On-Line Optimization of Dual-Fuel Combustion Operation by Extremum Seeking Techniques

[EN] Dual-fuel combustion engines have shown the potential to extend the operating range of Homogeneous Charge Compression Ignition (HCCI) by using several combustion modes, e.g. Reactivity Controlled Compression Ignition (RCCI) at low/medium load, and Partially Premixed Compression (PPC) at high load. In order to optimize the combustion mode operation, the respective sensitivity to the control inputs must be addressed. To this end, in this work the extremum seeking algorithm has been investigated. By definition, this technique allows to detect the control input authority over the system by perturbing its value by a known periodic signal. By analyzing the system response and calculating its gradient, the control input can be adjusted to reach optimal operation. This method has been applied to a dual-fuel engine under fully, highly and partially premixed conditions where the feedback information was provided by in-cylinder pressure and NOx sensors. The gasoline fraction and the injection timing were selected as control inputs and an extremum seeking controller was designed and verified to optimize brake efficiency by tracking the ideal combustion phasing and to reduce NOx emissions as well.The authors would like to recognize the financial support through Alvin Barbier's grant ACIF/2018/141, Programa Operativo del Fondo Social Europeo (FSE) de la Comunitat Valenciana 2014-2020. The authors also wish to thank Gabriel Alcantarilla for his assistance during the experimental campaign.Pla Moreno, B.; Bares-Moreno, P.; Barbier, ARS.; Guardiola, C. (2021). On-Line Optimization of Dual-Fuel Combustion Operation by Extremum Seeking Techniques. SAE International. 1-10. https://doi.org/10.4271/2021-01-051911

Model-Guided Data-Driven Optimization and Control for Internal Combustion Engine Systems

The incorporation of electronic components into modern Internal Combustion, IC, engine systems have facilitated the reduction of fuel consumption and emission from IC engine operations. As more mechanical functions are being replaced by electric or electronic devices, the IC engine systems are becoming more complex in structure. Sophisticated control strategies are called in to help the engine systems meet the drivability demands and to comply with the emission regulations. Different model-based or data-driven algorithms have been applied to the optimization and control of IC engine systems. For the conventional model-based algorithms, the accuracy of the applied system models has a crucial impact on the quality of the feedback system performance. With computable analytic solutions and a good estimation of the real physical processes, the model-based control embedded systems are able to achieve good transient performances. However, the analytic solutions of some nonlinear models are difficult to obtain. Even if the solutions are available, because of the presence of unavoidable modeling uncertainties, the model-based controllers are designed conservatively

In-Cylinder Pressure-Based Control of Premixed Dual-Fuel Combustion

[ES] La actual crisis climática ha instado a la comunidad investigadora y a los fabricantes a brindar soluciones para hacer que el sector del transporte sea más sostenible. De entre las diversas tecnologías propuestas, la combustión a baja temperatura ha sido objeto de una extensa investigación. La combustión premezclada dual-fuel es uno de los conceptos que abordan el compromiso de NOx-hollín en motores de encendido por compresión manteniendo alta eficiencia térmica. Esta combustión hace uso de dos combustibles con diferentes reactividades para mejorar la controlabilidad de este modo de combustión en un amplio rango de funcionamiento. De manera similar a todos los modos de combustión premezclados, esta combustión es sensible a las condiciones de operación y suele estar sujeta a variabilidad cíclica con gradientes de presión significativos. En consecuencia, se requieren estrategias de control avanzadas para garantizar un funcionamiento seguro y preciso del motor. El control en bucle cerrado es una herramienta eficaz para abordar los desafíos que plantea la combustión premezclada dual-fuel. En este tipo de control, para mantener el funcionamiento deseado, las acciones de control se adaptan y corrigen a partir de una retroalimentación con las señales de salida del motor. Esta tesis presenta estrategias de control basadas en la medición de la