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In this article, two novel linear parameter–varying modeling and control techniques are proposed for active flutter suppression of a smart airfoil model. The smart airfoil model is instrumented with a moving mass that can be used to actively control the airfoil pitching and plunging motions. The first linear parameter–varying modeling approach makes use of the moving mass position as a scheduling parameter, and the hard constraint at the boundaries is imposed by proper selection of the parameter-varying function. The second modeling technique utilizes nonlinear springs and dampers, which are added to both ends of the airfoil groove to confine the motion of the moving mass. A state-feedback-based linear parameter–varying gain-scheduling controller with the guaranteed H ∞ performance is proposed by utilizing the dynamics of the moving mass. In this study, both the position of the moving mass and the free-stream airspeed are considered as the scheduling parameters. The numerical simulations demonstrate the effectiveness of the proposed linear parameter–varying control architectures by significantly improving the performance, while increasing the flutter speed and reducing the control effort. [ABSTRACT FROM AUTHOR]

A control-oriented engine model is necessary for developing and validating the associated engine control strategies. For engines equipped with the turbulent jet ignition system, the interaction between the pre- and main-combustion chambers should be considered in the control-oriented model for model-based control strategies that optimize the overall thermal efficiency in real-time. Therefore, a two-zone combustion model based on the newly proposed parameter-varying Wiebe function is proposed. Since the engine uses the liquid fuel, a pre-chamber air–fuel mixing and vaporization model are also developed. The model was validated using the experimental data from a single-cylinder turbulent jet ignition engine under different operational conditions, and the simulation results show a good agreement with the experimental data. The relative simulation error of the in-cylinder pressure is less than 8%. For most of the other pressure-related variables, such as indicated mean effective pressure and main-chamber burn duration, the relative errors are within 5%. [ABSTRACT FROM AUTHOR]

This paper presents a control-oriented, reaction-based diesel combustion model that predicts the time-based rate of combustion, in-cylinder gas temperature, and pressure over one engine cycle. The model, based on the assumption of a homogeneous thermodynamic combustion process, uses a two-step chemical reaction mechanism that consists of six species: diesel fuel (C10.8H18.7), oxygen (O2), carbon dioxide (CO2), water (H2O), nitrogen (N2), and carbon monoxide (CO). The temperature variation rate is calculated based on the rate of change of species concentrations; the heat loss correlation is also used to study the model performance. The accuracy of the model is evaluated using test data from a GM 6.6 L, eight-cylinder Duramax engine. The main contribution is the model calibration under different key operational conditions over a large engine speed and load range as well as different injection timings and exhaust gas recirculation rates by solving the optimal calibration problem. The calibrated reaction-based model accurately predicts the indicated mean effective pressure, while keeping the errors of in-cylinder pressure and temperature small, and, at the same time, significantly reduces the calibration effort, especially when the engine is operated under multiple fuel injection operations compared with Wiebe-based combustion models. The calibrated model parameters have a strong correlation to engine speed, load, and injection timings, and, as a result, a universal parameter calibration structure is proposed for entire operational conditions. [ABSTRACT FROM AUTHOR]

Traditionally the transmission gear-shifting schedule is based upon the throttle position and the vehicle (or engine) speed. This paper proposes to add a third parameter, called the terrain coefficient, to form a three-parameter gear-shifting schedule for improving the fuel economy of a vehicle. The terrain coefficient is a compound parameter consisting of the road grade and the rolling resistance coefficient. It can be estimated in real time by the proposed multi-step recursive least-squares method. The dynamic programming and the moving least-squares method are adopted to optimize the gear sequences and to generate the three-parameter gear-shifting schedule. The proposed gear-shifting schedule is evaluated against the traditional two-parameter gear-shifting schedule via Simulink simulations and on-road experiments using a heavy-duty vehicle. The simulation results for the Urban Dynamometer Driving Schedule and the US06 Supplemental Federal Test Procedure driving cycles show that the fuel economies of the proposed gear-shifting schedule are improved by 3.3% and 2.7% respectively over that of the traditional two-parameter schedule. The experimental results indicate that the three-parameter gear-shifting schedule improves the fuel economy by 3.5% over the traditional schedule with a satisfactory acceleration performance. [ABSTRACT FROM AUTHOR]

