Bastian Lehrheuer

Decoupling of consecutive gasoline controlled auto-ignition combustion cycles by field programmable gate array based real-time cylinder pressure analysis

Gasoline controlled auto-ignition combustion offers high potential for CO2 emission reduction, but faces challenges regarding combustion stability and high sensitivity to changing boundary conditions. Combustion chamber recirculation allows a wide operation range, but results in a strong coupling of consecutive cycles 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. State-of-the-art control algorithms use data-driven models of gasoline controlled auto-ignition combustion to achieve cycle-to-cycle control of the process or use offline calibration and optimization. A closed-loop control is proposed and implemented on a rapid control prototyping engine control unit. 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 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 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 gasoline controlled auto-ignition combustion are validated using a single-cylinder research engine and compared to steady-state operation.

Low Temperature Gasoline Combustion – Potential, Challenges, Process Modeling and Control

Worldwide efforts in combustion development focus on reducing carbon dioxide emissions. Besides improving conventional combustion systems, also alternative systems have to be considered as a measure to achieve that goal. The present work aims to increase the usability of gasoline controlled auto-ignition (GCAI) with its potential benefit regarding fuel consumption of up to 30 %.

Autoregressive modeling of cycle-to-cycle correlations in homogeneous charge compression ignition combustion

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.

Development and experimental validation of a real-time capable field programmable gate array–based gas exchange model for negative valve overlap:

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.