Rapid Control Prototyping for Cylinder Pressure Indication

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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: Methodsmentioning

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

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“…These additional calculations include a thermodynamic zero-point correction for cylinder pressure referencing. Along with a cylinder pressure indication system and angle calculation module as presented by Pfluger et al 26 For all the tests in this work the processor in the ECU has a sampling time which is set at 0.5 ms. Details of the MicroAutoBox II (MABX) prototyping ECU are provided in Table 2.…”

Section: Methodsmentioning

confidence: 99%

“…24,25 However, using the low latency and parallel computing architecture of field programmable gate array (FPGA) hardware, complex cylinder pressure analysis and control algorithms can be implemented in real time. 26 FPGA-based controllers have been successfully used to provide closed-loop control for the position of pneumatic valves. 27 An online calculation of heat release 28 on FPGA hardware has been used for engine control to calculate unburned fuel and prevent an overshoot of indicated mean effective pressure (IMEP).…”

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

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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.

“…For complex cylinder pressure analysis and control algorithms in real time, the low latency and parallel computing architecture of field programmable gate array (FPGA) hardware are useful. 29 FPGA hardware has successfully been used in experimental testing to provide closed-loop control for the position of pneumatic valves. 30 The calculation of heat release in real time has also been achieved in less than 0.02 CA at 1200 r/min on an FPGA, which can be used for HCCI combustion control.…”

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

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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.