ADAPTIVE MODEL BASED COMBUSTION PHASING CONTROL FOR MULTI FUEL SPARK IGNITION ENGINES

This research describes a physics-based control-oriented feed-forward model, combined with cylinder pressure feedback, to regulate combustion phasing in a spark-ignition engine operating on an unknown mix of fuels. This research may help enable internal combustion engines that are capable of on-the-fly adaptation to a wide range of fuels. These engines could; (1) facilitate a reduction in bio-fuel processing, (2) encourage locally-appropriate bio-fuels to reduce transportation, (3) allow new fuel formulations to enter the market with minimal infrastructure, and (4) enable engine adaptation to pump-to-pump fuel variations. These outcomes will help make bio-fuels cost-competitive with other transportation fuels, lessen dependence on traditional sources of energy, and reduce greenhouse gas emissions from automobiles; all of which are pivotal societal issues. Spark-ignition engines are equipped with a large number of control actuators to satisfy fuel economy targets and maintain regulated emissions compliance. The increased control flexibility also allows for adaptability to a wide range of fuel compositions, while maintaining efficient operation when input fuel is altered. Ignition timing control is of particular interest because it is the last control parameter prior to the combustion event, and significantly influences engine efficiency and emissions. Although Map-based ignition timing control and calibration routines are state of art, they become cumbersome when the number of control degrees of freedom increases are used in the engine. The increased system complexity motivates the use of model-based methods to minimize product development time and ensure calibration flexibility when the engine is altered during the design process. A closed loop model based ignition timing control algorithm is formulated with: 1) a feed forward fuel type sensitive combustion model to predict combustion duration from spark to 50% mass burned; 2) two virtual fuel property observers for octane number and laminar flame speed feedback; 3) an adaptive combustion phasing target model that is able to self-calibrate for wide range of fuel sources input. The proposed closed loop algorithm is experimentally validated in real time on the dynamometer. Satisfactory results are observed and conclusions are made that the closed loop approach is able to regulate combustion phasing for multi fuel adaptive SI engines

Design of a perfect-tracking soft-landing controller for electromagnetic switching devices

Electromagnetic switching devices such as electromechanical relays and solenoid valves suffer from impacts and mechanical wear when they are activated using a constant-voltage policy. This paper presents a new control approach that aims at achieving soft landing in these devices, i.e., a movement without neither impacts nor bouncing. The hybrid nonlinear dynamics of the system is firstly described taking into account the limited range of motion that characterizes this class of devices. Then, the nonlinear expression of the control law is derived and a method to design a soft-landing reference trajectory is proposed. It is shown that, when certain conditions are met, the design methodology presented in the paper results in a controller that achieves perfect tracking of the reference trajectory and, hence, soft landing is accomplished. The theoretical analysis is validated by simulation using a dynamical model of a specific switching device

Statistical investigation on effect of Electroless coating Parameter on Coating Morphology of Short Basalt Fiber.

The Objective of the present paper is to investigate the effect of electroless coating parameters, such as Sensitization time (A), Activation time (B) and Metallization time (C), on the coating morphology of the basalt short fiber and the optimization of the coating process parameters based on L27 Taguchi orthogonal design. Coated and non-coated basalt short fiber, typically used with 7075 Aluminium alloy as einforcement, is studied. The effect of coating the short basalt fiber with copper has proved beneficial to interfacial bonding (wettability) between the reinforcement and the matrix. The interface between the matrix and the reinforcement plays a crucial role in determining the properties of metal matrix composites (MMCs). An L27 array was used to accommodate the three levels of factors as well as their interaction effects. From the Taguchi methodology, the optimal combinations for coating parameters were found to be A1B3C3 (i.e., 5 min. sensitization time, 15 min. activation time and 3 min. for metallization time). In addition, the interaction between pH value and the coating time and that between the coating time and the temperature, influence the coating parameters significantly. Furthermore, a statistical analysis of variance reveals that the metallization time has the highest influence followed by the activation time and the sensitization time. Finally, confirmation tests were carried out to verify the experimental results, Scanning Electron Microscopic (SEM) & Energy Dispersive Spectroscope (EDS) studies were carried out on basalt fiber

High-precision hydraulic pressure control based on linear pressure-drop modulation in valve critical equilibrium state

High precision and fast response are of great significance for hydraulic pressure control in automotive braking systems. In this paper, a novel sliding mode control based high-precision hydraulic pressure feedback modulation is proposed. Dynamical models of the hydraulic brake system including valve dynamics are established. An open loop load pressure control based on the linear relationship between the pressure-drop and coil current in valve critical open equilibrium state is proposed, and also experimentally validated on a hardware-in-the-loop test rig. The control characteristics under different input pressures and varied coil currents are investigated. Moreover, the sensitivity of the proposed modulation on valve's key structure parameters and environmental temperatures are explored with some unexpected drawbacks. In order to achieve better robustness and precision, a sliding mode control based closed loop scheme is developed for the linear pressure-drop modulation. Comparative tests between this method and the existing methods are carried out. The results validate the effectiveness and superior performance of the proposed closed loop modulation method