señal de presión en el cilindro, aplicadas a motores de combustión premezclada dual-fuel. En ella se resuelven diversos aspectos del funcionamiento del motor mediante el diseño de controladores dedicados, haciéndose especial énfasis en analizar e implementar estas soluciones a los diferentes niveles de estratificación de mezcla considerados en estos motores (es decir, totalmente, altamente y parcialmente premezclada). Inicialmente, se diseñan estrategias de control basadas en el procesamiento de la señal de presión en el cilindro y se seleccionan acciones proporcionales-integrales para asegurar el rendimiento deseado del motor sin exceder las limitaciones mecánicas del motor. También se evalúa la técnica extremum seeking para realizar una supervisión de una combustión eficiente y la reducción de emisiones de NOx. Luego se analiza la resonancia de la presión en el cilindro y se implementa un controlador similar a aquel usado para el control de knock para garantizar el funcionamiento seguro del motor. Finalmente, se utilizan modelos matemáticos para diseñar un modelo orientado a control y un observador que tiene como objetivo combinar las señales medidas en el motor para mejorar las capacidades de predicción y diagnóstico en dicha configuración de motor. Los resultados de este trabajo destacan la importancia de considerar el control en bucle cerrado para abordar las limitaciones encontradas en los modos de combustión premezclada. En particular, el uso de la medición de presión en el cilindro muestra la relevancia y el potencial de esta señal para desarrollar estrategias de control complejas y precisas.[CA] L'actual crisi climàtica ha instat a la comunitat investigadora i als fabricants a brindar solucions per a fer que el sector del transport siga més sostenible. D'entre les diverses tecnologies proposades, la combustió a baixa temperatura ha sigut objecte d'una extensa investigació. La combustió premesclada dual-fuel és un dels conceptes que aborden el compromís de NOx-sutge en motors d'encesa per compressió mantenint alta eficiència tèrmica. Aquesta combustió fa ús de dos combustibles amb diferents reactivitats per a millorar la controlabilitat d'aquest tipus de combustió en un ampli rang de funcionament. De manera similar a tots els tipus de combustió premesclada, aquesta combustió és sensible a les condicions d'operació i sol estar subjecta a variabilitat cíclica amb gradients de pressió significatius. En conseqüència, es requereixen estratègies de control avançades per a garantir un funcionament segur i precís del motor. El control en bucle tancat és una eina eficaç per a abordar els desafiaments que planteja la combustió premesclada dual-fuel. En aquesta mena de control, per a mantindre el funcionament desitjat, les accions de control s'adapten i corregeixen a partir d'una retroalimentació amb els senyals d'eixida del motor. Aquesta tesi presenta estratègies de control basades en el mesurament del senyal de pressió en el cilindre, aplicades a motors de combustió premesclada dual-fuel. En ella es resolen diversos aspectes del funcionament del motor mitjançant el disseny de controladors dedicats, fent-se especial èmfasi a analitzar i implementar aquestes solucions als diferents nivells d'estratificació de mescla considerats en aquests motors (és a dir, totalment, altament i parcialment premesclada). Inicialment, es dissenyen estratègies de control basades en el processament del senyal de pressió en el cilindre i se seleccionen accions proporcionals-integrals per a assegurar el rendiment desitjat del motor sense excedir les limitacions mecàniques del motor. També s'avalua la tècnica extremum seeking per a realitzar una supervisió d'una combustió eficient i la reducció d'emissions de NOx. Després s'analitza la ressonància de la pressió en el cilindre i s'implementa un controlador similar a aquell usat per al control de knock per a garantir el funcionament segur del motor. Finalment, s'utilitzen models matemàtics per a dissenyar un model orientat a control i un observador que té com a objectiu combinar els senyals mesurats en el motor per a millorar les capacitats de predicció i diagnòstic en aquesta configuració de motor. Els resultats d'aquest treball destaquen la importància de considerar el control en bucle tancat per a abordar les limitacions trobades en la combustió premesclada. En particular, l'ús del mesurament de pressió en el cilindre mostra la rellevància i el potencial d'aquest senyal per a desenvolupar estratègies de control complexes i precises.