Closed-Loop Control of HCCI Engine Dynamics

The topic of the thesis is control of Homogeneous Charge Compression Ignition (HCCI) engine dynamics. HCCI offers a potential to combine high efficiency with very low emissions. In order to fulfill the potential benefits, closed-loop control is needed. The thesis discusses sensors, feedback signals and actuators for closed-loop control of the HCCI combustion. Closed-loop control of the HCCI combustion using ion current is demonstrated. Models of the HCCI dynamics suitable for purposes of control design are presented. It is shown that low-order models are sufficient to describe the HCCI dynamics. Models of HCCI combustion have been determined both by system identification and by physical modeling. Different methods for characterizing and controlling the HCCI combustion are outlined and demonstrated. In cases where the combustion phasing in a six-cylinder heavy-duty engine was controlled, either by a Variable Valve Actuation system using the inlet valve or a dual-fuel system, results are presented. Combustion phasing is a limiting factor of the load control and emission control performance. A system where control of HCCI on a cycle-to-cycle basis is outlined and cylinder individual cycle-to-cycle control on a six-cylinder heavy duty engine is presented. Various control strategies are compared. Model-based control, such as LQG and Model Predictive Control MPC, and PID control are shown to give satisfactory controller performance. An MPC controller is proposed as a solution to the problem of load-torque control with simultaneous minimization of the fuel consumption and emissions, while satisfying the constraints on cylinder pressure

PHYSICS-BASED MODELING AND CONTROL OF POWERTRAIN SYSTEMS INTEGRATED WITH LOW TEMPERATURE COMBUSTION ENGINES

Low Temperature Combustion (LTC) holds promise for high thermal efficiency and low Nitrogen Oxides (NOx) and Particulate Matter (PM) exhaust emissions. Fast and robust control of different engine variables is a major challenge for real-time model-based control of LTC. This thesis concentrates on control of powertrain systems that are integrated with a specific type of LTC engines called Homogenous Charge Compression Ignition (HCCI). In this thesis, accurate mean value and dynamic cycleto- cycle Control Oriented Models (COMs) are developed to capture the dynamics of HCCI engine operation. The COMs are experimentally validated for a wide range of HCCI steady-state and transient operating conditions. The developed COMs can predict engine variables including combustion phasing, engine load and exhaust gas temperature with low computational requirements for multi-input multi-output realtime HCCI controller design. Different types of model-based controllers are then developed and implemented on a detailed experimentally validated physical HCCI engine model. Control of engine output and tailpipe emissions are conducted using two methodologies: i) an optimal algorithm based on a novel engine performance index to minimize engine-out emissions and exhaust aftertreatment efficiency, and ii) grey-box modeling technique in combination with optimization methods to minimize engine emissions. In addition, grey-box models are experimentally validated and their prediction accuracy is compared with that from black-box only or clear-box only models. A detailed powertrain model is developed for a parallel Hybrid Electric Vehicle (HEV) integrated with an HCCI engine. The HEV model includes sub-models for different HEV components including Electric-machine (E-machine), battery, transmission system, and Longitudinal Vehicle Dynamics (LVD). The HCCI map model is obtained based on extensive experimental engine dynamometer testing. The LTC-HEV model is used to investigate the potential fuel consumption benefits archived by combining two technologies including LTC and electrification. An optimal control strategy including Model Predictive Control (MPC) is used for energy management control in the studied parallel LTC-HEV. The developed HEV model is then modified by replacing a detailed dynamic engine model and a dynamic clutch model to investigate effects of powertrain dynamics on the HEV energy consumption. The dynamics include engine fuel flow dynamics, engine air flow dynamics, engine rotational dynamics, and clutch dynamics. An enhanced MPC strategy for HEV torque split control is developed by incorporating the effects of the studied engine dynamics to save more energy compared to the commonly used map-based control strategies where the effects of powertrain dynamics are ignored. LTC is promising for reduction in fuel consumption and emission production however sophisticated multi variable engine controllers are required to realize application of LTC engines. This thesis centers on development of model-based controllers for powertrain systems with LTC engines

Transient Load-Speed Control in Multi-Cylinder Recompression HCCI Engines

Strict proposed fuel economy and emissions standards for automotive internal combustion engines have motivated the study of advanced low-temperature combustion modes that promise higher combustion efficiencies with low engine-out emissions. This work presents modeling and control results for one such combustion mode -- recompression homogeneous charge compression ignition (HCCI) combustion. Regulating desired charge properties in recompression HCCI involves the retention of a large amount of the residual charge between engine cycles, thus introducing significant inter-cycle feedback in the system. This work considers a baseline controller from literature, and proposes two improved model-based control strategies. The controllers use exhaust valve timing and fuel injection timings to track combustion phasings during transitions in the HCCI region of the multi-cylinder engine load-speed operating map. Fast and stable control of these transitions is demonstrated, which maximizes the length of stay in the HCCI region, and hence the efficiency benefit of advanced combustion. The baseline controller, which is a feedback-feedforward controller adapted from literature, is tuned using a low-order, discrete-time, control-oriented model that describes the stable, high efficiency HCCI region. The first improved control strategy augments the baseline controller with a reference or fuel governor that modifies transient fuel mass commands during large load transitions, when the possibility of future actuator constraint violations exists. This approach is shown in experiments to improve the combustion phasing and load responses, as well as prevent engine misfires. Issues with high cyclic variability during late phasing and low load conditions, and their impact on transient performance, are discussed. These issues are physically explained through recompression heat release caused due to unburned and recycled fuel. The control-oriented model is augmented with recompression heat release to predict the onset of the oscillatory, high variability region. The second improved control strategy uses this physical understanding to improve combustion phasing tracking performance. Transitions tested on a multicylinder HCCI engine include load transitions at fixed engine speeds, engine speed ramps at fixed load, simultaneous load and speed transitions, and select FTP75 drive-cycle transitions with high load slew rates. This improved model-based control strategy is proposed as a solution for the HCCI transient control problem.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107072/1/sjade_1.pd

Experimental Analysis and Control of Recompression Homogeneous Charge Compression Ignition Combustion at the High Cyclic Variability Limit.

