Observer Based Cylinder Charge Estimation for Spark-ignition Engines

Internal combustion engines require accurate cylinder charge estimation for determining engine torque, controlling air-to-fuel ratio (AFR), and ensuring high after-treatment efficiency. This is challenging due to the highly transient operating conditions that are common in automobile engines. The problem is further complicated by spark ignition (SI) engine technologies such as variable valve timing (VVT) and exhaust gas recirculation (EGR) which are applied to improve fuel economy and reduce pollutant emissions. With manifold filling/emptying/mixing phenomenon and different actuator response times, these technologies significantly increase the complexity of cylinder charge estimation. Current cylinder charge estimation methodologies require a combination of sensors and empirical models to deal with the high degrees of control freedom existent on the engine. But these methods have the drawbacks of great dependency on accurate calibration and poor transient performance. Most importantly, the current methods isolate feed-forward cylinder charge estimation and feedback AFR control. When there is discrepancy between target lambda value and sensed lambda value at exhaust side, the current control/estimation method will trim the fuel injection amount no matter where the error source is. As a matter of fact, the error might come from the throttle flow estimation, the fuel injection flow estimation, EGR flow estimation, or any combination of these error sources. Increased air-path complexity and drawbacks of traditional methods drive the need for cost effective solutions that produce high air/EGR/fuel charge estimation accuracy with the ability to identify the error source while minimizing sensor cost, computational effort, and calibration time. This research first evaluates the existing work on air charge estimation for SI engines with massive experimental tests covering various operating conditions, which are designed for the algorithm verification of this research. Then several estimation methods which utilize both Manifold Absolute Pressure (MAP) and Mass Air Flow (MAF) sensors are studied and analyzed. Reduction of calibration effort and improvement of accuracy are observed from the proposed cylinder air charge estimation methods. Following that, a model is built to study the engine gas path dynamics and characteristics and then simplified to provide system dynamic basis for the following estimation algorithm development. Using the developed model, a disturbance observer based cylinder charge estimation technique is developed based on a combination of sensors including MAF, MAP, and exhaust lambda sensors. This developed algorithm significantly improves engine states estimation accuracy compared to conventional Single-Input-Single-Output (SISO) methods. Also, the augmentation of disturbance observation is able to pin point the source of the estimation error. Through experimental validation, using the developed estimation method with proper parameters, the error source of estimation can be identified and rectified when disturbance is introduced to throttle flow model, EGR flow model, fuel injection flow model or any combination of these models. The structure of the proposed algorithm should adapt to most SI engine configurations. It can help the engine controller to mitigate modeling errors thus improve the performance of physics model based engine control especially AFR control

In-cylinder pressure resonance analysis for trapped mass estimation in automotive engines