[EN] The current climate crisis has urged the research community and manufacturers to provide solutions to make the transportation sector cleaner. Among the various technologies proposed, low temperature combustion has undergone extensive investigation. Premixed dual-fuel combustion is one of the concepts addressing the NOx-soot trade-off in compression ignited engines, while maintaining high thermal efficiency. This combustion makes use of two fuels with different reactivities in order to improve the controllability of this combustion mode over a wide range of operation. Similarly to all premixed combustion modes, this combustion is nevertheless sensitive to the operating conditions and traditionally exhibits cycle-to-cycle variability with significant pressure gradients. Consequently, advanced control strategies to ensure a safe and accurate operation of the engine are required. Feedback control is a powerful approach to address the challenges raised by the premixed dual-fuel combustion. By measuring the output signals from the engine, strategies can be developed to adapt and correct the control actions to maintain the desired operation. This thesis presents control strategies, based on the in-cylinder pressure signal measurement, applied to premixed dual-fuel combustion engines. Various objectives were addressed by designing dedicated controllers, where a special emphasis was made towards analyzing and implementing these solutions to the different levels of mixture stratification considered in these engines (i.e., fully, highly and partially premixed). At first, feedback control strategies based on the in-cylinder pressure signal processing were designed. Proportional-integral actions were selected to ensure the desired engine performance without exceeding the mechanical constraints of the engine. Extremum seeking was evaluated to track efficient combustion phasing and NOx emissions reduction. The in-cylinder pressure resonance was then analyzed and a knock-like controller was implemented to ensure safe operation of the engine. Finally, mathematical models were used to design a control-oriented model and a state observer that aimed to leverage the signals measured in the engine to improve the prediction and diagnostic capabilities in such engine configuration. The results from this work highlighted the importance of considering feedback control to address the limitations encountered in premixed combustion modes. Particularly, the use of the in-cylinder pressure measurement showed the relevance and potential of this signal to develop complex and accurate control strategies.This thesis was financially supported by the Programa Operativo del Fondo Social Europeo (FSE) de la Comunitat Valenciana 2014-2020 through grant ACIF/2018/141.Barbier, ARS. (2022). In-Cylinder Pressure-Based Control of Premixed Dual-Fuel Combustion [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/18327

A Study Model Predictive Control for Spark Ignition Engine Management and Testing

Pressure to improve spark-ignition (SI) engine fuel economy has driven thedevelopment and integration of many control actuators, creating complex controlsystems. Integration of a high number of control actuators into traditional map basedcontrollers creates tremendous challenges since each actuator exponentially increasescalibration time and investment. Model Predictive Control (MPC) strategies have thepotential to better manage this high complexity since they provide near-optimal controlactions based on system models. This research work focuses on investigating somepractical issues of applying MPC with SI engine control and testing.Starting from one dimensional combustion phasing control using spark timing(SPKT), this dissertation discusses challenges of computing the optimal control actionswith complex engine models. A nonlinear optimization is formulated to compute thedesired spark timing in real time, while considering knock and combustion variationconstraints. Three numerical approaches are proposed to directly utilize complex high-fidelity combustion models to find the optimal SPKT. A model based combustionphasing estimator that considers the influence of cycle-by-cycle combustion variations isalso integrated into the control system, making feedback and adaption functions possible.An MPC based engine management system with a higher number of controldimensions is also investigated. The control objective is manipulating throttle, externalEGR