SoftcOVel: reprint of the hardcover 1st edition 2004 The use of general descriptive names, registered names trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Preface Who should read this text?This text is intended for students interested in the design of classical and novel IC engine control systems. Its focus lies on the control-oriented mathematical description of the physical processes involved and on the model-based control system design and optimization. This text has evolved from a lecture series held during the last several years in the mechanical engineering (ME) department at ETH Zurich. The presumed audience is graduate ME students with a thorough understanding of basic thermodynamic and fluid dynamics processes in internal combustion engines (ICE). Other prerequisites are knowledge of general ME topics (calculus, mechanics, etc.) and a first course in control systems. Students with little preparation in basic ICE modeling and design are referred to [52] Why has this text been written?Internal combustion engines represent one of the most important technological success stories in the last 100 years. These systems have become the most frequently used sources of propulsion energy in passenger cars. One of the main reasons that this has occurred is the very high energy density of liquid hydrocarbon fuels. As long as fossil fuel resources are used to fuel cars, there are no foreseeable alternatives that offer the same benefits in terms of cost, safety, pollutant emission and fuel economy (always in a total cycle, or "wellto-wheel" sense, see e.g., [5] and [55]).Internal combustion engines still have a substantial potential for improvements; Diesel (compression ignition) engines can be made much cleaner and Otto (spark ignition) engines still can be made much more fuel efficient. Each goal can be achieved only with the help of control systems. Moreover, with the systems becoming increasingly complex, systematic and efficient system VI Preface design procedures have become technological and commercial necessities. This text addresses these issues by offering an introduction to model-based control system design for ICE. What can be learned from this text?The primary emphasis is put on the ICE (torque production, pollutant formation, etc.) and its auxiliary devices (air-charge control, mixture formation, pollutant abatement systems, etc.). Mathematical models for some of these processes will be developed below. Using these models, selected feedforward and feedback control problems will then be discussed.A model-based approach is chosen because, even though more cumbersome in the beginning, it after proves to be the most cost-effective in the long run. Especially the control system development and calibration processes benefit greatly from mathematical models at early project stages.The appendix contains a brief summary of the most important control...

tandard preservation of donor livers is performed by flushing the organ with a cold solution at the time of procurement, which is followed by static storage on ice. This approach reduces liver metabolic activity, allowing safe storage for up to 12-18 h (refs. 1,2). Recently, the combination of supercooling with subzero storage (−4 °C) and hypothermic, as well as subnormothermic, machine perfusion achieved an extension of the preservation time of human livers up to 27 h (ref. 2). By contrast, human livers can also be kept metabolically fully active for up to 24 h by supplying normothermic blood or oxygenated fluids in a controlled environment by machine perfusion 1,3-5. The possibility of repairing poor-quality livers sufficiently to enable transplantation requires preserving metabolically active livers 1,3 for several days. Accordingly, the need for long-term organ preservation technology has been endorsed by multiple private and governmental initiatives 1. However, currently used normothermic machine perfusion technologies have been used only for a relatively short time period (for example, a median perfusion time of 9 h (ref. 5)), to successfully maintain hemodynamics, perfusate oxygenation and temperature. We sought to extend perfusion time beyond 24 h by engineering a perfusion machine that recapitulates additional core body functions that are critical to liver health. We chose 7-d as a target because this time period has been shown to offer a credible time frame for inducing clinically relevant liver regeneration in patients undergoing complex liver resection 6-8. Under physiologic conditions, the liver, which constitutes 2.5% of body weight, receives 25% of the blood output of the heart and performs >5,000 functions 9. It has a unique dual vascular supply with high-pressure, oxygen-rich arterial blood entering through the hepatic artery and low-pressure, oxygen-reduced portal vein blood draining the abdominal viscera. Its high metabolic activity produces waste products that are excreted in the bile or removed by hepatic macrophages or the kidneys. The metabolic profile is largely controlled by pancreatic hormones, including insulin and glucagon. Our perfusion technology, developed in the "Liver4Life project", includes automated control of glucose levels by injection of insulin and glucagon, a dialysis membrane for waste-product removal, regulation of oxygenation and liver movement to prevent pressure necrosis. Results Liver perfusion machine. Our perfusion machine (Fig. 1a,b) recapitulates blood supply through the two vascular entries of the liver, the hepatic artery and portal vein. The hepatic artery is supplied with oxygen-rich blood at elevated pressure (mean arterial pressure (MAP) ≥ 65 mmHg) in a pulsatile manner (Fig. 1c), whereas the portal vein receives blood at low pressure (around 5-10 mmHg) with a reduced oxygen content (venous blood, non-pulsatile). The system maintains oxygen saturation of 65% in the vena cava by continuously adjusting oxygen content in the portal vein (Fig. 1d). In vivo, nutr...

The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.

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This paper presents a novel method to solve the energy management problem for hybrid electric vehicles (HEVs) with engine start and gearshift costs. The method is based on a combination of deterministic dynamic programming (DP) and convex optimization. As demonstrated in a case study, the method yields globally optimal results while returning the solution in much less time than the conventional DP method. In addition, the proposed method handles state constraints, which allows for the application to scenarios where the battery state of charge (SOC) reaches its boundaries.

In this paper we study models and coordination policies for intermodal Autonomous Mobility-on-Demand (AMoD), wherein a fleet of self-driving vehicles provides ondemand mobility jointly with public transit. Specifically, we first present a network flow model for intermodal AMoD, where we capture the coupling between AMoD and public transit and the goal is to maximize social welfare. Second, leveraging such a model, we design a pricing and tolling scheme that allows to achieve the social optimum under the assumption of a perfect market with selfish agents. Finally, we present a real-world case study for New York City. Our results show that the coordination between AMoD fleets and public transit can yield significant benefits compared to an AMoD system operating in isolation.

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