Homogeneous charge compression ignition has the potential to significantly reduce NO x emissions, while maintaining a high fuel efficiency. Homogeneous charge compression ignition is characterized by compression-induced autoignition of a lean homogeneous air–fuel mixture. Combustion timing is highly dependent on the in-cylinder state including pressure, temperature and trapped mass. To control homogeneous charge compression ignition combustion, it is necessary to have an accurate representation of the gas exchange process. Currently, microprocessor-based engine control units require that the gas exchange process is linearized around a desired operating point to simplify the model for real-time implementation. This reduces the models’ ability to handle disturbances and limits the flexibility of the model. However, using a field programmable gate array, a detailed simulation of the physical gas exchange process can be implemented in real time. This paper outlines the process of converting physical governing equations to an offline zero-dimensional gas exchange model. The process used to convert this model to a field programmable gate array capable model is described. This model is experimentally validated using a single cylinder research engine with electromagnetic valves to record real-time field programmable gate array gas exchange results and comparing to the offline zero-dimensional physical model. The field programmable gate array model is able to accurately calculate the cylinder temperature and cylinder mass at 0.1 °CA intervals during the gas exchange process for a range of negative valve overlaps, boost conditions and engine speeds making the model useful for future real-time control applications.

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Homogeneous charge compression ignition is a part-load combustion method, which can significantly reduce oxides of nitrogen (NO x) emissions compared to current lean-burn spark ignition engines. The challenge with homogeneous charge compression ignition combustion is the high cyclic variation due to the lack of direct ignition control. A fully variable electromagnetic valve train provides the internal exhaust gas recirculation through negative valve overlap which is required to obtain the necessary thermal energy to enable homogeneous charge compression ignition. This also increases the cyclic coupling as residual gas and unburnt fuel is transferred between cycles through exhaust gas recirculation. To improve combustion stability, an experimentally validated feed-forward water injection controller is presented. Utilizing the low latency and rapid calculation rate of a field programmable gate array, a real-time calculation of residual fuel mass is implemented on a prototyping engine controller. Using this field programmable gate array–based calculation, it is possible to calculate the amount of fuel and the required control interaction during an engine cycle. This controller prevents early rapid combustion following a late combustion cycle using direct water injection to cool the cylinder charge and counter the additional thermal energy from any residual fuel that is transferred between cycles. By cooling the trapped cylinder mass, the upcoming combustion phasing can be delayed to the desired setpoint. The controller was tested at several operating points and showed an improvement in the combustion stability as shown by a reduction in the standard deviation of combustion phasing and indicated mean effective pressure.

Gasoline Controlled Auto Ignition (GCAI) combustion offers high potential for CO 2 emission reduction, but faces challenges regarding combustion stability and high sensitivity to changing boundary conditions. 1 Combustion chamber recirculation allows a wide operation range, but results in a strong coupling of consecutive cycles 2 due to residuals that are transferred to the subsequent combustion cycle. The cycle coupling leads to phases of unstable operation with reduced efficiency and increased emission levels. 3 State of the art control algorithms use data-driven models of GCAI combustion to achieve cycle-to-cycle control of the process 4 or use offline calibration and optimization. 5 A closed-loop control is proposed and implemented on a rapid control prototyping ECU. The control algorithm continuously calculates the current residual fuel in the combustion chamber. The heat release is observed and compared with the theoretical heat release of the injected fuel mass. The rate of unburned fuel mass transferred to the subsequent cycle is calculated offline by a detailed gas exchange model. Based on this information, the control algorithm adapts the injected fuel quantity for each cycle individually using an inverse injector model. In this article, a concept for decoupling consecutive cycles is presented to reduce the deviations of the indicated mean effective pressure (IMEP) and thus the heat release. Unstable sequences are analyzed in the time domain, and unburned residuals are identified as a strong correlating factor for consecutive cycles. Using real-time cylinder pressure analysis based on a field programmable gate array (FPGA) enables the online calculation of unburned residual fuel. Based on this calculation, the injection of each cycle can be adapted individually to decouple consecutive cycles and avoid unstable operation. The results of the control algorithm and the stabilization of the GCAI combustion are validated using a single cylinder research engine and compared to steady state operation.

