Christopher H. Onder

Bio: Christopher H. Onder is an academic researcher from ETH Zurich. The author has contributed to research in topics: Fuel efficiency & Optimal control. The author has an hindex of 30, co-authored 180 publications receiving 4433 citations. Previous affiliations of Christopher H. Onder include University of Zurich & Springer Science+Business Media.

Introduction to Modeling and Control of Internal Combustion Engine Systems

Abstract: Internal combustion engines (ICE) still have potential for substantial improvements, particularly with regard to fuel efficiency and environmental compatibility. In order to fully exploit the remaining margins, increasingly sophisticated control systems have to be applied. This book offers an introduction to cost-effective model-based control-system design for ICE. The primary emphasis is put on the ICE and its auxiliary devices. Mathematical models for these processes are developed and solutions for selected feedforward and feedback control-problems are presented. The discussions concerning pollutant emissions and fuel economy of ICE in automotive applications constantly intensified since the first edition of this book was published. Concerns about the air quality, the limited resources of fossil fuels and the detrimental effects of greenhouse gases exceedingly spurred the interest of both the industry and academia in further improvements. The most important changes and additions included in this second edition are: - restructured and slightly extended section on superchargers; - short subsection on rotational oscillations and their treatment on engine test-benches; - complete section on modeling, detection, and control of engine knock; - improved physical and chemical model for the three-way catalytic converter; - new methodology for the design of an air-to-fuel ratio controller; - short introduction to thermodynamic engine-cycle calculation and corresponding control-oriented aspects. (orig.)

An integrated perfusion machine preserves injured human livers for 1 week.

Abstract: The ability to preserve metabolically active livers ex vivo for 1 week or more could allow repair of poor-quality livers that would otherwise be declined for transplantation. Current approaches for normothermic perfusion can preserve human livers for only 24 h. Here we report a liver perfusion machine that integrates multiple core physiological functions, including automated management of glucose levels and oxygenation, waste-product removal and hematocrit control. We developed the machine in a stepwise fashion using pig livers. Study of multiple ex vivo parameters and early phase reperfusion in vivo demonstrated the viability of pig livers perfused for 1 week without the need for additional blood products or perfusate exchange. We tested the approach on ten injured human livers that had been declined for transplantation by all European centers. After a 7-d perfusion, six of the human livers showed preserved function as indicated by bile production, synthesis of coagulation factors, maintained cellular energy (ATP) and intact liver structure.

Convex Optimization for the Energy Management of Hybrid Electric Vehicles Considering Engine Start and Gearshift Costs

Abstract: 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.

Control of an SCR catalytic converter system for a mobile heavy-duty application

Abstract: Selective catalytic reduction (SCR) is well known for exhaust gas aftertreatment in power plant applications. In the near future, it will be introduced in Europe in mobile heavy-duty diesel applications. Stringent specifications and the dynamic operation mode of such applications demand advanced control strategies. Such a control strategy is presented here. It incorporates a model-based feedforward controller (FFC) which handles the known dynamics of the plant. It further contains a feedback controller (FBC) to compensate for disturbances and slowly varying parameters. The realization of the feedback control loop is possible only due to the use of a nitrogen oxide (NO/sub x/) sensor which is cross-sensitive against ammonia (NH/sub 3/), and the implementation of a procedure separating the detection of NO/sub x/ and NH/sub 3/.

Control of hybrid electric vehicles

Abstract: Global optimization techniques, such as dynamic programming, serve mainly to evaluate the potential fuel economy of a given powertrain configuration. Unless the future driving conditions can be predicted during real-time operation but the results obtained using this noncausal approach establish a benchmark for evaluating the optimality of realizable control strategies. Real-time controllers must be simple in order to be implementable with limited computation and memory resources. Moreover, manual tuning of control parameters should be avoided. This article has analyzed two approaches, namely, feedback controllers and ECMS. Both of these approaches can lead to system behavior that is close to optimal, with feedback controllers based on dynamic programming. Additional challenges stem from the need to apply optimal energy-management controllers to advanced HEV architectures, such as combined and plug-in HEVs, as well as to optimization problems that include performance indices in addition to fuel economy, such as pollutant emissions, driveability, and thermal comfort

Optimal control of parallel hybrid electric vehicles

Abstract: In this paper, a model-based strategy for the real-time load control of parallel hybrid vehicles is presented. The aim is to develop a fuel-optimal control which is not relying on the a priori knowledge of the future driving conditions (global optimal control), but only upon the current system operation. The methodology developed is valid for those problem that are characterized by hard constraints on the state-battery state-of-charge (SOC) in this application-and by an arc cost-fuel consumption rate-which is not an explicit function of the state. A suboptimal control is found with a proper definition of a cost function to be minimized at each time instant. The "instantaneous" cost function includes the fuel energy and the electrical energy, the latter related to the state constraints. In order to weight the two forms of energy, a new definition of the equivalence factors has been derived. The strategy has been applied to the "Hyper" prototype of DaimlerChrysler, obtained from the hybridization of the Mercedes A-Class. Simulation results illustrate the potential of the proposed control in terms of fuel economy and in keeping the deviations of SOC at a low level.