Rail Pressure Research Articles

Performance study of an innovative dual injection mode injector for marine low-speed dual-fuel engine

Marine low-speed dual-fuel engines typically have two sets of fuel injection system, main-injection and micro-injection. In order to make the fuel injection system of marine low-speed dual-fuel engine compact in structure and flexible in injection control, an innovative dual injection mode injector (DIMI) which can achieve both the functions of main-injection and micro-injection was proposed. The switching between main-injection and micro-injection mode of the injector is achieved through the collaborative control of dual solenoid valves. Based on the constructed AMESim model, the injection quantity characteristic and hydraulic efficiency of the DIMI were investigated under different working conditions and injection modes. The results show that, when the DIMI in main-injection mode achieves injection quantity characteristic similar to those of a traditional electronically controlled injector (TECI), the electromagnetic forces of solenoid valves of the DIMI are less required to 80% of that of the TECI, and the fuel return quantity and hydraulic efficiency of the DIMI are comparable to those of the TECI under the same working conditions. By changing the minimum limit height of the needle of the DIMI under micro-injection mode, different ranges of micro-injection quantity could be designed according to the requirements of the engine, and the control accuracy of injection pulse width (IPW) on micro-injection quantity is higher than on main-injection quantity. Both the hydraulic efficiency of the DIMI under main-injection and micro-injection mode increase with the rail pressure and IPW in the small IPW range, then gradually tend to be saturated with the increase of IPW. As the minimum limit height of the needle increases, the injection quantity and hydraulic efficiency of the DIMI under micro-injection mode increases overall, however, the saturation values of the hydraulic efficiency in micro-injection mode under different needle minimum limit heights are still smaller than those in main-injection mode.

Experimental characterization on injection and spray of coal-derived liquid fuel

Coal-derived liquid fuels (CDLs) are petroleum diesel's (PD) alternatives produced by coal liquefaction. The injection and non-evaporating spray characteristics of CDLs, including diesel from direct coal liquefaction (DDCL), diesel from indirect coal liquefaction (DICL), and their blends (DBCL), were discussed. The high-pressure common rail test bench was used to evaluate the injection delay, injection rate, injection quantity, single injection heat value, and injector inlet pressure. A constant volume chamber along with high-speed camera was used to visualize the spray, then measuring the spray tip penetration distance, spray cone angle, and spray area. Besides, injection tests were conducted using injectors removed from engines that had finished durability tests fueled with DBCL and PD. The results revealed that DDCL had shorter injection delays and more mass injection quantity than PD, with an injection heat value 7 % higher at a rail pressure of 140 MPa. Regarding the spray, PD had a longer spray tip penetration distance and smaller cone angle than CDLs. On test conditions, the spray Sauter mean diameters of DDCL and DICL were over 30 % less than that of PD. Inferring from the reduction in injection rate and quantity, PD generated more clog in the injector hole than DBCL.

Optimization of NOX emissions of a CRDI DIESEL engine using CMA-ES method

Engine calibration is the tuning of embedded parameters in the engine control unit (ECU) software to improve vehicle characteristics and meet legal requirements. Due to the stricter emission limits and rising customer expectations, current ECU software may include variables up to 30,000, which require very much time for engine calibration development. For this reason, automotive manufacturers continuously develop mathematical-based optimization methods to find optimum operating conditions for the engines. This study aimed to develop an online optimization algorithm to conduct automated dynamometer tests in the calibration development process. A modified covariance matrix adaptation (CMA) algorithm, which is an evolutionary strategy (ES) method belonging to meta-heuristic optimization, was integrated with an automation system for online calibration optimization. Some CMA method parameters such as step size and damping factor were initially revised to achieve the method to function efficiently in online engine calibration. Optimization was conducted at three different operating points of a 2-liter common rail direct injection (CRDI) diesel engine, where NOx emission mainly impacts the New European Driving Cycle (NEDC) results. The main injection timing, rail pressure, pilot injection quantity and timing, manifold pressure, and mass air flow were controlled in the optimization process. Optimization targets were determined according to the NOx-PM Pareto curve for each operating point. Covariance matrix adaptation was used to generate Pareto curves. Sixty-five measurements were taken for each operating point in the optimization process. Once optimization targets were determined, optimization occurred at each operating point. A total NOx emission reduction of 3.8% was obtained in the NEDC test, while fuel consumption and PM remained almost the same at steady-state operating points. The modified CMA-ES algorithm is expected to be an efficient method for online calibration optimization.