Gasoline-controlled auto ignition is a promising technology capable of reducing both fuel consumption and emissions at the same time. There are, however, challenges to overcome in order to make practical use of it. One area of research addresses methods that guarantee stable combustion as gasoline-controlled auto ignition is very sensitive to disturbances. This article investigates the capability of nonlinear model predictive control to ensure stable combustion while maintaining efficient operation. For this purpose, a suitable gasoline-controlled auto ignition model is selected and identified using measurement data of a single-cylinder test bed. Building upon this model, a controller based on nonlinear model predictive control is derived and analyzed by means of simulation. The investigation shows that the control manages to follow prescribed set points, also for late combustion, and indicates promising results with respect to real-time computation constraints.

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When compared to traditional engines, homogeneous charge compression ignition has the potential to significantly reduce NO x raw emissions, while maintaining a high fuel efficiency. Homogeneous charge compression ignition is characterized by compression-induced autoignition of a lean homogeneous air–fuel mixture. Since homogeneous charge compression ignition does not utilize direct ignition control, it is strongly dependent on the state of the cylinder charge and can suffer from high cyclic variability. With spark-assisted compression ignition, it has been demonstrated that misfires can be reduced, while preserving the high thermal efficiency of homogeneous charge compression ignition as a result of the more favorable physical mixture properties due to dilution. However, spark-assisted compression ignition reduces the NO x benefits of homogeneous charge compression ignition, as it increases the local combustion temperatures. To merge the advantages of the homogeneous charge compression ignition and the spark-assisted compression ignition combustion processes, a field-programmable gate array for detailed simulation of the physical gas exchange is combined with a rapid spark system. The low latency and computational speed of the field-programmable gate array allows the simulation process to be implemented in real time. When combined with the rapid reaction time of the high-frequency current-based rapid ignition system, a feedforward controller based on the cylinder pressure or heat release is realized. The developed model-based controller determines if a spark is required to assist the homogeneous charge compression ignition combustion process. The use of the field-programmable gate array and rapid ignition system allows for the calculation of combustion properties and controller output within 0.1 °CA. This article presents the development and experimental validation of the developed controller on a single-cylinder research engine. The combustion stability has been significantly improved as reflected in an improved standard deviation of the indicated mean effective pressure and a reduction of the combustion phasing variations. Furthermore, compared to a traditional homogeneous charge compression ignition system, the hydrocarbon emissions can be reduced, while maintaining low NO x emissions.

Homogeneous charge compression ignition or gasoline controlled auto-ignition combustion is characterized by a strong coupling of consecutive cycles, which is caused by residuals from the predecessor cycle. Closed-loop combustion control is considered a promising technology to actively stabilize the process. Model-based control algorithms require precise prediction models that are calculated in real time. In this article, a new approach for the transient measurement of the auto-ignition process and the data-driven modeling of combustion phasing and load is presented. Gasoline controlled auto-ignition combustion is modeled as an autoregressive process to represent the cycle-to-cycle coupling effects. The process order was estimated by partial autocorrelation analysis of steady-state operation measurements. No significant correlations are found for lags that are greater than one. This observation is consistent with the assumption that cycle coupling is mainly caused by the amount of exhaust gas that is directly transferred to the consecutive combustion. Because steady-state operation results in a hard coupling of actuation and feedback variables, only minor variations of the test data can be achieved. The steady-state tests delivered insufficient data for the generalized modeling of the transient autoregressive effects. A new transient testing and measurement approach is required, which maximizes the variation of the predecessor cycle's characteristics. Dynamic measurements were performed with the individual actuation of the injection strategy for each combustion cycle. A polynomial model is proposed to predict the combustion phasing and load. The regression analysis shows no overfitting for higher polynomial orders; nevertheless, a first-order polynomial was selected because of the good extrapolation capabilities of extreme outliers. The prediction algorithm was implemented in MATLAB/Simulink and transferred to a real-time-capable engine control unit. The verification of the approach was performed by test bench measurements in dynamic operation. The combustion phasing was precisely predicted using the autoregressive model. The combustion phasing prediction error could be reduced by 53% in comparison to a state-of-the-art mean value-based prediction. This work provides the basis for the development of a closed-loop autoregressive model-based control for gasoline controlled auto-ignition combustion.