Flexible and robust control of heavy duty diesel engine airpath using data driven disturbance observers and GPR models

Diesel engine airpath control is crucial for modern engine development due to increasingly stringent emission regulations. This thesis aims to develop and validate a exible and robust control approach to this problem for speci cally heavy-duty engines. It focuses on estimation and control algorithms that are implementable to the current and next generation commercial electronic control units (ECU). To this end, targeting the control units in service, a data driven disturbance observer (DOB) is developed and applied for mass air ow (MAF) and manifold absolute pressure (MAP) tracking control via exhaust gas recirculation (EGR) valve and variable geometry turbine (VGT) vane. Its performance bene ts are demonstrated on the physical engine model for concept evaluation. The proposed DOB integrated with a discrete-time sliding mode controller is applied to the serial level engine control unit. Real engine performance is validated with the legal emission test cycle (WHTC - World Harmonized Transient Cycle) for heavy-duty engines and comparison with a commercially available controller is performed, and far better tracking results are obtained. Further studies are conducted in order to utilize capabilities of the next generation control units. Gaussian process regression (GPR) models are popular in automotive industry especially for emissions modeling but have not found widespread applications in airpath control yet. This thesis presents a GPR modeling of diesel engine airpath components as well as controller designs and their applications based on the developed models. Proposed GPR based feedforward and feedback controllers are validated with available physical engine models and the results have been very promisin

Integration of intermittent measurement from in-cylinder pressure resonance in a multi-sensor mass flow estimator

[EN] A novel technique of trapped mass determination, based on the in-cylinder pressure resonance, has been recently published by the authors. However, the method only works when sufficient resonance intensity exists and the current formulation might preclude its implementation in real-time due to excessive computational burden. The present paper proposes an iterative algorithm for reducing the number of operations, an adaptive filter to identify faulty measurements and a Kalman filter that combines several sensors and models, currently used in commercial light-duty engines, to ensure a continous estimation of trapped mass, air mass, and exhaust gas recirculation (EGR). The filter is implemented using experimental data of a EURO 6 light-duty engine in a world harmonize light-duty test cycle (WLTC), showing the potential of being implemented in real driving conditions with robustness and harnessing a new measurement to improve the accuracy and response of current estimations.Guardiola, C.; Pla Moreno, B.; Bares-Moreno, P.; Peyton Jones, J. (2019). Integration of intermittent measurement from in-cylinder pressure resonance in a multi-sensor mass flow estimator. Mechanical Systems and Signal Processing. 131:152-165. https://doi.org/10.1016/j.ymssp.2019.05.052S15216513

In-cylinder pressure based model for exhaust temperature estimation in internal combustion engines

[EN] Exhaust temperature is a valuable parameter for engine control. However, measurement conditions at the engine exhaust and the slow dynamic response of temperature sensors difficult the determination of the instantaneous exhaust temperature. The present paper proposes a methodology for estimating the exhaust temperature exclusively relying in-cylinder pressure signal, engine speed and exhaust lambda.The presented methodology can replace or actualize widespread look-up table models for correcting calibration offsets, due to ageing, sensor bias or disturbances associated with the engine operation. The method uses the existence of resonant modes in the in-cylinder pressure for inferring the trapped mass and the in-cylinder temperature. An isentropic expansion of the gasses through the valves is assumed for estimating the cylinder outlet temperature of the gases, and the gas temperature drop along the exhaust runner and manifold is modelled through a nodal thermal model. The method was compared with current models under steady and transient conditions in a four stroke CI engine. Variations of injection, EGR, intake pressure and rail pressure were performed under steady operation and the transient response of the method was validated under specific transient test and at the WLTP cycle. A time invariant first order model was used for comparing the estimated temperature with that provided by the experimental sensors. (C) 2016 Elsevier Ltd. All rights reserved.This research has been partially financed by the Spanish Ministerio de Economia Competitividad, through project TRA2013-40853-R "Desarrollo de nuevas tecnicas de limitation de la perdida de presion en DPFs para reducir las emisiones y el consumo de los motores diesel (PRELIMIT)".Guardiola, C.; Olmeda, P.; Plá Moreno, B.; Bares-Moreno, P. (2017). In-cylinder pressure based model for exhaust temperature estimation in internal combustion engines. Applied Thermal Engineering. 115:212-220. https://doi.org/10.1016/j.applthermaleng.2016.12.092S21222011

Knock probability estimation through an in-cylinder temperature model with exogenous noise

[EN] This paper presents a new knock model which combines a deterministic knock model based on the in-cylinder temperature and an exogenous noise disturbing this temperature. The autoignition of the end-gas is modelled by an Arrhenius-like function and the knock probability is estimated by propagating a virtual error probability distribution. Results show that the random nature of knock can be explained by uncertainties at the in cylinder temperature estimation. The model only has one parameter for calibration and thus can be easily adapted online. In order to reduce the measurement uncertainties associated with the air mass flow sensor, the trapped mass is derived from the in-cylinder pressure resonance, which improves the knock probability estimation and reduces the number of sensors needed for the model. A four stroke SI engine was used for model validation. By varying the intake temperature, the engine speed, the injected fuel mass, and the spark advance, specific tests were conducted, which furnished data with various knock intensities and probabilities. The new model is able to predict the knock probability within a sufficient range at various operating conditions. The trapped mass obtained by the acoustical model was compared in steady conditions by using a fuel balance and a lambda sensor and differences below 1% were found. (C) 2017 Elsevier Ltd. All rights reserved.Bares-Moreno, P.; Selmanaj, D.; Guardiola, C.; Onder, C. (2018). Knock probability estimation through an in-cylinder temperature model with exogenous noise. Mechanical Systems and Signal Processing. 98:756-769. https://doi.org/10.1016/j.ymssp.2017.05.033S7567699