Volume 3 – Conference

We are pleased to present the conference proceedings for the 12th edition of the International Fluid Power Conference (IFK). The IFK is one of the world’s most significant scientific conferences on fluid power control technology and systems. It offers a common platform for the presentation and discussion of trends and innovations to manufacturers, users and scientists. The Chair of Fluid-Mechatronic Systems at the TU Dresden is organizing and hosting the IFK for the sixth time. Supporting hosts are the Fluid Power Association of the German Engineering Federation (VDMA), Dresdner Verein zur Förderung der Fluidtechnik e. V. (DVF) and GWT-TUD GmbH. The organization and the conference location alternates every two years between the Chair of Fluid-Mechatronic Systems in Dresden and the Institute for Fluid Power Drives and Systems in Aachen. The symposium on the first day is dedicated to presentations focused on methodology and fundamental research. The two following conference days offer a wide variety of application and technology orientated papers about the latest state of the art in fluid power. It is this combination that makes the IFK a unique and excellent forum for the exchange of academic research and industrial application experience. A simultaneously ongoing exhibition offers the possibility to get product information and to have individual talks with manufacturers. The theme of the 12th IFK is “Fluid Power – Future Technology”, covering topics that enable the development of 5G-ready, cost-efficient and demand-driven structures, as well as individual decentralized drives. Another topic is the real-time data exchange that allows the application of numerous predictive maintenance strategies, which will significantly increase the availability of fluid power systems and their elements and ensure their improved lifetime performance. We create an atmosphere for casual exchange by offering a vast frame and cultural program. This includes a get-together, a conference banquet, laboratory festivities and some physical activities such as jogging in Dresden’s old town.:Group 8: Pneumatics Group 9 | 11: Mobile applications Group 10: Special domains Group 12: Novel system architectures Group 13 | 15: Actuators & sensors Group 14: Safety & reliabilit

Sensorless Nonlinear Stroke Controller for an Implantable, Undulating Membrane Blood Pump

This paper describes an original methodology to operate a new nonlinear vibrating membrane pump, actuated by a moving magnet actuator without the use of a motion sensor, in the scope of cardiac assistance. A nonlinear mathematical model of the system is established and used to parametrize a nonlinear position observer that uses the coils current as an input and which output is a feedback to a stroke controller. Actuator’s parameters are identified by a recursive least square algorithm and direct measurements. Finally, a numerical experiment illustrates the implementation of the algorithm and its possible applications

An electromechanical valve drive incorporating a nonlinear mechanical transformer

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (leaves 145-147).In traditional internal combustion engines, a camshaft acts on the valve stems to open and close the valves. Valve timing is fixed relative to piston position. On the other hand, if a valve is flexibly controlled by a variable valve actuation (VVA) system, we can achieve significant improvements in fuel efficiency, engine performance, and emissions. One of the most advanced variable valve actuation systems is the VVA operated by an electromechanical actuator without a camshaft, the so-called bi-positional electromechanical valve drive (EMVD). Existing EMVDs characteristically use a spring to provide the required mechanical power for operating a valve. The use of a spring provides many benefits to the design of the system, but it also results in difficult design challenges. The large holding force against the spring at the ends of the stroke suggests the use of a normal-force electromagnetic actuator, which, from a servomechanical point of view, is considerably inferior to a shear-force actuator. Furthermore, the large holding force generates a large jerk at the beginning and the end of a stroke and makes it difficult to achieve soft valve landing. An innovative electromechanical valve drive (EMVD) design is proposed, which incorporates a nonlinear mechanical transformer and a shear-force actuator. This allows not only fast but also smooth valve motion, almost zero seating velocity, zero holding power, and improved control with acceptable electric power. This proposed concept is modeled, analyzed, simulated, designed, and implemented. Experimental results show the beneficial features of the promising proposed concept.by Woo Sok Chang.Ph.D

Semi-Physical Real-Time Models with State and Parameter Estimation for Diesel Engines

Increasing requirements for the reduction of fuel consumption (CO2) and emissions require a precise electronic management of combustion engines. Engine-related measures to meet these requirements lead to an increase in variability and system complexity. To cope with increasing system complexity, model-based development methodology has proven effective. In this context, virtual development with real-time models plays an increasingly important role. The corresponding models can either be derived theoretically on the basis of known physical laws (white-box models) or obtained experimentally on the test bench by mathematically modeling the measured input and output behavior (black-box models). Both types of modeling have their advantages and disadvantages. A semi-physical modeling methodology is presented that combines the advantages of theoretical and experimental modeling and overcomes their disadvantages. The goal is to find suitable, simplified equation structures and to determine their unknown parameters experimentally by real-time capable, recursive parameter estimation methods. This leads to physically interpretable real-time models that are able to adapt their parameters according to the current engine operating behavior and thus offer good transferability to other engines. The semi-physical modeling methodology is applied to the air system and combustion of a common rail diesel engine with a variable exhaust gas turbocharger and high- and low-pressure exhaust gas recirculation. The focus lies on the derivation of semi-physical real-time model for the combustion and its underlying processes inside the cylinder. A semi-physical model approach for modeling the dynamics of combustion chamber processes is developed and combined with state and parameter estimation methods. This model approach enables crank angle-resolved calculation of the in-cylinder gas states and the determination of the characteristic combustion components of diesel combustion (premixed, diffusive combustion and burn-out). The technical implementation is realized close to the pressure indication system of the engine test bench, enabling a crankshaft-resolved model adaptation based on measured in-cylinder pressure. Model identification is performed using combined state and parameter estimation in steady-state engine operation. Model parameters are estimated perpetually for each duty cycle and converge to a constant value within 30-60 engine duty cycles. Final estimation results are stored as functions of engine operating point using experimental modeling. In this way, semi-physical real-time models are created directly online during the measurement. The treated method is considered as an extension of the functionality of conventional pressure indication systems. Furthermore, the derived semi-physical models are used for real-time engine simulation in the context of hardware-in-the-loop testing of ECUs. The research project (Project No. 1231) was financially and advisory supported by the Research Association for Combustion Engines (FVV) e.V. (Frankfurt am Main, Germany)