Evaluation of NOx and PN Emission in Relation to Actuator Control.

This study aimed to investigate the interrelationships between key harmful emission components, nitrogen oxides (NOx), and particulate numbers (PNs) in diesel engine exhaust and the control actuators of diesel engines. This research involved conducting a series of experiments under fixed parameters within an engine brake laboratory environment to elucidate these correlations. The objectives of this study were to conduct a comprehensive review of the relevant emissions technology literature and a comparative assessment of particle measurement methods based on dilution ratios and develop innovative aerosol preparation principles tailored to condensation particle measurement. Additionally, this research involved designing and implementing an aerosol preparation unit based on the newly developed principles, along with the creation of test cell control programs using the AVL PUMA Open TST editor interface and Visual Basic. Furthermore, this study was concerned with conducting evaluations of fixed-parameter engine dynamometer tests to explore the functional relationships between the emission of 10/23 nm particles, NOx emissions, common rail pressure variations, and exhaust gas recirculation levels. This study aimed to enhance the understanding of diesel engine emissions dynamics and contribute valuable insights for developing more efficient and environmentally friendly engine control strategies.

Study on fuel injection stability improvement in marine low-speed dual-fuel engines

Pressure waves within the fuel injection system exert a significant influence on the fuel injection process. This study investigated the impact of pressure waves on injection quantity stability. To quantify the influence of pressure waves on injection quantity stability, the relative standard deviation (RSD) was introduced as a metric. Through computational analysis under various operating conditions, the following results were obtained: when the target rail pressure is constant, the RSD tends to diminish as the injection quantity increases. The elevated RSDs observed during small injection quantities are predominantly attributed to the short power-on period of the solenoid valve. Subsequently, parameter optimization and structural improvements were carried out on the injector to address this problem. The results indicate that optimizing structural parameters alone has a limited effect on reducing RSD. However, by adding a block in the control chamber above the needle to improve the structural layout of the injector, the maximum RSD has been reduced from 21.08% to 4.58% under the action of pressure waves caused by fuel injection, and from 29.24% to 6.67% under the action of given random high-frequency pressure waves. The proposed improvement idea for existing injectors enhances injection stability across the entire operating condition range, thereby improving fuel utilization efficiency.

Diesel direct injection and EGR optimization for a syngas-diesel dual-fuel generator operating at constant load

Diesel generators are widely used to produce electricity and heat in remote communities. However, their use contributes to harmful pollutant and greenhouse gas (GHG) emissions, negatively impacting the environment and public health. Syngas, which is a sustainable fuel, can play an important role in the transition from petroleum to renewable fuels. When used in dual-fuel diesel engines, it can contribute to reducing GHG emissions and the cost of transporting diesel, especially for rural and remote communities. This study investigates the effects of optimizing the diesel direct injection (DI) and exhaust gas recirculation (EGR) strategies on the combustion and emission performance of a syngas-diesel dual-fuel generator at constant load. The experiments were conducted using a 30-kW generator with a four-stroke, four-cylinder, turbocharged, and electronically controlled direct-injection diesel engine. The intake manifold of the engine was modified to allow introducing syngas upstream of the turbocharger. The syngas was simulated using individually controlled flow rates of hydrogen (H2), carbon monoxide (CO), carbon dioxide (CO2), and nitrogen (N2). The syngas flow rate was adjusted to replace 40% of the energy provided by diesel fuel while optimizing the diesel DI parameters such as the pilot injection timing, main injection timing and diesel direct injection rail pressure, as well as the EGR rate. The findings of this study reveal that optimizing diesel injection strategy and appropriately raising the EGR rate have a positive impact on the engine performance and emissions.

