148 research outputs found
Design, Modelling and Verification of Distributed Electric Drivetrain
The electric drivetrain in a battery electric vehicle (BEVs) consists of an electric machine, an inverter, and a transmission. The drivetrain topology of available BEVs, e.g., Nissan Leaf, is centralized with a single electric drivetrain used to propel the vehicle. However, the drivetrain components can be integrated mechanically, resulting in a more compact solution. Furthermore, multiple drivetrain units can propel the vehicle resulting in a distributed drive architecture, e.g., Tesla Model S. Such drivetrains provide an additional degree of control and topology optimization leading to cheaper and more efficient solutions. To reduce the cost, the drivetrain unit in a distributed drivetrain can be standardized. However, to standardize the drivetrain, the drivetrain needs to be dimensioned such that the performance of a range of different vehicles can be satisfied. This work investigates a method for dimensioning the torque and power of an electric drivetrain that could be standardized across different passenger and light-duty vehicles. A system modeling approach is used to verify the proposed method using drive cycle simulations. The laboratory verification of such drivetrain components using a conventional dyno test bench can be expensive. Therefore, alternative methods such as power-hardware-in-the-loop (PHIL) and mechanical-hardware-in-the-loop (MHIL) are investigated. The PHIL test method for verifying inverters can be inexpensive as it eliminates the need for rotating electric machines. In this method, the inverter is tested using a machine emulator consisting of a voltage source converter and a coupling network, e.g., inductors and transformer. The emulator is controlled so that currents and voltages at the terminals resemble a machine connected to a mechanical load. In this work, a 60-kW machine emulator is designed and experimentally verified. In the MHIL method, the real-time simulation of the system is combined with a dyno test bench. One drivetrain is implemented in the dyno test bench, while the remaining are simulated using a real-time simulator to utilize this method for distributed drivetrain systems. Including the remaining drivetrains in the real-time simulation eliminates the need for a full-scale dyno test bench, providing a less expensive method for laboratory verification. An MHIL test bench for verification of distributed drivetrain control and components is also designed and experimentally verified
Design and Application of Electrical Machines
Electrical machines are one of the most important components of the industrial world. They are at the heart of the new industrial revolution, brought forth by the development of electromobility and renewable energy systems. Electric motors must meet the most stringent requirements of reliability, availability, and high efficiency in order, among other things, to match the useful lifetime of power electronics in complex system applications and compete in the market under ever-increasing pressure to deliver the highest performance criteria. Today, thanks to the application of highly efficient numerical algorithms running on high-performance computers, it is possible to design electric machines and very complex drive systems faster and at a lower cost. At the same time, progress in the field of material science and technology enables the development of increasingly complex motor designs and topologies. The purpose of this Special Issue is to contribute to this development of electric machines. The publication of this collection of scientific articles, dedicated to the topic of electric machine design and application, contributes to the dissemination of the above information among professionals dealing with electrical machines
Compendium in Vehicle Motion Engineering
This compendium is written for the course “MMF062 Vehicle Motion Engineering” at Chalmers University of Technology. The compendium covers more than included in that course; both in terms of subsystem designs and in terms of some teasers for more advanced studies of vehicle dynamics. Therefore, it is also useful for the more advanced courses, such as “TME102 Vehicle Modelling and Control”.The overall objective of the compendium is to educate engineers that understand and can contribute to development of good motion and energy functionality of vehicles. The compendium focuses on road vehicles, primarily passenger cars and commercial vehicles. Smaller road vehicles, such as bicycles and single-person cars, are only very briefly addressed. It can be mentioned that there exist a lot of ground-vehicle types not covered at all, such as: off-road/construction vehicles, tracked vehicles, horse wagons, hovercrafts, and