This thesis presents a new application for in-cylinder pressure sensors in internal combustion engines. The new method takes profit of the high-frequency content of the in-cylinder pressure signal to determine the speed of sound evolution during the expansion stroke and combines this estimation with the low-frequency content of the pressure signal and a volume estimation to obtain a measurement of the trapped mass. The new method is based on the studies of the resonance phenomenon in pent-roof combustion chambers and proposes three calibration procedures to determine the resonant frequency evolution when bowl-in-piston geometries are considered. The Fourier transform has been modified in order to include harmonics with frequency variations, which allows a rapid identification of the resonant modes with no need of time-frequency analysis, e.g. STFT or WD. The main limitation of the method resides in the resonance excitation, which may be insufficient in low-load conditions, such as idle. An observer is presented to overcome that problem. The observer takes into account the dynamics of the sensors, the dynamics at the intake manifold, and combines current flow sensors with intermittent measurements, such as the trapped mass obtained by the resonance method, to provide the system with accurate and robust measurements of the trapped mass, the EGR, and the composition at the exhaust. The trapped mass obtained by the resonance method has been compared with auxiliary methods in various experimental facilities: in a SI engine, where no EGR exist, the differences founded were below 1%, in a conventional CI light-duty engine the average of the differences over 808 operating conditions accounted for a 2.64 %, in a research heavy-duty RCCI engine, with EGR, port fuel gasoline, and direct diesel injections, the average difference was 2.17 %, and in a research two-strokes single cylinder engine, where significant short-circuit and residual gases exist, the differences founded were 4.36 %. In all the studied cases the differences founded with the reference estimation can be attributed to the auxiliary method employed and its expected error. In order to demonstrate the potential of the resonance method four applications for control and diagnosis of internal combustion engines have been proposed: the estimation of residuals in engines with NVO, the prediction of knock in SI engines, the estimation of the exhaust gases temperature, and a NOx model for CI engines. In the four applications the method was compared with current methodologies and with additional sensors, demonstrating the improvement in accuracy and a cycle-to-cycle resolution.Esta tesis presenta una nueva aplicación para los sensores de presión en cámara. El nuevo método utiliza el contenido de alta frecuencia de la señal de presión en cámara para estimar la evolución de la velocidad del sonido durante la expansión de los gases de escape y combina esta estimación con el contenido de baja frecuencia de la presión en cámara y el volumen instantáneo de la cámara para obtener una medida de la masa atrapada. El nuevo método está basado en los estudios de la resonancia en cámaras de combustión cilíndricas y propone tres procedimientos de calibración para estimar la evolución de la frecuencia de resonancia en cámaras de combustión con bowl. La transformada de Fourier ha sido modificada para considerar harmónicos con frecuencias que varían en el tiempo, lo que permite una rápida identificación de los modos de resonancia sin necesidad de utilizar un análisis en tiempo frecuencia, como por ejemplo STFT o WD. La principal limitación del método es la necesidad de excitación suficiente de la resonancia, que puede impedir su uso en condiciones de baja carga como el ralentí. Para solventar este problema se ha diseñado un observador. El observador incluye las dinámicas de los sensores, las dinámicas del colector de admisión, y combina los sensores actuales de flujo con medidas intermitentes (como la medida ofrecida por el nuevo método de la resonancia) para obtener medidas de la masa atrapada, del EGR y de la composición en el escape precisas y robustas. La medida de la masa atrapada obtenida por el método de la resonancia ha sido comparado con métodos auxiliares en diferentes instalaciones experimentales: en un motor SI, sin EGR, las diferencias con los sensores eran menores del 1%, en un motor convencional CI la media de las diferencias sobre 808 puntos de operación distintos ha sido de 2.64 %, en un motor de investigación con EGR, con inyección gasolina en el colector e inyección directa de diesel, las diferencias fueron de 2.17 %, y en un motor de investigación de dos tiempos, donde existían grandes cantidades de corto-circuito y gases residuales, las diferencias fueron de 4.36 %. En todos los casos estudiados las diferencias encontradas pueden ser atribuidas a los errores que caracterizan los métodos auxiliares utilizados para obtener la medida de referencia. Finalmente, para demostrar el potencial del método se han desarrollado cuatro aplicaciones para control y diagnóstico de motores de combustión interna alternativos: la estimación de gases residuales en motores con NVO, la predicción de knock en motores SI, la estimación de la temperatura de los gases de escape, y un modelo de NOx para motores CI. En las cuatro aplicaciones el método ha sido comparado con los sistemas de medidas actuales y con sensores adicionales, demostrando mejoras importantes en la precisión de la medida y una resolución de un solo ciclo.Aquesta tesi presenta una nova aplicació per als sensors de pressió en cambra. El nou mètode utilitza el contingut d'alta freqüència del senyal de pressió en cambra per estimar l'evolució de la velocitat del so durant l'expansió dels gasos d'eixida i combina aquesta estimació amb el contingut de baixa freqüència de la pressió en cambra i el volum instantani de la cambra per obtenir una mesura de la massa atrapada. El nou mètode està desenvolupat dels estudis de la ressonància en cambres de combustió cilíndriques i proposa tres procediments de calibratge per estimar l'evolució de la freqüència de ressonància en cambres de combustió amb bowl. La transformada de Fourier ha sigut modificada per considerar harmònics amb freqüències que varien en el temps, el que permet una ràpida identificació dels modes de ressonància sense necessitat d'utilitzar una anàlisi en temps-freqüència, com per exemple la STFT o la WD. La principal limitació del mètode és la necessitat d'excitació suficient de la ressonància, que pot impedir el seu ús en condicions de baixa càrrega, com al ralentí. Per solucionar aquest problema s'ha desenvolupat un observador. L'observador inclou les dinàmiques dels sensors, les dinàmiques del col·lector d'admissió, i combina els sensors actuals de flux amb mesures intermitents (com l'obtinguda pel nou mètode de la ressonància) per obtenir mesures de la massa atrapada, del EGR i de la composició d'eixida precises i robustes. La mesura de la massa atrapada obtinguda pel mètode de la ressonància ha sigut comparada en mètodes auxiliars en diferents instal·lacions experimentals: a un motor SI, sense EGR, les diferencies amb els sensors estaven per davall de l'1 %, a un motor convencional CI la mitja de les diferències sobre 808 punts d'operació diferents ha sigut de 2.64 %, a un motor d'investigació, en EGR, en injecció gasolina en el col·lector i injecció directa de dièsel, les diferències van ser de 2.17 %, i a un motor d'investigació de dos temps, on existien grans quantitats de curtcircuit i residuals, les diferencies foren de 4.36 %. En tots els casos estudiats les diferències trobades poden ser atribuïdes als errors que caracteritzen els mètodes auxiliars utilitzats per obtenir la mesura de referència. Finalment, per demostrar el potencial del mètode s'han desenvolupat quatre aplicacions per al control i diagnòstic de motors de combustió interna alternatius: l'estimació de gasos residuals en motors amb NVO, la predicció de knock en motors SI, l'estimació de la temperatura dels gasos d'eixida, i un model de NOx per a motors CI. En les quatre aplicacions el mètode ha sigut comparat amb els sistemes de mesures actuals i amb sensors addicionals, demostrant millores importants en la precisió de la mesura i una resolució de solament un cicle.Bares Moreno, P. (2017). In-cylinder pressure resonance analysis for trapped mass estimation in automotive engines [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/9042

