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

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

Design and Optimization of In-Cycle Closed-Loop Combustion Control with Multiple Injections

With the increasing demand of transportation, biofuels play a fundamental role in the transition to sustainable powertrains. For the increased uncertainty of biofuel combustion properties, advanced combustion control systems have the potential to operate the engine with high flexibility while maintaining a high efficiency and robustness. For that purpose, this thesis investigates the analysis, design, implementation, and application of closed-loop Diesel combustion control algorithms. By fast in-cylinder pressure measurements, the combustion evolution can be monitored to adjust a multi-pulse fuel injection within the same cycle. This is referred to as in-cycle closed-loop combustion control.The design of the controller is based on the experimental characterization of the combustion dynamics by the heat release analysis, improved by the proposed cylinder volume deviation model. The pilot combustion, its robustness and dynamics, and its effects on the main injection were analyzed. The pilot burnt mass significantly affects the main combustion timing and heat release shape, which determines the engine efficiency and emissions. By the feedback of a pilot mass virtual sensor, these variations can be compensated by the closed-loop feedback control of the main injection. Predictive models are introduced to overcome the limitations imposed by the intrinsic delay between the control action (fuel injection) and output measurements (pressure increase). High prediction accuracy is possible by the on-line model adaptation, where a reduced multi-cylinder method is proposed to reduce their complexity. The predictive control strategy permits to reduce the stochastic cyclic variations of the controlled combustion metrics. In-cycle controllability of the combustion requires simultaneous observability of the pilot combustion and control authority of the main injection. The imposition of this restriction may decrease the indicated efficiency and increase the operational constraints violation compared to open-loop operation. This is especially significant for pilot misfire. For in-cycle detection of pilot misfire, stochastic and deterministic methods were investigated. The on-line pilot misfire diagnosis was feedback for its compensation by a second pilot injection. High flexibility on the combustion control strategy was achieved by a modular design of the controller. A finite-state machine was investigated for the synchronization of the feedback signals (measurements and model-based predictions), active controller and output action. The experimental results showed an increased tracking error performance and shorter transients, regardless of operating conditions and fuel used.To increase the indicated efficiency, direct and indirect optimization methods for the combustion control were investigated. An in-cycle controller to reach the maximum indicated efficiency increased it by +0.42%unit. The indirect method took advantage of the reduced cyclic variations to optimize the indicated efficiency under constraints on hardware and emission limits. By including the probability and in-cycle compensation of pilot misfire, the optimization of the set-point reference of CA50 increased the indicated efficiency by +0.6unit at mid loads, compared to open-loop operation.Tools to evaluate the total cost of the system were provided by the quantification of the hardware requirements for each of the controller modules

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

Adaptive torque-feedback based engine control

The aim of this study was to develop a self-tuning or adaptive SI engine controller using torque feedback as the main control variable, based on direct/indirect measurement and estimation techniques. The indirect methods include in-cylinder pressure measurement, ion current measurement, and crankshaft rotational frequency variation. It is proposed that torque feedback would not only allow the operating set-points to be monitored and achieved under wider conditions (including the extremes of humidity and throttle transients), but to actively select and optimise the set-points on the basis of both performance and fuel economy. A further application could allow the use of multiple fuel types and/or combustion enhancing methods to best effect. An existing experimental facility which comprised a Jaguar AJ-V8 SI engine coupled to a Heenan-Froude Dynamatic GVAL (Mk 1) dynamometer was adopted for this work, in order to provide a flexible distributed engine test system comprising a combined user interface and cylinder pressure monitoring system, a functional dynamometer controller, and a modular engine controller which is close coupled to an embedded PC has been created. The considerable challenges involved in creating this system have meant that the core research objectives of this project have not been met. Nevertheless, an open-architecture software and hardware engine controller and independent throttle controller have been developed, to the point of testing. For the purposes of optimum ignition timing validation and combustion knock detection, an optical cylinder pressure measurement system with crank angle synchronous sampling has been developed. The departure from the project’s initial aims have also highlighted several important aspects of eddy-current dynamometer control, whose closed-loop behaviour was modelled in Simulink to study its control and dynamic response. The design of the dynamometer real-time controller was successfully implemented and evaluated in a more contemporary context using an embedded digital controller.EThOS - Electronic Theses Online ServiceSchool of Mechanical & Systems EngineeringNewcastle UniversityGBUnited Kingdo

Intelligent Transportation Related Complex Systems and Sensors

Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITS) are being widely adopted worldwide to improve the efficiency and safety of the transportation system. They enable users to be better informed and make safer, more coordinated, and smarter decisions on the use of transport networks. Current ITSs are complex systems, made up of several components/sub-systems characterized by time-dependent interactions among themselves. Some examples of these transportation-related complex systems include: road traffic sensors, autonomous/automated cars, smart cities, smart sensors, virtual sensors, traffic control systems, smart roads, logistics systems, smart mobility systems, and many others that are emerging from niche areas. The efficient operation of these complex systems requires: i) efficient solutions to the issues of sensors/actuators used to capture and control the physical parameters of these systems, as well as the quality of data collected from these systems; ii) tackling complexities using simulations and analytical modelling techniques; and iii) applying optimization techniques to improve the performance of these systems. It includes twenty-four papers, which cover scientific concepts, frameworks, architectures and various other ideas on analytics, trends and applications of transportation-related data

Parabolic Dish Solar Thermal Power Annual Program Review Proceedings

The results of activities of the parabolic dish technology and applications development element of DOE's Solar Thermal Energy System Program are presented. Topics include the development and testing of concentrators, receivers, and power conversion units; system design and development for engineering experiments; economic analysis and marketing assessment; and advanced development activities. A panel discussion concerning industrial support sector requirements is also documented

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

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

Powertrain Systems for Net-Zero Transport

The transport sector continues to shift towards alternative powertrains, particularly with the UK Government’s announcement to end the sale of petrol and diesel passenger cars by 2030 and increasing support for alternatives. Despite this announcement, the internal combustion continues to play a significant role both in the passenger car market through the use of hybrids and sustainable low carbon fuels, as well as a key role in other sectors such as heavy-duty vehicles and off-highway applications across the globe. Building on the industry-leading IC Engines conference, the 2021 Powertrain Systems for Net-Zero Transport conference (7-8 December 2021, London, UK) focussed on the internal combustion engine’s role in Net-Zero transport as well as covered developments in the wide range of propulsion systems available (electric, fuel cell, sustainable fuels etc) and their associated powertrains. To achieve the net-zero transport across the globe, the life-cycle analysis of future powertrain and energy was also discussed. Powertrain Systems for Net-Zero Transport provided a forum for engine, fuels, e-machine, fuel cell and powertrain experts to look closely at developments in powertrain technology required, to meet the demands of the net-zero future and global competition in all sectors of the road transportation, off-highway and stationary power industries

Marshall Space Flight Center Faculty Fellowship Program

The research projects conducted by the 2016 Faculty Fellows at NASA Marshall Space Flight Center included propulsion studies on propellant issues, and materials investigations involving plasma effects and friction stir welding. Spacecraft Systems research was conducted on wireless systems and 3D printing of avionics. Vehicle Systems studies were performed on controllers and spacecraft instruments. The Science and Technology group investigated additive construction applied to Mars and Lunar regolith, medical uses of 3D printing, and unique instrumentation, while the Test Laboratory measured pressure vessel leakage and crack growth rates