valve and SPKT to provide demanded torque (IMEP) output with minimum fuelconsumption. A cascaded control structure is introduced to simplify the formulation and solution of the MPC problem that solves for desired control actions. Sequential quadratic programming (SQP) MPC is applied to solve the nonlinear optimization problem in real time. A real-time linearization technique is used to formulate the sub-QP problems with the complex high dimensional engine system. Techniques to simplify the formulation of SQP and improve its convergence performance are also discussed in the context of tracking MPC. Strategies to accelerate online quadratic programming (QP) are explored. It is proposed to use pattern recognition techniques to “warm-start” active set QP algorithms for general linear MPC applications. The proposed linear time varying (LTV) MPC is used in Engine-in-Loop (EIL) testing to mimic the pedal actuations of human drivers who foresee the incoming traffic conditions. For SQP applications, the MPC is initialized with optimal control actions predicted by an ANN. Both proposed MPC methods significantly reduce execution time with minimal additional memory requirement

Dynamic modeling and control strategies of organic Rankine cycle systems: Methods and challenges

Organic Rankine cycle systems are suitable technologies for utilization of low/medium-temperature heat sources, especially for small-scale systems. Waste heat from engines in the transportation sector, solar energy, and intermittent industrial waste heat are by nature transient heat sources, making it a challenging task to design and operate the organic Rankine cycle system safely and efficiently for these heat sources. Therefore, it is of crucial importance to investigate the dynamic behavior of the organic Rankine cycle system and develop suitable control strategies. This paper provides a comprehensive review of the previous studies in the area of dynamic modeling and control of the organic Rankine cycle system. The most common dynamic modeling approaches, typical issues during dynamic simulations, and different control strategies are discussed in detail. The most suitable dynamic modeling approaches of each component, solutions to common problems, and optimal control approaches are identified. Directions for future research are provided. The review indicates that the dynamics of the organic Rankine cycle system is mainly governed by the heat exchangers. Depending on the level of accuracy and computational effort, a moving boundary approach, a finite volume method or a two-volume simplification can be used for the modeling of the heat exchangers. From the control perspective, the model predictive controllers, especially improved model predictive controllers (e.g. the multiple model predictive control, switching model predictive control, and non-linear model predictive control approach), provide excellent control performance compared to conventional control strategies (e.g. proportional–integral controller, proportional–derivative controller, and proportional–integral–derivative controllers). We recommend that future research focuses on the integrated design and optimization, especially considering the design of the heat exchangers, the dynamic response of the system and its controllability

Modélisation dynamique et commande optimale d'un système de réfrigération à base d'éjecteur

Recently, the ejector-based refrigeration system (ERS) has been widely used in the cooling industry as an appropriate alternative to the compressor-based cooling systems. However, the advantages of ERS such as the reliable operation and low operation and maintenance costs are overshadowed by its low efficiency and design complexity. In this context, this thesis presents the efforts to develop a control model enabling the ERS to operate in its optimal operational conditions. The extensive experimental studies of ERS revealed that at a fixed condenser inlet condition, there exists an optimal primary stream mass flow rate (generating pressure) that simultaneously maximizes the compression ratio (Cr) and exergy efficiency and minimizes the evaporating pressure. Then, the steady state models of the heat exchangers were developed and used to investigate the influence of the increase in generating pressure on the coefficient of performance (COP) of the system and it showed that increasing the generating pressure reduces the COP, linearly. In order to predict the choking regime of the ejector