railway vehicles.Functions are needed for requirement setting, design and verification. The overall order within the compendium is that models/methods/tools needed to understand each function are placed before the functions. Chapters 3-5 describes (complete vehicle) “functions”, organised after vehicle motion directions:\ub7\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 Chapter 3:\ua0Longitudinal\ua0dynamics\ub7\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 Chapter 4:\ua0Lateral\ua0dynamics\ub7\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 Chapter 5:\ua0Vertical\ua0dynamicsChapter 1 introduces automotive industry and the overall way of working there and defines required pre-knowledge from “product-generic” engineering, e.g. modelling of dynamic systems.Chapter 2 also describes the subsystems relevant for vehicle dynamics:• Wheels and Tyre\ua0• Suspension\ua0• Propulsion\ua0• Braking System\ua0• Steering System\ua0• Environment Sensing SystemThe compendium is released in a new version each year, around October, which is the version your read now. A "latest draft" is more frequently updated and often includes some more, sometimes unfinished, material: https://chalmersuniversity.box.com/s/6igaen1ugcjzuhjziuon08axxiy817f
Information Theory and Its Application in Machine Condition Monitoring
Condition monitoring of machinery is one of the most important aspects of many modern industries. With the rapid advancement of science and technology, machines are becoming increasingly complex. Moreover, an exponential increase of demand is leading an increasing requirement of machine output. As a result, in most modern industries, machines have to work for 24 hours a day. All these factors are leading to the deterioration of machine health in a higher rate than before. Breakdown of the key components of a machine such as bearing, gearbox or rollers can cause a catastrophic effect both in terms of financial and human costs. In this perspective, it is important not only to detect the fault at its earliest point of inception but necessary to design the overall monitoring process, such as fault classification, fault severity assessment and remaining useful life (RUL) prediction for better planning of the maintenance schedule. Information theory is one of the pioneer contributions of modern science that has evolved into various forms and algorithms over time. Due to its ability to address the non-linearity and non-stationarity of machine health deterioration, it has become a popular choice among researchers. Information theory is an effective technique for extracting features of machines under different health conditions. In this context, this book discusses the potential applications, research results and latest developments of information theory-based condition monitoring of machineries
Advances in Fluid Power Systems
The main purpose of this Special Issue of “Advances in Fluid Power Systems” was to present new scientific work in the field of fluid power systems for hydraulic and pneumatic control of machines and devices used in various industries. Advances in fluid power systems are leading to the creation of new smart devices that can replace tried-and-true solutions from the past. The development work of authors from various research centres has been published. This Special Issue focuses on recent advances and smart solutions for fluid power systems in a wide range of topics, including: • Fluid power for IoT and Industry 4.0: smart fluid power technology, wireless 5G connectivity in fluid power, smart components, and sensors.• Fluid power in the renewable energy sector: hydraulic drivetrains for wind power and for wave and marine current power, and hydraulic systems for solar power. • Hybrid fluid power: hybrid transmissions, energy recovery and accumulation, and energy efficiency of hybrid drives.• Industrial and mobile fluid power: industrial fluid power solutions, mobile fluid power solutions, eand nergy efficiency solutions for fluid power systems.• Environmental aspects of fluid power: hydraulic water control technology, noise and vibration of fluid power components, safety, reliability, fault analysis, and diagnosis of fluid power systems.• Fluid power and mechatronic systems: servo-drive control systems, fluid power drives in manipulators and robots, and fluid power in autonomous solutions
Experimental modelling and optimal torque vectoring control for 4WD vehicles
