Control Of Combustion Process Research Articles

Research on multi-objective control of PPCI diesel engine combustion process based on data driven modelling

Research on multi-objective control of PPCI diesel engine combustion process based on data driven modelling

Adaptive sliding mode control of petrochemical flare combustion process based on radial basis function network

Steam-assisted combustion elevated flares are currently the most widely used type of petrochemical flares. Due to the complex and variable composition of the waste gas they handle, the combustion environment is severely affected by meteorological conditions. Key process parameters such as intake composition, flow rate, and real-time data of post-combustion residues are difficult to measure or exhibit lag in data availability. As a result, the control methods for these flares are limited, leading to poor control effectiveness. To address this issue, this paper proposes an adaptive sliding mode control method based on the Radial Basis Function (RBF) network. Firstly, the operational characteristics of the petrochemical flare combustion process are analyzed, and a control model for the combustion process is established based on carbon dioxide detection. Secondly, an RBF neural network-based unknown function approximator is designed to identify the nonlinear part of the actual operating system. Finally, by combining the control model of the petrochemical flare combustion and designing the RBF sliding mode controller with its adaptive control law, fast and stable control of the flare combustion state is achieved. Simulation results demonstrate that the designed control strategy can achieve tracking control of the petrochemical flare combustion state, and the adaptive law also accomplishes system identification.

3D Digital Modeling Technology for Thermal Power Plant Boilers Based on Digital Twins

With the rapid advancement of Digital Twins (DTs) technologies, they have emerged as viable solutions for enhancing the control and optimization of thermal power combustion processes. This paper presents a pioneering approach that leverages DTs to revolutionize the combustion process control system within thermal power generating units. Focused on bridging the physical and digital realms, our research establishes DTs of the combustion process control system (CPCS), situated within the Networked Control System Laboratory (NCSLab). We propose a novel five-dimensional (5D) DTs model encompassing the physical, data, service, connection, and virtual models, thereby facilitating a comprehensive fusion of physical and digital information. By analyzing the demands and technical intricacies of the combustion process control system, we design and implement a virtual 3D model, enriching the visualization and analytical capabilities of the DT environment. Furthermore, through controlled experiments on the combustion process and rigorous comparison with offline simulations, we validate the efficacy and feasibility of our approach. Importantly, our research opens avenues for future exploration, particularly in harnessing industrial real-time data to drive the virtual 3D model. Through the integration of Artificial Intelligence (AI) techniques such as Deep Learning, we elevate the capabilities of our DT framework. This enhanced predictive analytics, dynamic optimization, human–machine interaction, and virtual model realism. This research contributes to the advancement of DT technology in the context of thermal power plants and holds promise for driving innovation and efficiency across diverse industrial sectors.

Development of an integrated online deposition and corrosion monitoring system in a full-scale solid waste CFB boiler

Solid waste incineration is a clean and sustainable approach for solid waste management. However, ash deposition and corrosion remain a critical issue due to fuel’s inherent enrichment of alkali chlorine. This study develops an integrated online deposition and corrosion monitoring system to enhance the operational safety and efficiency of solid waste incineration boilers. This system combines linear polarization resistance (LPR) for corrosion rate estimation with heat flux measurements for ash deposition analysis. It can offer a novel approach for real-time monitoring of heat exchangers’ safety during solid waste combustion. It was deployed in a full-scale circulating fluidized bed (CFB) boiler that purely combust solid wastes. Key findings demonstrate the system’s capability to deliver continuous, real-time data, crucial for the dynamic control of combustion processes and the maintenance of heat transfer surfaces. Its robust diagnostic capabilities were evident across various scenarios. Specially, initial corrosion rates sharply increase with deposition rates due to the enrichment of alkali chlorine on inner deposit layer, in which chlorine serves as a catalyst, facilitating the rapid penetration and aggravation of corrosion by other agents. As deposit further buildup, the corrosion rate steadily decreases along with surface temperature, highlighting a dynamic interaction. Moreover, measured corrosion rates can quickly response to temperature variations. Such multi-process online monitoring system provide more possibilities to investigate the inherent interaction between deposition and corrosion. Therefore, this work offers insights that could significantly influence operational strategies, maintenance protocols, and the overall reliability of waste-to-energy technologies.