and explain the reasons of observed physical phenomenon, the 1D model of a fixed geometry ejector installed within an R245fa ERS was developed. The developed model demonstrated that the ejector operates in the subcritical mode when the generating pressure is below the Cr optimum point, while it operates in critical mode at or above the optimum generating pressure. Next, a dynamic model of the ERS was built to evaluate the ERS transient response to an increase in the primary stream mass flow rate. Since the ERS dynamics is mainly dominated by the thermal dynamics of the heat exchangers, the dynamic models of the heat exchangers were developed using the moving boundary approach and connected to the developed models of the ejector and steady state models of the pump and expansion valve to build a single dynamic model of the system. The built dynamic model of an ERS was used to estimate the time response of the system in the absence of accurate experimental data of the system’s dynamics. Finally, a control model was designed to drive an ERS towards its optimal operation condition. A self-optimizing, model-free control strategy known as Extremum seeking control (ESC) was adopted to minimize evaporating pressure in a fixed condenser thermal fluid inlet condition. The innovative ESC model named batch phasor ESC (BPESC) was proposed based on estimating the gradient by evaluating the phasor of the output, in batch time. The simulation results indicated that the designed BPESC model can seek and find the optimum evaporating pressure with good performance in terms of predicting the steady state optimal values and the convergence rates.Récemment, le système de réfrigération à éjecteur (SRE) a été largement utilisé dans l'industrie du refroidissement en tant que solution de remplacement appropriée aux systèmes de refroidissement à compresseur. Cependant, les avantages du SRE, tels que le fonctionnement fiable et les faibles couts d'exploitation et de maintenance, sont éclipsés par son faible rendement et sa complexité de conception. Dans ce contexte, ce projet de recherche de doctorat a détaillé les efforts déployés pour développer une stratégie de commande permettant au système de fonctionner dans ses conditions opérationnelles optimales. Les études expérimentales approfondies du SRE ont révélé que, dans une condition d'entrée de condensateur constante, il existe un débit massique optimal du flux primaire (générant une pression) qui maximise simultanément le taux de compression (Cr) et l'efficacité exergétique, et minimise la pression d’évaporation. Ensuite, les modèles à l’état d’équilibre des échangeurs de chaleur ont été développés et utilisés pour étudier l’influence de l’augmentation de la pression générée sur le coefficient de performance (COP) du système et il en ressort que l'augmentation de la pression génératrice réduit le COP de manière linéaire. Afin de prédire le régime d'étouffement de l'éjecteur et d'expliquer les raisons du phénomène physique observé, le modèle 1D d'un éjecteur à géométrie fixe installé dans un système SRE R245fa a été développé. Le modèle développé a démontré que l'éjecteur fonctionne en mode sous-critique lorsque la pression génératrice est inférieure au point optimal de Cr, alors qu'il fonctionne en mode critique à une pression égale ou supérieure à la pression génératrice optimale. Ensuite, un modèle dynamique du SRE a été développé pour étudier la réponse transitoire du SRE lors d’une augmentation du débit massique du flux primaire. Puisque la dynamique du SRE est principalement dominée par la dynamique thermique des échangeurs de chaleur, les modèles dynamiques des échangeurs de chaleur ont été développés à l'aide de l'approche des limites mobiles et connectés aux modèles développés de l'éjecteur et des modèles à l'état stationnaire de la pompe et de la vanne un seul modèle dynamique du système. En l’absence de données expérimentales précises sur la dynamique d’un système SRE, le modèle dynamique développé du SRE a été simulé numériquement pour étudier sa réponse temporelle. Enfin, une stratégie de commande extrêmale (ESC) a été élaboré pour régler automatiquement le SRE à ses conditions de fonctionnement optimales, c’est-à-dire pour trouver la vitesse de la pompe qui minimise la pression dans des conditions d'entrée de condenseur fixes. Afin de proposer une ESC implémentable en temps discret sur une installation réelle sujette à un bruit de mesure important et un traitement hors-ligne par trame, une nouvelle commande extrémale basée sur une approche par phaseur avec une procédure de traitement de signal par trame (BPESC) a été développée et simulée avec le modèle numérique. Les résultats de la simulation ont indiqué que le modèle BPESC peut trouver la vitesse optimale de la pompe avec de bonnes performances en termes de précision et de vitesse de convergence