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis paper addresses the design of a torque vectoring architecture to control the four electrical machines in a four wheel-drive (4WD) formula-type competition vehicle. The scheme includes a new yaw-rate controller and a novel optimal torque distribution algorithm. Two yaw-rate controllers are proposed: one based on H8 optimal control and another based on linear parameter varying (LPV) system concepts. Both controllers are designed using an extended bicycle model validated with experimental data. Simulation results shown the effectiveness of the proposed overall control scheme in terms of energy efficiency, cornering speed and stability no matter the high-demanding working conditions. Such an effectiveness is quantitatively demonstrated by means of several key performance indicators chosen to ease the comparison of the proposed approach with respect to other reported works.Peer ReviewedPostprint (author's final draft
Towards Optimal Real-Time Automotive Emission Control
The legal bounds on both toxic and carbon dioxide emissions from automotive vehicles are continuously being lowered, forcing manufacturers to rely on increasingly advanced methods to reduce emissions and improve fuel efficiency. Though great strides have been made to date, there is still a large potential for continued improvement. Today, many subsystems in vehicles are optimized for static operation, where subsystems in the vehicle perform well at constant operating points. Extending optimal operation to the dynamic case through the use of optimal control is one method for further improvements.This thesis focuses on two subtopics that are crucial for implementing optimal control; dynamic modeling of vehicle subsystems, and methods for generating and evaluating computationally efficient optimal controllers. Though today\u27s vehicles are outfitted with increasingly powerful computers, their computational performance is low compared to a conventional PC. Any controller must therefore be very computationally efficient in order to feasibly be implemented. Furthermore, a sufficiently accurate dynamic model of the subsystem is needed in order to determine the optimal control value. Though many dynamic models of the vehicle\u27s subsystems exist, most do not fulfill the specific requirements set by optimal controllers.This thesis comprises five papers that, together, probe some methods of implementing dynamic optimal control in real-time. Two papers develop optimal control methods, one introduces and studies a cold-start model of the three-way catalyst, one paper extends the three-way catalyst model and studies optimal cold-start control, and one considers fuel-optimally controlling the speed of the engine in a series-hybrid. By combining the method and model papers we open for the potential to reduce toxic emissions by better managing cold-starts in hybrid vehicles, as well as reducing carbon dioxide emissions by operating the engine in a more efficient manner during transients
Techno-economic optimization and environmental evaluation of electric vehicles in commercial fleets
Die Einführung von batterieelektrischen Fahrzeugen (E-Pkw) gilt als eine wichtige Maßnahme zur Emissionsverringerung im Straßenverkehr. Gewerbliche Flotten in Deutschland bilden hierfür einen vielversprechenden Markt. Um dieses Potential zu realisieren, ist sowohl eine techno-ökonomische Optimierung als auch eine ökologische Bewertung über den Lebenszyklus erforderlich. Das Ziel der Dissertation ist es, hierfür ein methodisches Rahmenwerk zu liefern.
Die kumulative Dissertation besteht aus fünf Artikeln, die sich den einzelnen Bestandteilen des Rahmenwerks widmen und großteils auf Technologie- und Nutzungsdaten aus eigenen Messungen aufbauen. Der erste Artikel, Schücking et al. (2016) [Paper I], ist eine technische Analyse. Sie untersucht den realen Energieverbrauch von E-Pkws im Vergleich zu konventionellen Fahrzeugen und identifiziert optimale Betriebspunkte. Die Ergebnisse heben den Einfluss verschiedener Faktoren auf den Energieverbrauch als wichtige Komponente detaillierter techno-ökonomischer und ökologischer Betrachtungen hervor. Der zweite und der dritte Artikel haben einen techno-ökonomischen Fokus. Sie beschäftigen sich mit der Frage, wie E-Pkws einen schnelleren wirtschaftlichen Break-even im Vergleich zu konventionellen Fahrzeugen erreichen können. Der zweite Artikel, Schücking et al. (2017) [Paper II], stellt Ladestrategien vor, welche eine höhere Auslastung der E-Pkw ermöglichen und damit zu geringen Gesamtkosten im Vergleich zu konventionellen Pkw führen können. Unsicherheiten in Fahrprofilen und Energieverbrauch begrenzen die Anwendbarkeit dieser Strategien. Der dritte Artikel, Schücking & Jochem (2020) [Paper III], knüpft hieran an. Er schlägt ein zweistufiges stochastisches Optimierungsmodell zur Minimierung der Investition und Betriebskosten eines E-Pkw unter Berücksichtigung dieser Unsicherheiten vor. Neben der stochastischen Betrachtung ist auch die Abwägung zwischen Batteriekapazität und Ladeleistung in der Investitionsentscheidung ein neuer