Analytical study on improving the efficiency and environmental friendliness of solid organic fuels

The purpose of this study was to analyse methods of increasing the efficiency and environmental friendliness of the use of solid organic fuels (SOF) in electricity generation. This study employed a comprehensive approach to the analysis and optimisation of technological processes, operational systems, and environmental aspects of the use of SOF. The study found that the use of modern technologies, such as gasification and pyrolysis, considerably increases the efficiency of converting SOF into electricity. Optimisation of boiler and turbine designs and automation of fuel supply systems helps to reduce energy losses and improve overall system efficiency. It was found that the use of new materials for boilers increases their resistance to corrosion and erosion, which extends the service life of the equipment. The study also showed that the introduction of gas cleaning and secondary combustion systems significantly reduces emissions of harmful substances, which improves environmental performance. An analysis of ash utilisation opportunities showed that its use as a fertiliser or construction material is a promising area. The study proved that an integrated approach to the use of SOF can substantially increase their efficiency and environmental friendliness. The findings of the study suggest that the use of innovative methods of combustion process control allows achieving more stable and efficient power generation. It was proved that the introduction of automated monitoring and control systems reduces operating costs and increases the reliability of equipment. The study also found that the use of advanced analytical tools to predict equipment wear and tear allows for prompt preventive maintenance, which further increases the efficiency and duration of uninterrupted operation of energy systems

A deep learning-based dynamic deformable adaptive framework for locating the root region of the dynamic flames.

Traditional optical flame detectors (OFDs) in flame detection are susceptible to environmental interference, which will inevitably cause detection errors and miscalculations when confronted with a complex environment. The conventional deep learning-based models can mitigate the interference of complex environments by flame image feature extraction, which significantly improves the precision of flame recognition. However, these models focus on identifying the general profile of the static flame, but neglect to effectively locate the source of the dynamic flame. Therefore, this paper proposes a novel dynamic flame detection method named Dynamic Deformable Adaptive Framework (DDAF) for locating the flame root region dynamically. Specifically, to address limitations in flame feature extraction of existing detection models, the Deformable Convolution Network v2 (DCNv2) is introduced for more flexible adaptation to the deformations and scale variations of target objects. The Context Augmentation Module (CAM) is used to convey flame features into Dynamic Head (DH) to feature extraction from different aspects. Subsequently, the Layer-Adaptive Magnitude-based Pruning (LAMP) where the connection with the smallest LAMP score is pruned sequentially is employed to further enhance the speed of model detection. More importantly, both the coarse- and fine-grained location techniques are designed in the Inductive Modeling (IM) to accurately delineate the flame root region for effective fire control. Additionally, the Temporal Consistency-based Detection (TCD) contributes to improving the robustness of model detection by leveraging the temporal information presented in consecutive frames of a video sequence. Compared with the classical deep learning method, the experimental results on the custom flame dataset demonstrate that the AP0.5 value is improved by 4.4%, while parameters and FLOPs are reduced by 25.3% and 25.9%, respectively. The framework of this research extends applicability to a variety of flame detection scenarios, including industrial safety and combustion process control.

Simultaneous determination of 2-D distributions of temperature and absorption coefficient in large-scale pulverized-coal-fired boilers by flame images processing

This paper proposes a new algorithm that can simultaneously measure the two-dimensional temperature distribution and absorption coefficient distribution of a pulverized-coal-fired (PCF) boiler furnace. On the base of optimal estimation of the uniform absorption and scattering coefficients as well as 2-D temperature distribution from the color radiation images of the flame by the Tikhonov regularization algorithm, the product of the absorption coefficient and the absolute blackbody emission intensity forms a new unknown distribution of emission source, which is also reconstructed from the color radiation images of the flame by the Tikhonov method. Then the distribution of absorption coefficient can be obtained from the new distribution of emission source as the 2-D temperature distribution has been known. Experimental investigation has been conducted on a 660 MWe four corner, tangentially firing, PCF boiler. In the flame detectors, a three-band pass filter is added in the CCD industrial camera to improve the monochromaticity of the original flame image. The temperature and absorption coefficient distributions of the cross-sections at three detection layers under a load of 330 MW and at the highest layer under a load of 500 MW are obtained. In order to verify the reliability of the algorithm, the flame radiation intensity images calculated from the 2-D distributions of temperature and absorption coefficient reconstructed at the highest layer under the load of 330 MW are taken as measurement data, the algorithm is repeated and the results show that the 2-D temperature distribution reconstructed is similar to the input one, with relative error less than 1% between their mean temperatures, and relative error less than 10% between the reconstructed and input mean values of absorption and scattering coefficients. It demonstrates that the algorithm and technology proposed in this paper have important application prospects in the monitoring, diagnosis and control of PCF combustion processes.