Model construction and multi-objective performance optimization of a biodiesel-diesel dual-fuel engine based on CNN-GRU

To tackle the challenges of low efficiency and excessive NOx emissions in biodiesel-diesel dual-fuel engines, this paper presents an optimization method using the Pareto-multiple objective snake optimizer (Pareto-MOSO) to drive a convolutional neural network-gated recurrent unit (CNN-GRU). In the Pareto-MOSO, brake specific fuel consumption (BSFC), NOx, Soot, and CO are optimized by changing the engine control parameters, including injection timing (Tinject), engine speed (n), biodiesel blending ratio, torque (Ttorque), exhaust gas recirculation (EGR rate), intake pressure (Pin), and rail pressure (Prail). The experiment generates training data for CNN-GRU and verifies the accuracy of the Pareto-MOSO optimization results. The findings suggest that the optimized engine exhibits a balanced correlation between economy and emissions under propulsion characteristics. Furthermore, the NOx emissions are all in accordance with the IMO Tier III emission regulations. Under the rated condition, Scheme 2 demonstrates a significant reduction of 76.57 % in NOx emissions. However, this optimization has resulted in a 1.63 % increase in BSFC compared to its pre-optimized state. Therefore, the adoption of suitable control strategies proves advantageous in addressing the trade-off between economy and emissions of engines.

Experimental study on diesel spray flame and wall heat transfer of two-dimensional combustion chamber: effect of common rail pressure

Reducing the heat transfer occurring during the spray combustion of diesel engines remains a challenging task. This study investigated the spray flame behaviour, wall heat flux, and heat transfer phenomena of diesel engines at varying common rail pressures. A rapid compression and expansion machine (RCEM) was employed to simulate a single cycle of diesel spray combustion using split injection sprays. The two-dimensional (2D) stepped piston cavity is a uniquely shaped model used to describe the spray flame behaviour in the combustion chamber. To investigate the heat transfer phenomena, we installed wall heat flux sensors in the cylinder and cavity side. The results indicated that higher common rail pressures increased the peak value of the wall heat flux and reduced the combustion duration and the luminous flame. The higher common rail pressure led to an increase in spray velocity, thereby enhancing the turbulence level. This increase in turbulence to higher peak value of the wall heat flux. The highest peak value of the wall heat flux was reached by the cylinder head owing to the intense combustion region, followed by the cavity bottom owing to the highest flame temperature occurring around this location. Additionally, the heat transfer phenomena in diesel engines were successfully represented by local Nu-Re correlations. Our results contribute to the discussion on heat transfer phenomena that influence the thermal efficiency of diesel combustion engines.

Real-time prediction of fuel consumption and emissions based on deep autoencoding support vector regression for cylinder pressure-based feedback control of marine diesel engines

Predictive models serving as virtual sensors for online optimization and feedback control of diesel engines is gaining increasing attention. However, existing prediction models fall short in simultaneously achieving high prediction accuracy and fast computational speed. In this paper, a novel machine learning algorithm called deep autoencoding support vector regression (DASVR) was proposed, which combines the powerful non-linear feature extraction capability of artificial neural network (ANN) with the good adaptability of support vector regression (SVR) to low-dimensional input spaces. ANN-based autoencoder is firstly employed to extract features from the original high-dimensional input space, forming a low-dimensional latent variable space. SVR is then employed to perform non-linear mapping between latent variables and target output variables. Experiments were conducted on a 16-cylinder marine diesel engine under different load, rail pressure, and injection timing conditions. Prediction models for fuel consumption, NOx, PM, HC, and PM emissions were established based on experimental data and DASVR algorithm. The maximum error of DASVR-based models for the five desired output variables is less than 3.8 % under different operating conditions. DAVSR-based predictive models outperform conventional ANN-based and SVR-based models in terms of both prediction accuracy and real-time capability, and can theoretically meet the real-time requirement below 3000 r/min.

Investigations on the effects of injection parameters and EGR in a glow plug assisted methanol fueled Hot Surface Ignition (HSI) Engine

