scholarly journals Homogenous Charge Compression Ignition (HCCI) combustion control by controlling the CNG parameters

2021 ◽  
Author(s):  
S.Vignesh Eswaran ◽  
Dr. P.Naveen Chandran
Keyword(s):  
Compression Ignition ◽  
Combustion Control ◽  
Hcci Combustion ◽  
Homogenous Charge Compression Ignition

A Framework of Control-Oriented Reaction-Based Model for Trajectory-Based HCCI Combustion With Variable Fuels

2017 ◽  
Author(s):  
Chen Zhang ◽  
Zongxuan Sun
Keyword(s):  
High Fidelity ◽  
Compression Ignition ◽  
Combustion Control ◽  
Free Piston ◽  
Hcci Combustion ◽  
Least Squares Optimization ◽  
Pure Compression ◽  
Reduce Emissions ◽  
Combustion Processes ◽  
Engine Cycle

A novel combustion control, i.e. the trajectory-based combustion control, was proposed previously. This control is enabled by free piston engines (FPEs) and utilizes the FPE’s controllable piston trajectory to enhance thermal efficiency, reduce emissions and realize variable fuels applications. On top of that, a control-oriented model was also developed aimed to implement the trajectory-based combustion control in real-time. Specifically, a unique phase separation method was proposed in the model, which separates an engine cycle into four phases (pure compression, ignition, heat release and pure expansion) and employs the minimal reaction mechanism accordingly. In this paper, the framework of the previous control-oriented model is extended to variable fuels, such as methane, n-heptane and bio-diesel. Such an extension is reasonable since the separated four phases are representative in typical combustion processes of all fuels within an engine cycle. Besides, a least-squares optimization is formulated to calibrate the chemical kinetics variables for each fuel. At last, simulation results and the related analysis show that all the derived control-oriented models have high fidelity and much lighter computational burdens to represent the HCCI combustion of each fuel along variable piston trajectories.

A Phenomenological Model for Predicting the Combustion Phasing and Variability of Spark Assisted Compression Ignition (SACI) Engines

2015 ◽  
Author(s):  
Niket Prakash ◽  
Jason B. Martz ◽  
Anna G. Stefanopoulou
Keyword(s):  
Standard Deviation ◽  
Mean Value ◽  
Operating Conditions ◽  
Compression Ignition ◽  
Cyclic Variability ◽  
Hcci Combustion ◽  
Advanced Combustion ◽  
Gas Fuel ◽  
Homogenous Charge Compression Ignition ◽  
Fuel Fraction

An advanced combustion mode, Spark Assisted Compression Ignition (SACI) has shown the ability to extend loads relative to Homogenous Charge Compression Ignition (HCCI) combustion but at reduced fuel conversion efficiency. SACI combustion is initiated by a spark, with flame propagation followed by a rapid autoignition of the remaining end-gas fuel fraction. Extending upon previous work [1,2], the Wiebe function coefficients used to fit the two combustion phases are regressed here as functions of the air path variables and actuator settings. The parameterized regression model enables mean-value modeling and model-based combustion phasing control. SACI combustion however, exhibits high cyclic variability with random characteristics. Thus, combustion phasing feedback control needs to account for the cyclic variability to correctly filter the phasing data. This paper documents the success in regressing the cyclic variability (defined as the standard deviation in combustion phasing) at various operating conditions, again as a function of air path variables and actuator settings. The combination of the regressed mean and standard deviation models is a breakthrough in predicting the mean-value engine behavior and the random statistics of the cycle-to-cycle variability.

Implementation Challenges and Solutions for Homogenous Charge Compression Ignition Combustion in Diesel Engines

2014 ◽  
Author(s):  
Usman Asad ◽  
Ming Zheng ◽  
David Ting ◽  
Jimi Tjong
Keyword(s):  
High Pressure ◽  
Diesel Engines ◽  
Performance Metrics ◽  
Pressure Rise ◽  
Engine Performance ◽  
Injection Pressure ◽  
Combustion Stability ◽  
Compression Ignition ◽  
Hcci Combustion ◽  
Homogenous Charge Compression Ignition