Extremum Seeking Method And Its Applications In Automotive Control

Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2011Thesis (PhD) -- İstanbul Technical University, Institute of Science and Technology, 2011Kontrol uygulamalarındaki ana yöntem, ele alınan bir sistemi belli bir çalışma noktasına veya referans yörüngesine oturtmaktır. Fakat bazı kontrol problemlerinde, arzu edilen sistem performansı ile o performansı sağlayacak sistem çalışma noktası arasındaki ilişki önceden bilinmemektedir. Örneğin sistemin çalışma noktası ile çıkışı arasında o şekilde bir ilişki olabilir ki, bu fonksiyonun bir ekstremumu olabilir ve amaç, sistem çıkışını bu ekstremum değere getirecek çalışma noktasının aranması olabilir. Sistemin çalışma noktası ile çıkışı arasındaki fonksiyonun belirsizliği, çıkışı maksimize (veya minimize) edecek çalışma noktasının bulunması için bir uyarlama algoritmasının kullanımını gerekli kılmaktadır. Bu problem Ekstremum Arama Algoritması (EAA) ile çözülebilmektedir. Bu algoritma, sistemin performans fonksiyonunun tamamen veya kısmen bilinmediği, zamanla değişebildiği, sistemin eğrisel olduğu, belirsizlik ve bozucular içerdiği durumlar için uygundur. Örneğin acil durum frenlemesinde ihtiyaç duyulduğu gibi, bilinmeyen yol koşullarında tekerlek ile yol arasındaki teker kuvvetlerinin maksimize edilmesi başa çıkılması gereken zor bir iştir. Yol sürtünme katsayısı genellikle önceden bilinmemektedir ve anlık olarak kestirimi zordur. ABS kontrol algoritması, bilinmeyen yol koşullarında teker frenleme kuvvetini maksimize edecek hidrolik fren basıncının optimum çalışma noktasını bulmalıdır. Optimum çalışma noktası seçimindeki bir yanlış karar, ya olabilecekten daha az frenleme kuvvetinin üretilmesine ya da tekerleklerin kilitlenmesine, böylece aracın kontrol edilebilirliğinin ortadan kalkmasına sebep olacaktır. Minimum durma mesafesi ancak tekerleklerin, tekerlek kuvveti-tekerlek kayma oranı eğrisinde en tepe noktasında çalışmaları durumunda gerçekleşir. Bu durumda tekerleklerin kilitlenmesi engellendiği için aracın yanal kararlılığı ve direksiyon ile yönlendirilebilirliği de iyileşecektir. Tezde önce, optimum tekerlek kayma değeri bilinmeden tekerlek kuvvetinin maksimize edilmesi için, tekerlek modeli parametrelerinin uyarlanması yöntemi ile entegre edilmiş bir Ekstremum Arama Algoritması (EAA) önerilmiştir. Bunun için bir çeyrek araç modeli ele alınmıştır. Literatürdeki çoğu ekstremum arama algoritmaları, optimum çalışma noktasını ararken amaç fonksiyonunun gerçek zamanlı olarak ölçümüne dayanmaktadır. Bu çalışmada önerilen kontrol algoritması, amaç fonksiyonunun anlık ölçümü gereksinimini ortadan kaldırarak onun yerine parametre uyarlamalı analitik bir yöntem geliştirmiştir. Kararlılık ve global maksimum noktasına yakınsama durumları, Lyapunov kararlılık analizi ile gösterilmiştir. Önerilen yaklaşımın etkinliğini göstermek için farklı yol koşullarında simulasyon çalışmaları yapılmıştır. İkinci olarak, boyuna frenleme yanında engelden kaçınma manevrasında olduğu gibi yanal hareketi de gözönüne alan EAA temelli bir ABS kontrol algoritması sunulmuştur. Bu algoritmada, yol sürtünme katsayısını kestirmeye gerek kalmadan, tekerlek ve yol arasındaki optimum kayma oranı anlık olarak aranmaktadır. Literatüre getirilen bir yenilik olarak, “tekerlek kuvveti”-“kayma oranı” karakteristik eğrisi üzerinde tekerleklerin çalışma bölgesini belirlemek için sürücü direksiyon girişi ABS frenleme prosedürüne eklenmiştir. Sadece boyuna frenleme durumunda algoritma, tekerleklerin çalışma bölgesini, kuvvet-kayma eğrisinin tepe noktası yakınında tutmaktadır. Eğer sürücü frenlemeye ek olarak yanal hareket de talep ederse, tekerleklerin çalışma bölgesi otomatik olarak değiştirilmekte ve böylece yanal tekerlek kuvvetleri arttırılarak aracın yanal kararlılığı iyileştirilmektedir. Gerçek bir araçtan alınan ölçümlerle doğrulanmış bir tam araç modeli kullanılarak yapılan simülasyonlar algoritmanın etkinliğini göstermektedir. Üçüncü olarak, bir paralel tip hibrid elektrikli araç (HEA) için enerji yönetimi stratejisi önerilmiştir. HEA’lar, daha verimli, daha az çevreyi kirleten araçlara