Methanol can be produced from renewable sources and is also clean burning. Hence it is an ideal alternative fuel for transportation applications. However, its low cetane number prevents its direct application in compression ignition (CI) engines. One of the promising but not widely explored methods is to use a hot surface for its ignition in CI engines at normal compression ratios. In this work a turbocharged automotive common rail diesel engine was modified to operate in the hot surface ignition (HSI) mode with methanol as the sole fuel with 3% by mass of lubricity and corrosion inhibiting additive. Initially, a single pulse injection (SPI) strategy was employed at different injection timings at a BMEP of 8 bar. Subsequently a double pulse injection (DPI) strategy was employed and the effects of gap between the injection pulses, injection timing and injection pulse width share among the two pulses were studied. The HSI mode of neat methanol performed with comparable brake thermal efficiency (BTE), reduced combustion rates and hence low NOx emission levels with respect to diesel operation when the DPI mode was employed with almost equal pulse width share. Engine performance was better at rail pressures of around 800 bar. Hot EGR of up to 8% was beneficial as it reduced the engine-out NOx without affecting the BTE. The engine was operated at different BMEPs in the range of 4–10 bar and compared with the baseline diesel operation. The BTE was similar to the baseline diesel engine at all loads. Engine-out NOx was lower than diesel operation by 23.6%–61.5% while near zero smoke levels and similar CO and THC emissions (after the DOC) were observed. Though slipped methanol and formaldehyde were the significant unregulated emissions, they were reduced to very low levels after the DOC.

A Multiple Attention Convolutional Neural Networks for Diesel Engine Fault Diagnosis.

Fault diagnosis can improve the safety and reliability of diesel engines. An end-to-end method based on a multi-attention convolutional neural network (MACNN) is proposed for accurate and efficient diesel engine fault diagnosis. By optimizing the arrangement and kernel size of the channel and spatial attention modules, the feature extraction capability is improved, and an improved convolutional block attention module (ICBAM) is obtained. Vibration signal features are acquired using a feature extraction model alternating between the convolutional neural network (CNN) and ICBAM. The feature map is recombined to reconstruct the sequence order information. Next, the self-attention mechanism (SAM) is applied to learn the recombined sequence features directly. A Swish activation function is introduced to solve "Dead ReLU" and improve the accuracy. A dynamic learning rate curve is designed to improve the convergence ability of the model. The diesel engine fault simulation experiment is carried out to simulate three kinds of fault types (abnormal valve clearance, abnormal rail pressure, and insufficient fuel supply), and each kind of fault varies in different degrees. The comparison results show that the accuracy of MACNN on the eight-class fault dataset at different speeds is more than 97%. The testing time of the MACNN is much less than the machine running time (for one work cycle). Therefore, the proposed end-to-end fault diagnosis method has a good application prospect.

Real-time estimation of fuel injection rate and injection volume in high-pressure common rail systems

The injection rate and injection volume are essential parameters for the combustion process, which greatly affect the engine efficiency and emission performance. However, at the current time the injection information cannot be obtained in real time during the actual operation of engine. This paper presents a novel real-time estimation method for the injection rate and injection volume based on the measurable rail pressure. A comprehensive dynamic model is derived by considering both the effect of fuel injection and supply process on the pressure fluctuation. Then a linear time-varying state space model is constructed by choosing three appropriate state variables. On this basis, considering the measurement noise and model uncertainty, a Kalman filter-based estimation method of the injection information is investigated. And the noise covariance matrix Q is optimally designed to adapt to a wide range of operating conditions. The proposed estimation method is validated on the different conditions, and the results show the injection rate estimation errors are within 4.5 %, the injection volume estimation errors are within 4 %. And on the situation with overlap of injection and supply process, the injection rate and injection volume estimation errors are all within 4.5 %.

Optical study on a heavy-duty natural gas dual-fuel engine applying POMDME as pilot fuel