Thermal Characteristics Enhancement of AN/Mg/NC Composite Using Activated Carbon/Cobalt Oxide as Highly Effective Catalytic Additive

Our study examined the potential of using activated carbon/nanosized cobalt oxide (AC-Co3O4) as a new catalytic additive to improve the efficiency of the parent ammonium nitrate/magnesium/nitrocellulose (AN/Mg/NC) composite. These findings demonstrate a significant improvement in the thermal characteristics of AN/Mg/NC/AC-Co3O4 compared to the initial AN/Mg/NC. Raman spectra confirmed the multilayered nature of AC. Fourier-transform infrared spectroscopy (FTIR) analysis confirmed the presence of cobalt oxide in the synthesized additive. Differential scanning calorimetry (DSC) revealed the catalytic effect of AC-Co3O4 on the AN/Mg/NC composite, resulting in the reduction in the decomposition peak temperature (Tmax) from 277.4 °C (for AN/Mg/NC) to 215.2 °C (for AN/Mg/NC/AC-Co3O4). Thermal gravimetric analysis (TG) determined the overall mass losses (%) for AN/Mg/NC (70%), AN/Mg/NC/AC (75%), and AN/Mg/NC/AC-Co3O4 (80%). This analysis highlights the significant role of AC-Co3O4 in enhancing the energy release during decomposition. Moreover, the use of the differential thermogravimetric (DTG) technique demonstrated the two-step decomposition pathways attributed to the multi-component system. Finally, the combustion tests under the pressure of 3.5 MPa validated the catalytic efficiency of the AC-Co3O4 additive, which enhanced the burning rate (rb) of the AN/Mg/NC/AC-Co3O4 composite from 10.29 to 19.84 mm/s compared to the initial AN/Mg/NC composite. The advantageous nature of the AN/Mg/NC/AC-Co3O4 composite with a lowered decomposition temperature can be applied in rocket propulsion systems, where the precise control of combustion and ignition processes is crucial.

Identification of combustion parameters from cylinder head vibration signal with the influence of random road excitation

The combustion process feedback information can be extracted from the vibration signals of the cylinder head. This is of positive significance for the online monitoring of combustion status and closed-loop control of combustion processes in internal combustion engines. To obtain the combustion process feedback information under the random road excitation (RRE) condition, this paper firstly simulates and analyses the influence of RRE on the combustion parameters identification by an established simplified diesel-suspension model. Results show that the amplitude, frequency and phase of road excitation signal seriously affect the identification of the combustion characteristics, and the combustion excitation response signal is covered by the road excitation response signal in most cases. Then, a method of combining a high-pass filter and principal component analysis (HPF-PCA) is proposed to extract the combustion parameters. This method effectively eliminates the road excitation response signal and successfully identifies the start of combustion (SOC), the location of maximum pressure rise rate (LMPRR) and the location of peak pressure (LPP) from the processed vibration acceleration signal. Finally, the phase deviation caused by the filtering is corrected based on the relationship between the phase deviation of SOC and the cut-off frequency of filtering. The corrected results show that the maximum deviation between the SOC identified from the vibration signals that with and without the influence of road excitation is 0.8 deg.

Co-optimization of injection parameters and injector layouts for a methanol/diesel direct dual-fuel stratification (DDFS) engine

Direct dual fuel stratification (DDFS) is a promising combustion mode to achieve satisfactory engine performance with the effective control of ignition and combustion processes. In this study, a DDFS engine fueled with methanol and diesel was investigated at low loads based on a four-stroke light-duty naturally aspirated engine. Both injection parameters and injector layouts of the two fuels were co-optimized by the fast nondominated sorting genetic algorithm (NSGA-II). The results show that the fractions, injection timings, spray half-included angles, and injector positions of the two fuels all showed significant influences on engine performance. Finally, the high methanol fraction, advanced diesel injection timing, methanol injection timing near the top dead center, and large spray half-included angle of methanol were adopted in the optimal case to achieve both low EISFC and NOx simultaneously. Meanwhile, a centrally-mounted methanol injector was beneficial to shorten combustion duration, and the diesel injector can be arranged in a semicircle area with a radius of approximately 1.14 cm to provide the sufficiently high temperature for the complete combustion of methanol.

Optimal Design of Power Plant Boiler Based on Predictive Control

This paper uses a predictive control algorithm based on ant colony optimization (ACO) and support vector machines (SVM) to simulate the actual historical data of power plant boilers based on the problem that the traditional PID control of boiler combustion process is difficult to achieve the desired control effect, and concludes that the algorithm can effectively overcome the nonlinear, strong coupling, multi-object and large delay characteristics of power plant combustion process. However, its applicability needs to be improved.