gereksinim sonucunda geliştirilmiştir. Elektrikli araçlar parlak bir çözüm olsa da şu andaki kısa menzilleri ve uzun batarya şarj süreleri, yaygın kullanımlarını geleceğe ötelemektedir. HEA’lar bu doğrultuda kabul edilebilir bir ara çözüm sunmaktadırlar. Hibrid bir elektrikli araçta, elektrokimyasal bir batarya ile güç verilen bir elektrikli motor (EM), fosil yakıt tarafından güç verilen içten yanmalı motor (İYM) ile birlikte kullanılmaktadır. Bunlar, yakıt tüketimi ve emisyonları azaltmadaki önemli potansiyelleri ile günümüzde en uygulanabilir teknoloji olarak görülmektedirler. Tezde verilen HEA enerji yönetim stratejisinin ana amacı, toplam verimi maksimize ederek yakıt tüketimini iyileştirmek ve bunu yaparken de sürücünün güç isteğini karşılamak, batarya şarj durumunu korumak ve İYM, EM güç kısıtları gibi çeşitli kısıtları göz önüne almaktır. Önerilen enerji yönetimi stratejisinde, ekstremum arama algoritması, toplam verimi maksimize edecek şekilde içten yanmalı motor ve elektrik motoru arasında optimum tork dağılımını belirlemektedir. Kontrol stratejisi üst seviye ve alt seviye olmak üzere iki seviyelidir: Üst seviyedeki karar verme kontrolcüsü aracın hangi modda çalışacağını tespit eder. Bu modlar: İçten yanmalı motor ve elektrik motorunun eşzamanlı çalışması, yalnızca elektrik motoru, yalnızca içten yanmalı motor, veya rejeneratif frenleme modlarıdır. İçten yanmalı motor ve elektrik motorunun eşzamanlı çalışması sırasında, bu iki enerji kaynağı arasındaki optimum enerji dağılımını ekstremum arama algoritması, toplam verimi maksimize edecek şekilde belirlemektedir. Böylece literatürde ilk defa bir ekstremum arama algoritması HEA kontrol problemine uyarlanmıştır. Önerilen kontrol algoritmasının performans değerlendirmesi için ayrıca bir dinamik programlama (DP) çözümü de elde edilmiştir. DP çözümü, ele alınan sürüş çevrimi ve sürüş koşulları için elde edilebilecek minimum yakıt tüketimini hesaplamaktadır. DP prosedürünü uygulamak için, bütün bir sürüş çevrimi ve sürüş koşulları önceden bilinmelidir. Gerçek bir araçta gelecekteki sürüş koşulları bilinmediği için DP gerçek zamanlı bir kontrolcü olarak kullanılamaz. Dinamik programlama çözümü gerçek zamanlı kontrol algoritmasının performansının değerlendirilmesi için kullanılmaktadır. Tezde önerilen kontrol algoritmasının etkinliğini göstermek için gerçekçi bir araç modeli kullanılarak çeşitli sürüş çevrimleri ile simülasyonlar yapılmıştır.The mainstream methodology in control applications is to regulate the considered system to known set points or reference trajectories. However, in some control problems, the relation between the system setpoint and a desired system performance is unknown a priori. One situation is that, the reference-to-output map has an extremum and the objective is to select the set point to keep the output at that extremum value. The uncertainty in the reference-to-output map makes it necessary to use an adaptation method to find the set point which maximizes (or minimizes) the output. This problem can be solved via the Extremum Seeking Algorithm (ESA). The algorithm fits problems that possess completely or partially unknown performance functions that may also change in time or that have nonlinear systems with structured or unstructured uncertainties and disturbances. For example, as needed in an emergency braking case, the maximization of the tire force between the tire contact patch and the road in the presence of unknown road conditions is a challenging task. The road friction coefficient is mostly unknown a priori and it is difficult to estimate it on-line. The ABS control algorithm should find the optimal set point of brake hydraulic pressure, which maximizes the wheel braking force subject to unknown and possibly changing road conditions. A misjudgment about the optimal set point choice may cause lower performance of braking via either less friction force generation or via blocking the tire rotation. The minimum stopping distance is ensured when the tires operate at the peak point of the braking force versus slip characteristic curve subject to unknown road conditions. In addition, lateral stability and steerability are also improved as locking of the wheels is prevented. In this thesis, firstly, an Extremum Seeking Algorithm (ESA) integrated with the adaptation of the tire model parameters is proposed for maximizing braking force without utilizing optimum slip value information. A quarter car vehicle model is considered in this section of the thesis. Most