A control-oriented model for the variable-geometry turbocharger is critical for model-based variable-geometry turbocharger control design. Typically, the variable-geometry turbocharger turbine power is modeled with a fixed mechanical efficiency of the turbocharger on the assumption of an isentropic process. The fixed-efficiency approach is an oversimplification and may lead to modeling errors because of an overpredicted or underpredicted compressor power. This leads to the use of lookup-table-based approaches for defining the mechanical efficiency of the turbocharger. Unfortunately, since the vane position of a variable-geometry turbocharger introduces a third dimension into these maps, real-time implementation requires three-dimensional interpolations with increased complexity. Map-based approaches offer greater fidelity in comparison with the fixed-efficiency approach but may introduce additional errors due to interpolation between the maps and extrapolation to extend the operational range outside the map. Interpolation errors can be managed by using dense maps with extensive flow bench testing; smooth extrapolation is necessary when the turbine is operated outside the mapped region, e.g. in low-flow and low-speed conditions. Extending the map to this region requires very precise flow control and measurement using a motor-driven compressor, which currently is not a standard test procedure. In this paper, a physics-based control-oriented model of the turbine power and the associated power loss is proposed and developed, where the turbine efficiency is modeled as a function of both the vane position of the variable-geometry turbocharger and the speed of the turbine shaft. As a result, the proposed model eliminates the interpolation errors with smooth extension to operational conditions outside typically mapped regions. [ABSTRACT FROM AUTHOR]

Turbulent jet ignition combustion is a promising concept for achieving high thermal efficiency and low NOx (nitrogen oxides) emissions. A control-oriented turbulent jet ignition combustion model with satisfactory accuracy and low computational effort is usually a necessity for optimizing the turbulent jet ignition combustion system and developing the associated model-based turbulent jet ignition control strategies. This article presents a control-oriented turbulent jet ignition combustion model developed for a rapid compression machine configured for turbulent jet ignition combustion. A one-zone gas exchange model is developed to simulate the gas exchange process in both pre- and main-combustion chambers. The combustion process is modeled by a two-zone combustion model, where the ratio of the burned and unburned gases flowing between the two combustion chambers is variable. To simulate the influence of the turbulent jets on the rate of combustion in the main-combustion chamber, a new parameter-varying Wiebe function is proposed and used for the mass fraction burned calculation in the main-combustion chamber. The developed model is calibrated using the least-squares fitting and optimization procedures. Experimental data sets with different air-to-fuel ratios in both combustion chambers and different pre-combustion chamber orifice areas are used to calibrate and validate the model. The simulation results show good agreement with the experimental data for all the experimental data sets. This indicates that the developed combustion model is accurate for developing and validating turbulent jet ignition combustion control strategies. Future work will extend the rapid compression machine combustion model to engine applications. [ABSTRACT FROM AUTHOR]

The vast majority of the existing work in gain-scheduling (GS) control literature assumes perfect knowledge of scheduling parameters. Generally, this assumption is not realistic since for practical control applications measurement noises are unavoidable. In this paper, novel synthesis conditions are derived to synthesise robust GS controllers with mixedperformance subject to uncertain scheduling parameters. The conditions are formulated in terms of parameterised bilinear matrix inequalities (PBMIs) that depend on varying parameters inside multi-simplex domain. The conditions providepracticalGS controllers independent of the derivatives of scheduling parameters. That is, the designed controllers are feasible for implementation. Since bilinear matrix inequality problems are intractable, an iterative PBMI algorithm is developed to solve the developed synthesis conditions. By the virtue of this algorithm, conservativeness reduction is achieved with few iterations. Examples are presented to illustrate the effectiveness of the developed conditions. Compared to other design methods from literature, the developed conditions achieve better performance. [ABSTRACT FROM AUTHOR]