Homogenous charge compression ignition (HCCI) combustion in diesel engines can provide for cleaner operation with ultra-low NOx and soot emissions. While HCCI combustion has generated significant attention in the last decade, however, to date, it has seen very limited application in production diesel engines. HCCI combustion is typically characterized by earlier than top-dead-center (pre-TDC) phasing, very high pressure rise rates, short combustion durations and minimal control over the timing of the combustion event. To offset the high reactivity of the diesel fuel, large amounts of EGR (30 to 60%) are usually applied to postpone the initiation of combustion, shift the combustion towards TDC and alleviate to some extent, the high pressure rise rates and the reduced energy efficiency. In this work, a detailed analysis of HCCI combustion has been carried out on a high-compression ratio, single-cylinder diesel engine. The effects of intake boost, EGR quantity/temperature, engine speed, injection scheduling and injection pressure on the operability limits have been empirically determined and correlated with the combustion stability, emissions and performance metrics. The empirical investigation is extended to assess the suitability of common alternate fuels (n-butanol, gasoline and ethanol) for HCCI combustion. On the basis of the analysis, the significant challenges affecting the real-world application of HCCI are identified, their effects on the engine performance quantified and possible solutions to overcome these challenges explored through both theoretical and empirical investigations. This paper intends to provide a comprehensive summary of the implementation issues affecting HCCI combustion in diesel engines.

Numerical Simulation of the Effect of Ethanol on Diesel HCCI Combustion Using Multi-Zone Model

2012 ◽  
Vol 229-231 ◽  
pp. 78-81 ◽  
Author(s):  
Su Wei Zhu ◽  
Chun Mei Wang ◽  
Ye Jian Qian ◽  
Li Jun Ou ◽  
Hui Chun Wang
Keyword(s):  
Low Temperature ◽  
Zone Model ◽  
Compression Ignition ◽  
Low Temperature Oxidation ◽  
Temperature Oxidation ◽  
Hcci Combustion ◽  
Active Intermediate ◽  
Simulation Results ◽  
Homogenous Charge Compression Ignition ◽  
Heat Released

This study investigates the potential of controlling diesel homogenous charge compression ignition (HCCI) combustion by blending ethanol, which inhibits low temperature oxidation offering the possibility to control ignition in HCCI combustion. The simulation results from a multi-zone model show that the ethanol reduces the key active intermediate radicals OH, CH2O, H2O2, delays the low temperature oxidation reaction (LTR), reduces the heat released during LTR stage. As a result, it retards the main combustion stage.

Residual-effected homogeneous charge compression ignition at a low compression ratio using exhaust reinduction

2003 ◽  
Vol 4 (3) ◽  
pp. 163-177 ◽  
Author(s):  
P. A. Caton ◽  
A. J. Simon ◽  
J. C. Gerdes ◽  
C. F. Edwards
Keyword(s):  
Compression Ratio ◽  
Equivalence Ratio ◽  
Homogeneous Charge Compression Ignition ◽  
Compression Ignition ◽  
Single Digit ◽  
Hcci Combustion ◽  
Actuation System ◽  
Order Of Magnitude ◽  
No Emissions ◽  
Homogeneous Charge

Studies have been conducted to assess the performance of homogeneous charge compression ignition (HCCI) combustion initiated by exhaust reinduction from the previous engine cycle. Reinduction is achieved using a fully flexible electrohydraulic variable-valve actuation system. In this way, HCCI is implemented at low compression ratio without throttling the intake or exhaust, and without preheating the intake charge. By using late exhaust valve closing and late intake valve opening strategies, steady HCCI combustion was achieved over a range of engine conditions. By varying the timing of both valve events, control can be exerted over both work output (load) and combustion phasing. In comparison with throttled spark ignition (SI) operation on the same engine, HCCI achieved 25–55 per cent of the peak SI indicated work, and did so at uniformly higher thermal efficiency. This was accompanied by a two order of magnitude reduction in NO emissions. In fact, single-digit (ppm) NO emissions were realized under many load conditions. In contrast, hydrocarbon emissions proved to be significantly higher in HCCI combustion under almost all conditions. Varying the equivalence ratio showed a wider equivalence ratio tolerance at low loads for HCCI.