of the commonly used extremum seeking algorithms in the literature search for the optimal operating point in order to maximize or minimize a given cost function which is measured on a real-time basis. The control algorithm introduced in this dissertation removes the on-line cost function measurement requirement and instead, an analytic approach with adaptive parameter tuning is developed along the ESA. Stability and reaching the global maximum operating point of the unknown cost function are proved using Lyapunov stability analysis. Simulation study for ABS control under different road pavement conditions is presented to illustrate the effectiveness of the proposed approach. Secondly, an ABS control algorithm based on ESA is presented for considering lateral motion in addition to the longitudinal emergency braking, such as the obstacle avoidance maneuvers, also. The optimum slip ratio between the tire contact patch and the road is searched online without having to estimate the road friction conditions. This is achieved by adapting the ESA as a self-optimization routine that seeks the peak point of the force-slip curve. As a novel addition to the literature, the proposed algorithm incorporates driver steering input information into the ABS braking procedure to determine the operating region of the tires on the “tire force”-“slip ratio” characteristic curve. The algorithm operates the tires near the peak point of the force-slip curve during straight line braking. When the driver demands lateral motion in addition to braking, the operating regions of the tires are modified automatically, for improving the lateral stability of the vehicle by increasing the tire lateral forces. Simulations with a full vehicle model validated with actual vehicle measurements show the effectiveness of the algorithm. Thirdly, an energy management strategy for a parallel type hybrid electric vehicle (HEV) is proposed. HEVs are developed in the need of more efficient, less polluting vehicles. Electric vehicles seem as a promising solution but for now, their short driving distance combined with the long recharging period for batteries postpones their widespread use to the future. HEVs offer an acceptable, intermediate solution. In a hybrid electric vehicle, an electric motor (EM) powered by an electrochemical battery is used along with the internal combustion engine (ICE) powered by fossil fuel. They appear to be one of the most viable technologies with significant potential to reduce fuel consumption and pollutant emissions. The main objective of the HEV energy management strategy given in the thesis is maximizing the powertrain efficiency and hence improving the fuel consumption while meeting the driver’s power demand, sustaining the battery state of charge and considering constraints such as engine and electric motor power limits. In the proposed energy management strategy, extremum seeking algorithm searches constantly optimum torque distribution between the internal combustion engine and electric motor for maximizing the powertrain efficiency. The control strategy has two levels of operation: the upper and lower levels. The upper level decision making controller chooses the vehicle operation mode such as the simultaneous use of the internal combustion engine and electric motor, use of only the electric motor, use of only the internal combustion engine, or regenerative braking. In the simultaneous use of the internal combustion engine and electric motor, the optimum energy distribution between these two sources of energy is determined via the extremum seeking algorithm that searches for maximum powertrain efficiency. In the literature, this is the first time an extremum seeking algorithm is applied to the HEV control problem. A dynamic programming (DP) solution is also obtained and used to form a benchmark for performance evaluation of the proposed method. DP solution gives the minimum obtainable fuel consumption in a considered driving cycle and driving conditions. In order to apply DP procedure, the whole driving cycle and driving conditions should be known in advance. Since future driving conditions are unknown in a real vehicle, DP cannot be utilized in a real time controller. The dynamic programming solution is used offline for performance evaluation of the real time control algorithm. Detailed simulations with various driving cycles and using a realistic vehicle model are presented to illustrate the effectiveness of the methodology.DoktoraPh