Beitrag zur Forschung. Im Kontext der stochastischen Optimierung werden ein Hidden Markov Modell zur Generierung komplexer Fahrprofile und eine neue Szenario-Reduktionsheuristik als methodische Weiterentwicklungen angewandt. Artikel vier und fünf liefern eine ökologische Bewertung. Die empirischen Daten sowie der Fokus auf den deutsch-französischen Grenzverkehr zeichnen beide Artikel aus. Der vierte Artikel, Ensslen et al. (2017) [Paper IV], konzentriert sich auf die E-Pkw Nutzungsphase. Er verdeutlicht den Einfluss unterschiedlicher Strommixe und Ladezeitpunkte auf die CO2- Emissionen und Reduktionspotentiale. Der fünfte Artikel, Held & Schücking (2019) [Paper V], betrachtet verschiedene ökologische Wirkungskategorien (wie z.B. Klimawandel, Versauerung Eutrophierung) über den gesamten Lebenszyklus mittels eines modularen Screening-Modells. Die Ergebnisse unterstreichen den Einfluss der Batterie und der Nutzungsphase auf die ökologische Gesamtbilanz. Dem übergreifenden Forschungsziel folgend, zeigen die Ergebnisse der einzelnen Artikel in ihrer Kombination, dass die Optimierung des wirtschaftlichen Nutzens auch die ökologischen Vorteile erhöhen kann. Die ex-ante Ermittlung der optimalen Batteriekapazität sowie ein hoher Betriebsgrad erhöhen nicht nur die Wettbewerbsfähigkeit von E-Pkw, sondern beschleunigen unter bestimmten Voraussetzungen auch den ökologischen Break-even in einem Großteil der betrachteten Wirkungskategorien. Die Eigenschaften, die gewerbliche Anwendungen aus wirtschaftlicher Sicht zu einem vielversprechenden Einführungsmarkt für E-Pkws machen, können damit auch die angestrebten ökologischen Vorteile unterstützen
Energy Management
Forecasts point to a huge increase in energy demand over the next 25 years, with a direct and immediate impact on the exhaustion of fossil fuels, the increase in pollution levels and the global warming that will have significant consequences for all sectors of society. Irrespective of the likelihood of these predictions or what researchers in different scientific disciplines may believe or publicly say about how critical the energy situation may be on a world level, it is without doubt one of the great debates that has stirred up public interest in modern times. We should probably already be thinking about the design of a worldwide strategic plan for energy management across the planet. It would include measures to raise awareness, educate the different actors involved, develop policies, provide resources, prioritise actions and establish contingency plans. This process is complex and depends on political, social, economic and technological factors that are hard to take into account simultaneously. Then, before such a plan is formulated, studies such as those described in this book can serve to illustrate what Information and Communication Technologies have to offer in this sphere and, with luck, to create a reference to encourage investigators in the pursuit of new and better solutions
Toward Holistic Energy Management Strategies for Fuel Cell Hybrid Electric Vehicles in Heavy-Duty Applications
The increasing need to slow down climate change for environmental protection demands further advancements toward regenerative energy and sustainable mobility. While individual mobility applications are assumed to be satisfied with improving battery electric vehicles (BEVs), the growing sector of freight transport and heavy-duty applications requires alternative solutions to meet the requirements of long ranges and high payloads. Fuel cell hybrid electric vehicles (FCHEVs) emerge as a capable technology for high-energy applications. This technology comprises a fuel cell system (FCS) for energy supply combined with buffering energy storages, such as batteries or ultracapacitors. In this article, recent successful developments regarding FCHEVs in various heavy-duty applications are presented. Subsequently, an overview of the FCHEV drivetrain, its main components, and different topologies with an emphasis on heavy-duty trucks is given. In order to enable system layout optimization and energy management strategy (EMS) design, functionality and modeling approaches for the FCS, battery, ultracapacitor, and further relevant subsystems are briefly described. Afterward, common methodologies for EMS are structured, presenting a new taxonomy for dynamic optimization-based EMS from a control engineering perspective. Finally, the findings lead to a guideline toward holistic EMS, encouraging the co-optimization of system design, and EMS development for FCHEVs. For the EMS, we propose a layered model predictive control (MPC) approach, which takes velocity planning, the mitigation of degradation effects, and the auxiliaries into account simultaneously
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