Multiple fuel injection strategy for premixed charge compression ignition combustion engine using biodiesel blends

2022 ◽  
pp. 146808742110667
Author(s):  
Akhilendra Pratap Singh ◽  
Ashutosh Jena ◽  
Avinash Kumar Agarwal
Keyword(s):  
Alternative Fuels ◽  
Fuel Injection ◽  
Engine Performance ◽  
Pilot Injection ◽  
Compression Ignition ◽  
Combustion Control ◽  
Combustion Mode ◽  
Biodiesel Blends ◽  
Injection Parameters ◽  
Study Results

In the last decade, advanced combustion techniques of the low-temperature combustion (LTC) family have attracted researchers because of their excellent emission characteristics; however, combustion control remains the main issue for the LTC modes. The objective of this study was to explore premixed charge compression ignition (PCCI) combustion mode using a double pilot injection (DPI; pilot-pilot-main) strategy to achieve superior combustion control and to tackle the soot-oxides of nitrogen (NOx) trade-off. Experiments were carried out in a single-cylinder research engine fueled with 20% v/v biodiesel blended with mineral diesel (B20) and 40% v/v biodiesel blended with mineral diesel (B40) vis-à-vis baseline mineral diesel. Engine speed and rate of fuel-mass injected were maintained constant at 1500 rpm and 0.6 kg/h mineral diesel equivalent, respectively. Pilot injection timings (at 45° and 35° before top dead center (bTDC)) and fuel quantities were fixed, while three fuel injection pressures (FIPs) and four different start of the main injection (SoMI) timings were investigated in this study. Results showed that multiple pilot injections resulted in a stable PCCI combustion mode, making it suitable for higher engine loads. For all test fuels, advancing SoMI timings led to relatively lesser knocking; however, engine performance characteristics degraded at advanced SoMI timings. B40 exhibited relatively superior engine performance among different test fuels at lower FIP; however, the difference in engine performance was insignificant at higher FIPs. Fuel injection parameters showed a significant effect on emissions, especially on the NOx and particulates. Advancing SoMI timing resulted in 20%–50% lower particulates emissions with a slight NOx increase; however, the differences in emissions at different SoMI timings reduced at higher FIPs. Somewhat higher particulates from biodiesel blends were a critical observation of this study, which was more dominant at advanced SoMI timings. Qualitative correlation between NOx-total particulate mass (TPM) was another critical analysis, which exhibited the relative importance of different fuel injection parameters for other alternative fuels. Overall, B20 at 700 bar FIP and 20° SoMI timing emerged as the most promising proposition with some penalty in CO emission.

Machine Learning Integration with Combustion Physics to Develop a Composite Predictive Model for Reactivity Controlled Compression Ignition Engine

2021 ◽  
pp. 1-27
Author(s):  
Chinmaya Mishra ◽  
P.M.V. Subbarao
Keyword(s):  
Machine Learning ◽  
Predictive Model ◽  
Alternative Methods ◽  
Compression Ignition ◽  
Combustion Control ◽  
Reactivity Controlled Compression Ignition ◽  
Operating Condition ◽  
Residual Gas Fraction ◽  
Residual Gas ◽  
Engine Operating Condition

Abstract Phasing of combustion metrics close to the optimum values across operation range is necessary to avail benefits of reactivity controlled compression ignition (RCCI) engines. Parameters like start of combustion occurrence crank angle (θsoc), occurrence of burn rate fraction reaching 50% (θ50), mean effective pressure from indicator diagram (IMEP) etc. are described as combustion metrics. These metrics act as markers for macroscopic state of combustion. Control of these metrics in RCCI engine is relatively complex due to the nature of ignition. As direct combustion control is challenging, alternative methods like combustion physics derived models are a subject of research interest. In this work, a composite predictive model was proposed by integrating trained random forest (RF) machine learning and artificial neural networks (ANN) to combustion physics derived modified Livengood-Wu integral, parametrized double-Wiebe function, autoignition front propagation speed based correlations and residual gas fraction model. The RF machine learning established a correlative relationship between physics based model coefficients and engine operating condition. The ANN developed a similar correlation between residual gas fraction parameters and engine operating condition. The composite model was deployed for the predictions of θsoc, θ50 and IMEP as RCCI engine combustion metrics. Experimental validation showed an error standard deviation (θ68.3,err) of 0.67 °CA, 1.19°CA, 0.223 bar and symmetric mean absolute percentage error of 6.92%, 7.87% and 4.01% for the predictions of θsoc, θ50 and IMEP respectively on cycle to cycle basis. Wide range applicability, lesser experiments for model calibration, low computational costs and utility for control applications were the benefits of the proposed predictive model.

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