In this study, a fully optically accessible single-cylinder research engine is the basis for the visualization and generation of extensive knowledge about the in-cylinder processes of mixture formation, ignition, and combustion of alternative fuels for the dual-fuel combustion process. POMDME substitutes the fossil pilot fuel as a drop-in, non-sooting alternative to widely eliminate the NOx-PM tradeoff. Furthermore, an optimized ignition behavior, increased degrees of freedom in combustion phasing, and the pilot’s energy content are expected. The flame luminosity transmitted via an optical piston was split in the optical path to record the natural flame luminosity simultaneously with an RGB high-speed camera. The second channel consisted of OH chemiluminescence recording, isolated by a bandpass filter via an intensified monochrome high-speed camera. To investigate the combustion process spectrally, spatially, and temporally resolved in more detail, selected operating points were re-recorded via a high-speed imaging spectrograph. POMDME is benchmarked against regular diesel oil, according to EN590. Synthetic natural gas is applied as the primary gaseous fuel. Experimental sweeps along the overall pilot’s energy content (2%, 5%, 10%), injection pressure (500–1600 bar), and start of energizing (5–55 CAD bFTDC) are carried out. The given conditions result in decreased liquid-penetration length between 25% and 30% for the oxygenate, larger for earlier SOE and higher dilution. The lift-off length is nearer the liquid penetration length, increasing for higher rail pressures. The light-based ignition delay for EN590 is enlarged by 0.8 CAD after adding methane, while the oxygenate is not visibly retarded. Without methane, the oxygenate preceded EN590 by 0.6 CAD. The temporal and spatial position and extent of premixed, diffusive, and OH*, change significantly. RCCI operation at practically relevant 18.4 bar IMEP is demonstrated, highlighting the influence of the start of energizing variation with 51% decreased burn duration in the first half of combustion.

On convection vive in mixing-controlled combustion with thermal barrier coatings

Thermal barrier coatings (TBCs) could improve the efficiency of internal combustion engines by reducing heat losses. TBC modeling has demonstrated efficiency gains at all loads in compression ignition, including in gasoline compression ignition (GCI). However, after GCI testing of 13 coated pistons of various materials, thicknesses, and surface preparations in this work, a clear trend was observed: TBCs result in an efficiency gain at 6 bar IMEPn (low load) and an efficiency penalty at 15 bar IMEPn (high load). This can be explained by “convective vive”, which was originally presented by Woschni for engines with TBCs. Convection vive refers to a reduction in the quench distance of a reacting flame when the quenching surface temperature is elevated, resulting in an increased heat transfer coefficient and heat transfer rate despite the lower temperature difference between the gas and the wall. Although this work is unable to provide direct experimental evidence for convection vive, several experiments were performed to rule out alternate theories including differences in heat release rate, radiation heat transfer, combustion chamber deposits, and surface catalytic effects. Experiments also showed that at 6 bar IMEPn, injection pressure did not impact the performance of the TBC compared to the metal baseline, but at 15 bar IMEPn, the efficiency penalty increased with rail pressure. These results provide indirect evidence of convection vive: as the surface temperature of the TBC increases with load past a threshold, the quench distance decreases to the point where exothermic reactions can occur in the boundary layer, which raises the convective heat transfer coefficient. This implies that in mixing controlled combustion systems, the TBC should not be present on combustion chamber surfaces that experience high fuel-wall interaction during combustion.

A Vibration Analysis for the Evaluation of Fuel Rail Pressure and Mass Air Flow Sensors on a Diesel Engine: Strategies for Predictive Maintenance.

This research focuses on the analysis of vibration of a compression ignition engine (CIE), specifically examining potential failures in the Fuel Rail Pressure (FRP) and Mass Air Flow (MAF) sensors, which are critical to combustion control. In line with current trends in mechanical system condition monitoring, we are incorporating information from these sensors to monitor engine health. This research proposes a method to validate the correct functioning of these sensors by analysing vibration signals from the engine. The effectiveness of the proposal is confirmed using real data from a Common Rail Direct Injection (CRDi) engine. Simulations using a GT 508 pressure simulator mimic FRP sensor failures and an adjustable potentiometer manipulates the MAF sensor signal. Vibration data from the engine are processed in MATLAB using frequency domain techniques to investigate the vibration response. The results show that the proposal provides a basis for an efficient predictive maintenance strategy for the MEC engine. The early detection of FRP and MAF sensor problems through a vibration analysis improves engine performance and reliability, minimizing downtime and repair costs. This research contributes to the advancement of monitoring and diagnostic techniques in mechanical engines, thereby improving their efficiency and durability.

