Verbrennungssteuerung durch Selbstzündung

Homogeneous Charge Compression Ignition (HCCI) is a low temperature combustion technique with a high potential for reducing emissions while simultaneously improving fuel consumption. However, the high sensitivity to changing boundary conditions and low combustion stability at the edges of the operating range has lead to implementation challenges. Additionally, cyclic coupling through internal exhaust gas recirculation causes cyclic variations of the process, resulting in incomplete combustion, or even misfiring. Thus, consecutive cycles must be decoupled to increase the process stability. To achieve an accurate description of the coupling effects on a cycle-to-cycle and an inner-cyclic timescale, a novel measurement methodology is presented to generate data with a high variance. For this purpose, an active process excitation is performed to capture all relevant interactions between operating and feedback variables to enable modeling of the coupling effects on both timescales. To demonstrate the potential of the methodology, the generated data is used to design multiple input, multiple output (MIMO) models for both cyclic and inner-cyclic timescales. Artificial neural networks are then utilized to address the highly nonlinear process by taking advantage of the large amount of training data. Inverse process models are then used to implement a pure cycle-to-cycle and a multiscale MIMO closed-loop controller. Compared to state-of-the-art rule-based control approaches, the process stability and its thermodynamic efficiency are significantly improved. For the multiscale MIMO controller, a reduction of the standard deviation of the indicated mean effective pressure and the combustion phasing of more than 65% is achieved. In particular, the additional inner-cyclic feedback loop achieves a remarkable reduction of the standard deviation of approximately 35% and a 1.2% higher indicated efficiency compared to the cycle-to-cycle MIMO controller. The dynamic measurement with active in-cycle process excitation has proven to be an enabler for data-driven MIMO control of HCCI on multiple timescales.

Section: Introductionmentioning

confidence: 99%

Dynamic measurement with in-cycle process excitation of HCCI combustion: The key to handle complexity of data-driven control?

Bedei

Oberlies

Schaber

et al. 2022

“…1–3 Therefore, expensive exhaust after-treatment systems can be reduced or simplified. 4–6 HCCI utilizes rapid multi-site combustion, and this in combination with reduced wall heat losses from LTC leads to thermodynamic and fuel efficiency benefits of up to 30% over current gasoline engines. 7 HCCI combustion is defined by compression-induced autoignition and is therefore highly dependent on the in-cylinder temperature, pressure and fuel mixture after compression.…”

Section: Introductionmentioning

confidence: 99%

Development and experimental validation of a field programmable gate array–based in-cycle direct water injection control strategy for homogeneous charge compression ignition combustion stability

Gordon

Wouters

Wick

et al. 2019

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.

“…1–4 Therefore, expensive exhaust aftertreatment systems can be reduced or simplified. 4–6 Improved efficiency is also possible when using HCCI combustion due to the rapid global and spatial combustion in combination with reduced wall heat losses from the LTC. The potential of HCCI combustion has been proven in numerous research projects.…”

Section: Introductionmentioning

confidence: 99%

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

Gordon

Wouters

Wick

et al. 2018

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.