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

Observer-based engine air charge characterisation: rapid, observer-assisted engine air charge characterisation using a dynamic dual-ramp testing method

Characterisation of modern complex powertrains is a time consuming and expensive process. Little effort has been made to improve the efficiency of testing methodologies used to obtain data for this purpose. Steady-state engine testing is still regarded as the golden standard, where approximately 90% of testing time is wasted waiting for the engine to stabilize. Rapid dynamic engine testing, as a replacement for the conventional steady-state method, has the potential to significantly reduce the time required for characterisation. However, even by using state of the art measurement equipment, dynamic engine testing introduces the problem that certain variables are not directly measurable due to the excitation of the system dynamics. Consequently, it is necessary to develop methods that allow the observation of not directly measurable quantities during transient engine testing. Engine testing for the characterisation of the engine air-path is specifically affected by this problem since the air mass flow entering the cylinder is not directly measurable by any sensor during transient operation. This dissertation presents a comprehensive methodology for engine air charge characterisation using dynamic test data. An observer is developed, which allows observation of the actual air mass flow into the engine during transient operation. The observer is integrated into a dual-ramp testing procedure, which allows the elimination of unaccounted dynamic effects by averaging over the resulting hysteresis. A simulation study on a 1-D gas dynamic engine model investigates the accuracy of the developed methodology. The simulation results show a trade-off between time saving and accuracy. Experimental test result confirm a time saving of 95% compared to conventional steady-state testing and at least 65% compared to quasi steady-state testing while maintaining the accuracy and repeatability of conventional steady-state testing

