A New Combustion Pressure Sensor for Advanced Engine Management

Herden, W.; Küsell, Matthias

doi:10.4271/940379

Cited by 33 publications

(10 citation statements)

References 2 publications

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“…However, the equipment used in those experiments is far too expensive to be included in series production engines. Recently, new in-cylinder pressure sensors have been developed that are sufficiently robust and reasonably priced such that their inclusion in series production vehicles appears possible (see e.g., [79] and [174]). …”

Section: General Remarksmentioning

confidence: 99%

Introduction to Modeling and Control of Internal Combustion Engine Systems

2004

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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...

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Section: General Remarksmentioning

confidence: 99%

Introduction to Modeling and Control of Internal Combustion Engine Systems

2004

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“…Based on the P¿iff, Herden [23] and Leonhardt [13] suggested combustion phase detection methods which are the location of 50% difference pressure integral (DPI50) and the center of gravity (COG) of the P¿iff for combustion phase detection, respectively. However, these methods demand a wide range of pressure data.…”

Section: Difference Pressure Analysismentioning

confidence: 99%

Real-Time Combustion Phase Detection Using Central Normalized Difference Pressure in CRDI Diesel Engines

Lim

Chung

et al. 2012

Journal of Engineering for Gas Turbines and Power

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To develop eco-friendly diesel engines, accurate combustion phase control is important due to its significant effects on harmful emissions and fuel efficiency. In order to accurately control the combustion phase, the detection of the combustion phase should precede control system design. Currently, combustion phase detection is done by the location of 50% mass fraction burned (MFB50), because of its close correlation with emissions and fuel efficiency. However, this method is not easily implemented in realtime applications because the calculation of MFB50 requires a large amount of in-cylinder pressure data and an excessive computational load. For this reason, a combustion phase indicator with a simple algorithm is required for real-time combustion control. In this study, we propose a new combustion phase indicator, called the "Central normalized difference pressures (CNDP)." The CNDP indicates the center of the two crank angles where the normalized difference pressure between firing pressure and motoring pressure (NDP) reaches 90% of the maximum value before peak (NDPi,p90), and 70% of the maximum value after peak (NDPap70). The NDPhp90 and NDPap70 are highly correlated with MFB50 and the correlation is enhanced as the center between the two points obtained. The CNDP is represented by a fixed quadratic polynomial with MFB50 that robust to changes in various engine operating conditions such as engine speed, main injection timing, injected fuel quantity, fuel-rail pressure, exhaust gas recirculation (EGR) rate and boost pressure. Furthermore, in performance evaluation, the CNDP requires remarkably fewer in-cylinder pressure data samples, calculation steps and less computation time compared to MFB50. These results show great potential for the CNDP to be a substitute for the MFB50 since the proposed combustion phase detection algorithm can be used effectively for real-time combustion phase detection and control.

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“…Further, u is the specific internal energy, m c is the mass of charge entrapped inside the cylinder and h is the crank angle. Further, dQ ht /dh is the heat transfer by convection to the cylinder walls and as the total heat transfer is divided into portions for each zone; it can be expressed as (8).…”

Section: Two-zone Heat Release Modelmentioning

confidence: 99%

“…Some of these variables like location of peak pressure (LPP), peak pressure (PP), maximum rate of pressure rise and its location are used for control of spark advance, air-fuel ratio and NO x emission [1][2][3][4][5][6], etc. Monitoring of cylinder pressure is possible through various intrusive and nonintrusive sensors [7][8][9] but cost of these sensors limits their use in the engines of on-road vehicles. Further, poor durability of these sensors and space requirement in vehicle to install associated equipments also limit their use.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction of cylinder pressure for SI engine using recurrent neural network

Saraswati

Chand

2010

Neural Comput & Applic

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Cylinder pressure based engine control systems use variables deduced from cylinder pressure as a feedback input. Monitoring of cylinder pressure is possible through various intrusive and nonintrusive sensors but cost of these sensors limits their use in the engines of on-road vehicles. In the present work, a recurrent neural network (RNN) is proposed which can reconstruct cylinder pressure of spark ignition engine. The network uses instantaneous crankshaft speed and motored pressure as inputs. Initially, parameters of two-zone model are tuned at limited number of experimental points, so that cylinder pressure predicted by model matches to that of experimental results. Further, the tuned model is used to generate large number of training data. Validation has been carried out using experimental as well as simulated pressure trace. It has been found that RNN can reconstruct cylinder pressure with reasonably good accuracy.

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A New Combustion Pressure Sensor for Advanced Engine Management

Cited by 33 publications

References 2 publications

Introduction to Modeling and Control of Internal Combustion Engine Systems

Introduction to Modeling and Control of Internal Combustion Engine Systems

Real-Time Combustion Phase Detection Using Central Normalized Difference Pressure in CRDI Diesel Engines

Reconstruction of cylinder pressure for SI engine using recurrent neural network

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