Design and investigation of a diesel engine operated on pilot ignited LPG

This thesis explores the idea of igniting LPG in a compression ignition diesel engine using pilot diesel injection as spark ignition medium. The main advancement in using this technology on current diesel engines is the establishment of a better balance between NOx and PM emissions without losing too much of the CO2 benefits of diesel. With the advent of common rail diesel engines, it is now possible to get control of pilot diesel injection and make the LPG and diesel control systems work together. Combined diesel and LPG operation is a new subject for engine research, so the thesis moves on to consider the results from detailed engine simulation studies that explore the potential benefits of the mix. Subsequent simulations of a modern four cylinder dCi engine suggest that with closer control over the pilot diesel injection, diesel like performance can be obtained, hopefully with less emissions than currently expected from diesel only operation. A single cylinder variable compression ratio research engine was developed to explore diesel /LPG dual fuel operation. A second generation common rail injection rig was also developed for the engine and for fuel spray characterisation. Engine experiments proved the concept of using a modest charge of pilot injected diesel for igniting a larger dose of port injected LPG. The experimental work results suggest that combining diesel common rail injection technology with the state of the art LPG injection systems, it is possible to establish a better balance between NOx/ PM emissions without losing too much of the CO2 benefits from the diesel operation

Combustion Phasing Modeling for Control of Spark-Assisted Compression Ignition Engines

Substantial fuel economy improvements for light-duty automotive engines demand novel combustion strategies. Low temperature combustion (LTC) demonstrates potential for significant fuel efficiency improvement; however, control complexity is an impediment for real-world transient operation. Spark-assisted compression ignition (SACI) is an LTC strategy that applies a deflagration flame to generate sufficient energy to trigger autoignition in the remaining charge. For other LTC strategies, control of autoignition timing is difficult as there is no direct actuator for combustion phasing. SACI addresses this challenge by using a spark plug to initiate a flame that then triggers autoignition in a significant portion of the charge. The flame propagation phase limits the rate of cylinder pressure increase, while autoignition rapidly completes combustion. High dilution is generally required to maintain production-feasible reaction rates. This high dilution, however, increases the likelihood of flame quench, and therefore potential misfires. Mitigating these competing constraints requires careful mixture preparation strategies for SACI to be feasible in production. Operating a practical engine within this restrictive regime is a key modeling and control challenge. Current models are not sufficient for control-oriented work such as calibration optimization, transient control strategy development, and real-time control. To resolve the modeling challenge, a fast-running cylinder model is developed and presented in this work. It comprises of five bulk gas states and a fuel stratification model comprising of ten equal-mass zones within the cylinder. The zones are quasi-dimensional, and their state varies with crank angle to capture the effect of fuel spray and mixing. For each zone, combustion submodels predict flame propagation burn duration, autoignition phasing, and the concentration of oxides of nitrogen. During the development of the combustion submodels, both physics-based and data-driven techniques are considered. However, the best balance between accuracy and computational expense leads to the nearly exclusive selection of data-driven techniques. The data-driven models are artificial neural networks (ANNs), trained to an experimentally-validated one-dimensional (1D) engine reference model. The simplified model matches the reference 1D engine model with an R2 value of 70‒96% for key combustion parameters. The model requires 0.8 seconds to perform a single case, a 99.6% reduction from the reference 1D engine model. The reduced model simulation time enables rapid exploration of the control space. Over 250,000 cases are evaluated across the entire range of actuator positions. From these results, a transient-capable calibration is formulated. To evaluate the strength of the steady-state calibration, it is operated over a tip-in and tip-out. The response to the transients required little adjustment, suggesting the steady-state calibration is robust. The model also demonstrates the capability to adapt in-cylinder state and spark timing to offset combustion phasing disturbances. This positive performance suggests the candidate model developed in this work retains sufficient accuracy to be beneficial for control-oriented objectives. There are four contributions of this research: 1) a demonstration of the impact of combustion fundamentals on SACI combustion, 2) an identification of suitable techniques for data-driven modeling, 3) a quasi-dimensional fuel stratification model for radially-stratified engines, and 4) a comprehensive cylinder model that maintains high accuracy despite substantially reduced computational expense