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

Online adaptive fuzzy neural network automotive engine control

Automotive manufacturers are investing in research and development for hybridization and more modern advanced combustion strategies. These new powertrain systems can offer the higher efficiency required to meet future emission legislation, but come at the cost of significantly increased complexity. The addition of new systems to modernise an engine increases the degrees of freedom of the control problem and the number of control variables. Advanced combustion strategies also display interlinked behaviour between control variables. This type of behaviour requires a more orchestrated multi-input multi-output control approach. Model based control is a common solution, but accurate control models can be difficult to achieve and calibrate due to the nonlinear dynamics of the engines. The modelling problem becomes worse when some advanced combustion systems display nonlinear dynamics that can change with time. Any fixed model control system would suffer from increasing model/system mismatch. Direct feedback would help reduce a degree or error from model/system mismatch, but feedback methods are often limited by cost and are generally indirect and slow response. This research addresses these problems with the development of a mobile ionisation sensor and an online adaptive control architecture for multi-input multi-output engine control. The mobile ionisation system offers a cheap, fast response, direct in-cylinder feedback for combustion control. Feedback from 30 averaged cycles can be related to combustion timing with variance as small as 0.275 crank angle degrees. The control architecture combines neural networks and fuzzy logic for the control and reduced modelling effort for complex nonlinear systems. The combined control architecture allows continuous online control adaption for calibration against model/plant mismatch and time varying dynamics. In simulation, set point tracking could be maintained for combustion timing to 4 CAD and AFR to 4, for significant dynamics shifts in plant dynamics during a transient drive cycle.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Observability studies of a turbocharger systems

The use of diesel engine turbochargers is increasing today, as it represents an option that o ers high e ciency and low fuel consumption. To design the control system in order to reduce the level of exhaust emissions there is a need for information about all states that are not measurable. To this end, observers or virtual sensors are more frequently applied, achieving estimates of the system states from inputs and measured output. To propose an observer, the precise mathematical model of the air path diesel engine system is used. This is a nonlinear model of a third order which is analyzed in terms of observability. From the point of view of systems theory, certain conditions and the existence of a transformation of the system state, called di eomorphism, need to be evaluated. Observers have been designed based on di erent approaches: Extended Luenberger Observers, High Gain Observers, Sliding Modes Observers and Extended Kalman-Bucy Filters. They have been validated by simulation for the system under consideration in this work.Tesi

Putting reaction-diffusion systems into port-Hamiltonian framework

Reaction-diffusion systems model the evolution of the constituents distributed in space under the influence of chemical reactions and diffusion [6], [10]. These systems arise naturally in chemistry [5], but can also be used to model dynamical processes beyond the realm of chemistry such as biology, ecology, geology, and physics. In this paper, by adopting the viewpoint of port-controlled Hamiltonian systems [7] we cast reaction-diffusion systems into the portHamiltonian framework. Aside from offering conceptually a clear geometric interpretation formalized by a Stokes-Dirac structure [8], a port-Hamiltonian perspective allows to treat these dissipative systems as interconnected and thus makes their analysis, both quantitative and qualitative, more accessible from a modern dynamical systems and control theory point of view. This modeling approach permits us to draw immediately some conclusions regarding passivity and stability of reaction-diffusion systems. It is well-known that adding diffusion to the reaction system can generate behaviors absent in the ode case. This primarily pertains to the problem of diffusion-driven instability which constitutes the basis of Turing’s mechanism for pattern formation [11], [5]. Here the treatment of reaction-diffusion systems as dissipative distributed portHamiltonian systems could prove to be instrumental in supply of the results on absorbing sets, the existence of the maximal attractor and stability analysis. Furthermore, by adopting a discrete differential geometrybased approach [9] and discretizing the reaction-diffusion system in port-Hamiltonian form, apart from preserving a geometric structure, a compartmental model analogous to the standard one [1], [2] is obtaine

An LPV Adaptive Observer for Updating a Map Applied to an MAF Sensor in a Diesel Engine

In this paper, a new method for mass air flow (MAF) sensor error compensation and an online updating error map (or lookup table) due to installation and aging in a diesel engine is developed. Since the MAF sensor error is dependent on the engine operating point, the error model is represented as a two-dimensional (2D) map with two inputs, fuel mass injection quantity and engine speed. Meanwhile, the 2D map representing the MAF sensor error is described as a piecewise bilinear interpolation model, which can be written as a dot product between the regression vector and parameter vector using a membership function. With the combination of the 2D map regression model and the diesel engine air path system, an LPV adaptive observer with low computational load is designed to estimate states and parameters jointly. The convergence of the proposed algorithm is proven under the conditions of persistent excitation and given inequalities. The observer is validated against the simulation data from engine software enDYNA provided by Tesis. The results demonstrate that the operating point-dependent error of the MAF sensor can be approximated acceptably by the 2D map from the proposed method