Thermal efficiency improvement of a spark ignition engine by stratified water distribution

The stratified water distribution was introduced on a single cylinder direct injection spark ignition engine by changing the direct Water Injection Timing (WIT) and Water Fuel Ratio (WFR) to control the water distribution states before ignition. Experiments were conducted to fundamentally understand the stratified water effects on combustion process control. The results show that different water injection timing could result in wall wetting state, homogeneous state, and stratified state. Stratified water distribution has more obvious suppression effects on knock combustion than other states. Furthermore, optimized combustion process of stratified water distribution case by advancing spark timing is with higher thermal efficiency than homogeneous case.Finally, with the experiment of increasing water injection amounts at stratified state, thermal efficiency increasing was realized by 2.1 %. The high correlation between ignition delay and knocking combustion was demonstrated, which substantiate that water stratified injection has much talent on knock combustion suppressing and thermal efficiency increasing. In further research, the stratified water effects by split injection strategy is hopeful to reduce the water amounts and avoiding oil dilution.

Development of Combustion Process Control Model of HCCI engine

Development of Combustion Process Control Model of HCCI engine

Modeling and Control of Instabilities in Combustion Processes

This paper treats the control of nonstationary oscillations of acoustic pressure in the combustion instability process, which appears in the combustion chamber. Two models of nonstationary combustion process control are presented, where first of them is a classic model, which applies the Rayleigh criterium of phase matching between heat-release rate and acoustic pressure. The second model is an alternative van der Pol model exhibiting selfexciting oscillations due to the feedback with a negative damping. The paper outlines the model of fuel control, which is successfully applied for quenching of selfexcited oscillations. Efficiency of fuel control to quench selfexcited oscillations is shown in the phenomenon of competitive quenching, where the influence of various control parameters is explained.

Spatially selective dilution - A novel approach for heat release control in continuous combustion

To support the ongoing energy transition and minimize the environmental footprint of combustion related technologies, the paper presents a novel approach for combustion control in gas turbines and burners. It relies on spatially targeted injection of inert components in the spray core where existent concepts fail to deliver the desired dilution rate and are unable to fully govern the spatial distribution of heat release rates. Combustion process control is thus possible by actively adjusting the composition and mass flow of spatially selective introduction of inert species in the spray, optionally combined with classic, external exhaust gas recirculation, leading to an ultimate fuel-flexible concept which is capable of adjustments to heterogeneous fuels, their reactivity and physical properties. The proof of concept is demonstrated in a gas turbine combustion chamber first by investigating the isolated effects of spatially selective injection of inert species, its comparison to external exhaust gas recirculation and a combination of both. The results confirm the superiority of the approach as spatially selective mixture inertization is capable of 7% reduction of NO emissions with merely 3% increase of CO emissions and even 9% reduction of PM emissions. Furthermore, the concept proved transferrable together with all its benefits to combustion cycles with external exhaust gas recirculation. In this case, the 63% reduction of NO emissions with no observed CO penalty is possible. Simultaneous exploitation of spatially selective inertization, as well as external exhaust gas recirculation forms a fully controllable concept - spatially selective dilution control (SSDC), which enables extensive adjustability of dilution rates throughout the spray core and primary zone of combustion chamber. Compared to baseline case, such approach was proved to simultaneously reduce CO, NO and PM emissions normalized to fuel thermal power for 39%, 63% and 91%, respectively. The confirmation of applicability of the novel approach and its potential to influence the local conditions is opening a series of possible uses, either as an original design feature for future fuel-flexible systems or as a retrofit approach in existent combustion systems.

Local momentum flux measurement: An effective way for GDI spray targeting in flash boiling conditions

Fuel injection and spray development are crucial processes for gasoline direct injected engines as an extremely accurate control of mixture formation is mandatory in order to attain high thermal efficiency targets while limiting pollutant emissions formation (mainly soot and NOx). In particular detecting the actual spray targeting is challenging as the spray evolution is significantly affected by the wide range of injection operating conditions typically implemented in GDI engines to allow a proper combustion process control. Peculiar injection strategies (rail pressure level, number of injection events) and combustion chamber pressure/temperature levels can result in flash boiling conditions, in which both the atomization process is enhanced and the spray structure is heavily modified with respect to the nominal one, with the different jets possibly collapsing in one single plume. The spray structure experimental analysis is problematic in flash boiling conditions, being conventional optical techniques as imaging and phase Doppler anemometry often unable to provide quantitative data about the inner spray structure, particularly very close to the nozzle. In this study, the actual spray evolution in flashing and non-flashing conditions was investigated by imaging and by momentum local distribution measurement, a methodology based on the spray-impact force method applied to small portions of the fluid structure to detect the local contribution of both the liquid and the gaseous phases to the jet momentum flux. The resulting momentum flux maps can be obtained very close to the nozzle and are not affected by the injector and test chamber operating conditions, offering a significant insight in the jet-to-jet interaction and spray evolution in flash boiling conditions. The obtained results evidenced the progressive modification of the spray structure of a 6-hole symmetrical GDI nozzle from standard to flare flash-boiling conditions, passing from transitional state. The plumes fingerprint gets larger when the ambient to saturation pressure ratio decreases and, when flare flash-boiling occurs, the plumes interaction becomes so intense that the spray structure collapses with a strong reduction of the global cone angle and an increased tip penetration. The obtained results confirmed momentum distribution maps to be an effective way to quantitatively analyze the actual spray targeting, the hole-to-hole flow distribution and the overall spray evolution under a wide range of operating conditions, overcoming severe limitations of other diagnostics like spray visualization and phase Doppler anemometry.