A STUDY OF MODEL-BASED CONTROL STRATEGY FOR A GASOLINE TURBOCHARGED DIRECT INJECTION SPARK IGNITED ENGINE

To meet increasingly stringent fuel economy and emissions legislation, more advanced technologies have been added to spark-ignition (SI) engines, thus exponentially increase the complexity and calibration work of traditional map-based engine control. To achieve better engine performance without introducing significant calibration efforts and make the developed control system easily adapt to future engines upgrades and designs, this research proposes a model-based optimal control system for cycle-by-cycle Gasoline Turbocharged Direct Injection (GTDI) SI engine control, which aims to deliver the requested torque output and operate the engine to achieve the best achievable fuel economy and minimum emission under wide range of engine operating conditions. This research develops a model-based ignition timing prediction strategy for combustion phasing (crank angle of fifty percent of the fuel burned, CA50) control. A control-oriented combustion model is developed to predict burn duration from ignition timing to CA50. Using the predicted burn duration, the ignition timing needed for the upcoming cycle to track optimal target CA50 is calculated by a dynamic ignition timing prediction algorithm. A Recursive-Least-Square (RLS) with Variable Forgetting Factor (VFF) based adaptation algorithm is proposed to handle operating-point-dependent model errors caused by inherent errors resulting from modeling assumptions and limited calibration points, which helps to ensure the proper performance of model-based ignition timing prediction strategy throughout the entire engine lifetime. Using the adaptive combustion model, an Adaptive Extended Kalman Filter (AEKF) based CA50 observer is developed to provide filtered CA50 estimation from cyclic variations for the closed-loop combustion phasing control. An economic nonlinear model predictive controller (E-NMPC) based GTDI SI engine control system is developed to simultaneously achieve three objectives: tracking the requested net indicated mean effective pressure (IMEPn), minimizing the SFC, and reducing NOx emissions. The developed E-NMPC engine control system can achieve the above objectives by controlling throttle position, IVC timing, CA50, exhaust valve opening (EVO) timing, and wastegate position at the same time without violating engine operating constraints. A control-oriented engine model is developed and integrated into the E-NMPC to predict future engine behaviors. A high-fidelity 1-D GT-POWER engine model is developed and used as the plant model to tune and validate the developed control system. The performance of the entire model-based engine control system is examined through the software-in-the-loop (SIL) simulation using on-road vehicle test data

Review of air fuel ratio prediction and control methods

Air pollution is one of main challenging issues nowadays that researchers have been trying to address.The emissions of vehicle engine exhausts are responsible for 50 percent of air pollution. Different types of emissions emit from vehicles including carbon monoxide, hydrocarbons, NOX, and so on. There is a tendency to develop strategies of engine control which work in a fast way. Accomplishing this task will result in a decrease in emissions which coupled with the fuel composition can bring about the best performance of the vehicle engine.Controlling the Air-Fuel Ratio (AFR) is necessary, because the AFR has an enormous impact on the effectiveness of the fuel and reduction of emissions.This paper is aimed at reviewing the recent studies on the prediction and control of the AFR, as a bulk of research works with different approaches, was conducted in this area.These approaches include both classical and modern methods, namely Artificial Neural Networks (ANN), Fuzzy Logic, and Neuro-Fuzzy Systems are described in this paper.The strength and the weakness of individual approaches will be discussed at length