The automotive industry currently faces many challenges pertaining to strict emissions and fuel consumption constraints for a sustainable society. These regulations have motivated the investigation of low temperature combustion modes such as homogeneous charge compression ignition (HCCI) as a potential solution to meet these demands. HCCI combustion is characterized by high efficiency and low engine-out emissions. However, this advanced combustion mode is limited in the speed-load operating space due to high pressure rise rates for increased loads. Often higher loads are run at later combustion phasings to reduce pressure rise rates, however high cyclic variability (CV) can also be a limiting factor for late combustion phasings. This work presents advancements in the understanding of high variability dynamics in recompression HCCI as well as methods for control of CV and load transitions which typically encounter regions of high variability. Standard in-cylinder pressure based analysis methods are extended for use on high variability data. This includes a method of determining the trapped residual mass in real time. Determination of the residual mass is critical in recompression HCCI because of the combustion's sensitivity to the thermal energy contained within the residual charge. Trapping too much or little residuals can lead to ringing or misfires and CV, respectively. Various levels of CV are studied using large experimental data sets to ensure statistical relevance. The cycle resolved analysis of this data has allowed for the development of a predictive model of the variability associated with lean late phasing combustion. This model is used to develop control which can suppress cyclic variability at steady state. Knowledge about steady state control of CV and its oscillatory dynamics is further applied to the development of an adaptive controller. The adaptive controller uses a parameter estimation scheme in the feedforward component of a baseline midranging structure. The adaptive feedforward component enables the ability to correct for modeling errors and reduces parameterization effort. Experimental results demonstrate that the control is effective at navigating through large load transients while avoiding excess amounts of variability. Additionally, the actuators spend more time in a region of high authority when compared to non-adaptive control.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107231/1/larimore_1.pd

EXPERIMENTAL SETUP AND CONTROLLER DESIGN FOR AN HCCI ENGINE

Homogeneous charged compression ignition (HCCI) is a promising combustion mode for internal combustion (IC) engines. HCCI engines have very low NOx and soot emission and low fuel consumption compared to traditional engines. The aim of this thesis is divided into two main parts: (1) engine instrumentation with a step towards converting a gasoline turbocharged direct injection (GTDI) engine to an HCCI engine; and (2) developing controller for adjusting the crank angle at 50% mass fuel burn (CA50), exhaust gas temperature Texh, and indicated mean effective pressure (IMEP) of a single cylinder Ricardo HCCI engine. The base GTDI engine is modified by adding an air heater, inter-cooler, and exhaust gas recirculation (EGR) in the intake and exhaust loops. dSPACE control units are programmed for adding monitoring sensors and implementing actuators in the engine. Control logics for actuating electronic throttle control (ETC) valve, EGR valve, and port fuel injector (PFI) are developed using the rapid control prototyping (RCP) feature of dSPACE. A control logic for crank/cam synchronization to determine engine crank angle with respect to firing top dead center (TDC) is implemented and validated using in-cylinder pressure sensor data. A control oriented model (COM) is developed for estimating engine parameters including CA50, Texh, and IMEP for a single cylinder Ricardo engine. The COM is validated using experimental data for steady state and transient engine operating conditions. A novel three-input three-output controller is developed and tested on a detailed physical HCCI engine plant model. Two type of controller design approaches are used for designing HCCI controllers: (1) empirical, and (2) model-based. A discrete sub-optimal sliding mode controller (DSSMC) is designed as a model-based controller to control CA50 and Texh, and a PI controller is designed to control IMEP. The results show that the designed controllers can successfully track the reference trajectories and can reject the external disturbances within the given operating region

Lyapunov based optimal control of a class of nonlinear systems

Optimal control of nonlinear systems is in fact difficult since it requires the solution to the Hamilton-Jacobi-Bellman (HJB) equation which has no closed-form solution. In contrast to offline and/or online iterative schemes for optimal control, this dissertation in the form of five papers focuses on the design of iteration free, online optimal adaptive controllers for nonlinear discrete and continuous-time systems whose dynamics are completely or partially unknown even when the states not measurable. Thus, in Paper I, motivated by homogeneous charge compression ignition (HCCI) engine dynamics, a neural network-based infinite horizon robust optimal controller is introduced for uncertain nonaffine nonlinear discrete-time systems. First, the nonaffine system is transformed into an affine-like representation while the resulting higher order terms are mitigated by using a robust term. The optimal adaptive controller for the affinelike system solves HJB equation and identifies the system dynamics provided a target set point is given. Since it is difficult to define the set point a priori in Paper II, an extremum seeking control loop is designed while maximizing an uncertain output function. On the other hand, Paper III focuses on the infinite horizon online optimal tracking control of known nonlinear continuous-time systems in strict feedback form by using state and output feedback by relaxing the initial admissible controller requirement. Paper IV applies the optimal controller from Paper III to an underactuated helicopter attitude and position tracking problem. In Paper V, the optimal control of nonlinear continuous-time systems in strict feedback form from Paper III is revisited by using state and output feedback when the internal dynamics are unknown. Closed-loop stability is demonstrated for all the controller designs developed in this dissertation by using Lyapunov analysis --Abstract, page iv