Effect of injection system characteristics on performance, efficiency and emissions of agricultural tractor Diesel engines

The development and the control of Diesel engines combustion process are fundamentally influenced by the parameters of the injection system, namely by the fuel injection characteristic and the injection rate shape. This work comparatively evaluates, by numerical simulation the influences of the injection system characteristics on performance, efficiency, and emissions of two tractor engine types, with four and three cylinders, with similar energetic configuration and same piston displacement. Therefore, the simulation applied two AVL-BOOST computation models, each of them using the AVL-MCC combustion equations system, with the calibration of the models being based on experimental data obtained by testbed investigations. The corresponding specification of the injection systems, together with those of the fuel spray characteristics simulated by the AVL Hydsim tool and the appropriate injection parameters have been adapted for both engines. The results highlighted that for the 3-cylinders engine, presenting lesser total displacement compared to the 4-cylinders one, it is possible to achieve in the condition of similar performance per cylinder, higher efficiency and lower Soot emissions.

Nonlinear Acoustic Tomography for Measuring the Temperature and Velocity Fields by Using the Covariance Matrix Adaptation Evolution Strategy Algorithm

Accurate measurement of temperature and velocity fields in combustion and flow diagnostic plays an important role in analyzing the heat transfer mechanism and ensuring the safe operation of equipment. In this work, considering the refraction effect of sound waves, temperature and velocity fields are reconstructed simultaneously based on the nonlinear acoustic tomography (NAT) by using the covariance matrix adaptation evolution strategy (CMA-ES) algorithm. In the forward problem, the fast two-point ray-tracing algorithm is introduced to track curved sound waves more efficiently. Due to the sparse measurement signals caused by the limited space and curved acoustic paths, Tikhonov regularization is introduced as the constraint of smoothing prior information to reduce the ill-posedness of the problem. The influence of the velocity regularization parameter and temperature regularization parameter on simultaneously visualizing the temperature and corresponding velocity fields are investigated, respectively. Then the selection strategies of these two regularization parameters are given, which are proved to have high selection efficiency. On this basis, inhomogeneous temperature and velocity fields are reconstructed simultaneously by using the CMA-ES algorithm, simulated annealing, and genetic algorithms. By solving the inverse problem of the NAT, which is highly nonlinear and ill-posed, the feasibility and effectiveness of the CMA-ES algorithm in the simultaneous reconstruction of velocity and temperature fields are confirmed. The proposed method for visualizing the temperature and velocity fields will supply key feedback for the combustion process control.

The gaseous hydrocarbon fuel combustion process diagnostics using laser-spark emission spectrometry

To solve the gaseous hydrocarbon fuel combustion process control and diagnostics problem, it is proposed to apply the laser-spark emission spectrometry methods. In propane-air mixture combustion, three modes are investigated: stoichiometric combustion, an enriched mixture, and a lean mixture. A laboratory stand has been developed to study combustion processes by laser-spark emission spectrometry. The plasma radiation spectral characteristics an experimental study results formed in a flame when exposed to laser radiation are presented.

The Numerical Simulation and Experimental Research on Combustion Process in 660MW Boiler

In order to solve the problems of thermal insulation and ash prevention of the furnace combustion layer temperature detection devices installed on the boiler furnace, FLUENT software is used to numerically simulate the actual combustion process in the furnace of 660 MW power plant boiler, and the combustion status of each layer in the furnace is analyzed and studied. And then, according to the results of data simulation the thermal insulation and ash prevention technology implementation of the furnace combustion temperature detection devices is guided. The installation operation test results show that the furnace combustion temperature detection devices work within the range of instrument allowed −20°C∼85°C temperature, which can obtain the direct, rapid, real-time furnace combustion temperature data that provides a valuable source of data for further optimization control of boiler combustion process.