc2017-5200.

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Control and design optimization of hybrid electric powertrains is necessary to maximize the benefits of novel architectures. Previous studies have proposed multiple optimal and near-optimal control methods, approaches for design optimization, and ways to solve coupled design and control optimization problems for hybrid electric powertrains. This study presents control and design optimization of a novel hybrid electric powertrain architecture to evaluate its performance and potential using physics-based models for the electric machines, the battery and a near-optimal control, namely the equivalent consumption minimization strategy. Design optimization in this paper refers to optimizing the sizes of the powertrain components, i.e. electric machines, battery and final drive. The control and design optimization problem is formulated using nested approach with sequential quadratic programming as design optimization method. Metamodeling is applied to abstract the near-optimal powertrain control model to reduce the computational cost. Fuel economy, sizes of components, and consistency of city and highway fuel economy are reported to evaluate the performance of the powertrain designs. The results suggest an optimal powertrain design and control that grants good performance. The optimal design is shown to be robust and non-sensitive to slight component size changes when evaluated for the near-optimal control.
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Bai, Shushan, Daniel Brennan, Donald Dusenberry, Xuefeng Tao, and Zhen Zhang. "Integrated Powertrain Control." In SAE 2010 World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2010. http://dx.doi.org/10.4271/2010-01-0368.

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Narumi, N., H. Suzuki, and R. Sakakiyama. "Trends of Powertrain Control." In Convergence International Congress & Exposition On Transportation Electronics. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1990. http://dx.doi.org/10.4271/901154.

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Jin, Xiaoqing, Jyotirmoy V. Deshmukh, James Kapinski, Koichi Ueda, and Ken Butts. "Powertrain control verification benchmark." In HSCC'14: 17th International Conference on Hybrid Systems: Computation and Control. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2562059.2562140.

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Hettich, Gerhard, and Günther Alberter. "Architectures for Electronic Powertrain Control." In SAE International Congress and Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1997. http://dx.doi.org/10.4271/970024.

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Main, J. J. "Ford ELTEC Integrated Powertrain Control." In SAE International Congress and Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1986. http://dx.doi.org/10.4271/860652.

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Gupta, Pinaki, and Andrew Alleyne. "Powertrain Optimization for an Earthmoving Vehicle." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60023.

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The advent of integrated powertrain technologies offers great potential for improvements in efficiency and transient performance of powertrains. This work examines the integration of various powertrain subsystems onboard an earthmoving vehicle. The nature of the variable displacement pumping subsystem is similar in concept to other forms of continuously variable transmissions. Separate controllers are designed using gain scheduled H∞ synthesis to address the problems of efficiency and performance. Both controllers are combined through switching logic to enable explicit tradeoffs between the objectives and thus improve the powertrain productivity. The devised control strategies are implemented on a hardware-in-the-loop representation of an earthmoving vehicle powertrain. The baseline efficiency controller is further improved by a hybrid design that effectively deactivates part of the powertrain system when not in use.
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Corti, Enrico, and Luca Solieri. "Rapid Control Prototyping System for Combustion Control." In Powertrain & Fluid Systems Conference & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2005. http://dx.doi.org/10.4271/2005-01-3754.

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Gravel, Dave, Frank Maslar, George Zhang, Srini Nidamarthi, Heping Chen, and Tom Fuhlbrigge. "Toward robotizing powertrain assembly." In 2008 7th World Congress on Intelligent Control and Automation. IEEE, 2008. http://dx.doi.org/10.1109/wcica.2008.4592981.

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"Advanced Control for Energy Efficient Powertrain." In 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE). IEEE, 2019. http://dx.doi.org/10.1109/isie.2019.8781088.

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Reports on the topic "Powertrain control"

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Smith, David E. Powertrain Controls Optimization for HD Hybrid Line Haul Trucks - FY2014 Annual Report. Office of Scientific and Technical Information (OSTI), December 2014. http://dx.doi.org/10.2172/1185822.

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Smith, David, Paul Chambon, and Dean Deter. Simulation and controls for medium and heavy duty dual mode hybrid powertrain. Office of Scientific and Technical Information (OSTI), September 2014. http://dx.doi.org/10.2172/1167675.

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Jehlik, Forrest, Simeon Iliev, and Thomas Wallner. Testing and Optimization of Powertrain Controls for Hybrid-Electric MD Delivery Truck for XL Hybrids: Final CRADA Report. Office of Scientific and Technical Information (OSTI), December 2019. http://dx.doi.org/10.2172/1581766.

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