Diagnostics Methods and Their Application in Automotive Engine

Import 15/01/2013Gasoline engine is a complex power generating machines and used widely in automotive industry, which the failure rate is high. Carrying out the gasoline engine fault diagnostic methods have been studied and still a lasting topic for scientists. Crankshaft instantaneous angular acceleration contains information for fault diagnostic. It can directly reflect the state of applying work and current pressure in each cylinder. By means of analyzing the angular acceleration signal, the instantaneous engine running state and a lot of related faults can be discovered. Under the normal working conditions, the motive force performance of each cylinder is unanimous basically, the gasoline engine operates steadily. Its angular acceleration always fluctuates in a normal range and presents certain regularity. The operation when a certain cylinder is working abnormally, the consistency of motive force is destroyed, the engine becomes bad to the stationary of operation, and the angular acceleration signal will be out of shape. By observing its fluctuation, the working process in each cylinder can be evaluated. In this thesis, the instantaneous angular acceleration is evaluated by phase modulation method using the Hilbert Transform technique. To verify the signal analysis technique, the engine model created originally by Weeks, RW & Moskwa, J.J. is extended by modeling of the non-uniform driving torque in contrast to the original model assuming uniform driving torque to produce fluctuation of the crankshaft angular acceleration. Many subsystems of the engine are also modeled by the simulation program Matlab/Simulink. Torque of engine at some spark advances was simulated to compare and found out the best angle to obtain the maximum brake torque, as well.Zážehový motor je široce používán v dopravních prostředcích. Jako u každého stroje, i u zážehového motoru mohou vznikat poruchy, které je třeba diagnostikovat. Provedení benzínového motoru a metody diagnosticky poruch byly studovány a jsou stále tématem pro výzkum. Okamžité úhlové zrychlení klikového hřídele poskytuje diagnostické informace o poruchách spalovacího procesu. To se může přímo odrážet na výkonu motoru daném aktuálním spalovacím tlakem v každém válci. Prostřednictvím analýzy signálu úhlového zrychlení, ve stavu kdy motor běží, může být objevena spousta chyb. Za normálních pracovních podmínek jsou hnací síly každého válce v podstatě shodné, zážehový motor pracuje v ustáleném režimu. Jeho úhlové zrychlení vždy kolísá v normálním rozsahu a představuje určitou pravidelnost. Když za provozu některý válec pracuje nepravidelně, je narušen časový průběh krouticího momentu, motor se stane nestabilní ve stacionárním provozu a úhlové zrychlení signálu bude vykazovat odchylky. Tím, že sledujeme kolísání okamžitého úhlového zrychlení, může být vyhodnocen spalovací a kompresní proces individuálně v každém válci zvlášť. V této práci, je hodnoceno okamžité úhlové zrychlení klikového hřídele metodou fázové modulace. Nástrojem k demodulaci je analytický signál, jehož imaginární část je vypočtena pomocí Hilbertovy transformace. Chceme-li ověřit metodu zpracování impulsního signálu pro ECU, použijeme simulační model motoru. První dynamický model vytvořili Week, R.W. a Moskwa, J.J.. Tento model průběžně počítal krouticí moment jako konstantu pro všechny fáze práce motoru. K testování výpočtu okamžitého úhlového zrychlení klikového hřídele bylo třeba modelovat vznik nerovnoměrnosti krouticího momentu při hoření paliva ve válci a kompresi směsi, jako příčiny periodického zrychlování a zpomalování při otáčení kliky na požadovaných otáčkách. Model motoru je rozdělen na subsystémy, které jsou modelovány simulačním programem Matlab / Simulink. Krouticí moment motoru při některých zapalovacích postupech byl pro porovnání simulován a byl hledán nejlepší úhel předstihu zapalování pro dosažení maximálního hnacího momentu.Prezenční352 - Katedra automatizační techniky a řízenívyhově

Low-Pressure EGR in Spark-Ignition Engines: Combustion Effects, System Optimization, Transients & Estimation Algorithms

Low-displacement turbocharged spark-ignition engines have become the dominant choice of auto makers in the effort to meet the increasingly stringent emission regulations and fuel efficiency targets. Low-Pressure cooled Exhaust Gas Recirculation introduces important efficiency benefits and complements the shortcomings of highly boosted engines. The main drawback of these configurations is the long air-path which may cause over-dilution limitations during transient operation. The pulsating exhaust environment and the low available pressure differential to drive the recirculation impose additional challenges with respect to feed-forward EGR estimation accuracy. For these reasons, these systems are currently implemented through calibration with less-than-optimum EGR dilution in order to ensure stable operation under all conditions. However, this technique introduces efficiency penalties. Aiming to exploit the full potential of this technology, the goal is to address these challenges and allow operation with near-optimum EGR dilution. This study is focused on three major areas regarding the implementation of Low-Pressure EGR systems: Combustion effects, benefits and constraints System optimization and transient operation Estimation and adaptation Results from system optimization show that fuel efficiency benefits range from 2% – 3% over drive cycles through pumping and heat loss reduction, and up to 16% or more at higher loads through knock mitigation and fuel enrichment elimination. Soot emissions are also significantly reduced with cooled EGR. Regarding the transient challenges, a methodology that correlates experimental data with simulation results is developed to identify over-dilution limitations related to the engine’s dilution tolerance. Different strategies are proposed to mitigate these issues, including a Neural Network-actuated VVT that controls the internal residual and increases the over-dilution tolerance by 3% of absolute EGR. Physics-based estimation algorithms are also developed, including an exhaust pressure/temperature model which is validated through real-time transient experiments and eliminates the need for exhaust sensors. Furthermore, the installation of an intake oxygen sensor is investigated and an adaptation algorithm based on an Extended Kalman Filter is created. This algorithm delivers short-term and long-term corrections to feed-forward EGR models achieving a final estimation error of less than 1%. The combination of the proposed methodologies, strategies and algorithms allows the implementation of near-optimum EGR dilution and translates to fuel efficiency benefits ranging from 1% at low-load up to 10% at high-load operation over the current state-of-the-art