The Research and Development of a Jet Disturbance Combustion System for Heavy-Duty Diesel Engines

Herein, a diesel engine jet disturbance combustion system was proposed to achieve efficient and clean combustion under heavy load conditions in heavy-duty diesel engines. The key components of the combustion system were designed, and a research platform was constructed. Focusing on the internal combustion conditions of the disturbance chamber and the developmental path of high-speed jets, the design and comprehensive optimization of the jet disturbance combustion system were carried out. Following optimization, the peak internal heat release rate increased from 86 J/deg to 269 J/deg, and the cumulative heat release increased by 112 J, significantly enhancing the energy of the disturbance chamber jet. Then, considering combustion optimization and the heat transfer loss from the piston, it was determined that the optimal configuration for the disturbance chamber jet channel angles was 60 deg inter-channel angle and 10 deg channel incidence angle. This configuration allowed the disturbance chamber jet to precisely disturb the concentrated mixture area in the middle and late stages of combustion. The intervention of the disturbance chamber jet provided sufficient energy for the fuel–air mixing process and complicated the gas flow state in the main combustion chamber. Despite its low-momentum density, the residual mixture in the cylinder maintained a high mixing rate after the end of the fuel injection process. Single-cylinder engine test results showed that a diesel engine using this jet disturbance system and a 180 MPa common rail pressure fuel system achieved 52.12% thermal efficiency.

Research on pressure wave decoupling method for the nozzle of common rail electronically controlled injector based on water hammer theory

The pressure fluctuation in nozzle of the common rail injector directly affects the stability of fuel injection. As the pressure fluctuation often the result of coaction of multiple factors, it is difficult to carry out in-depth research. To reveal the mechanism of pressure fluctuation of common rail injector nozzle, based on the verified AMESim simulation model of the injector, the decoupling method of pressure wave in delivery chamber of the injector was investigated by applying the water hammer theory. The water hammer pressure in delivery chamber was divided into four stages, and pressure waves caused by the needle valve opening can be decoupled from that caused by the needle valve closing. In the range of 80–180 MPa rail pressure, both the opening and closing processes of the needle valve are direct water hammer phenomena. It is found that the water hammer pressure of the delivery chamber caused by fuel injection mainly consists of three pressure waves through a series of analysis and simplification. The results show that, all the pressures obtained by the superposition of three pressure waves under different working conditions are in good agreement with the simulated water hammer pressures.

Integrated optimization of dedicated engine and energy management strategy for the plug-in hybrid commercial vehicle at high altitude

To improve fuel efficiency and reduce pollutant emissions of plug-in hybrid commercial vehicles (PHCVs) at high altitude, an integrated optimization of dedicated engine of PHCV (DEP) and energy management strategy (EMS) is performed. Firstly, the physical model of DEP is established using experimental data. Its empirical model is developed through machine learning with samples generated by the physical model. Subsequently, a hybrid model-based successive approximation method is proposed to optimize various combinations of control parameters including fuel injection timing, rail pressure, VGT opening and EGR rate, aiming at reducing brake specific fuel consumption (BSFC) and NOx within the major working zone of DEP. This optimized DEP is then integrated into the PHCV model to collectively optimize EMS at this challenging altitude. Results demonstrate that this method considerably reduces optimization time without compromising model accuracy. Notably, at 4000 m altitude and under the CHTC-C driving cycle, overall BSFC reduces with a minimum of 194.27 g/(kW·h), most brake specific NOx values remain under 7.5 g/(kW·h), and optimal working range broadens. With integrated optimization, the DEP predominantly works in low-fuel consumption and low-emission zone. Consequently, the fuel economy of PHCV improves by 30.03 %, while NOx and CO2 emissions decrease by 35.88 % and 18.05 %, respectively.

Flow analysis of a control ball valve in a common rail fuel injector

The electronic control common rail fuel injection system is one of the key technologies being used in modern diesel engines to improve the engine performance. A numerical simulation was conducted to study the characteristics of the fuel flow around the ball valve in the common rail fuel injector. The lift of the control ball valve and static pressure of the flow field around the control ball valve were measured respectively. The simulation was performed with the measurements as boundary conditions such that the flow characteristics can be correlated with the valve lift and the pressure upstream of the ball valve. Simulation results showed that during the valve opening and closing, a high pressure area appeared below the ball valve, while cavitation appeared in the area around the control ball valve. Specifically, the cavitation mainly appeared around the sealing circle, and its upstream area and the conical surface from the entrance to a certain distance downstream. The flow throttling happened at the outlet orifice under the steady-state condition when the valve was at the maximum opening position. The cavitation around the control ball valve was more serious under higher rail pressure conditions. The formation and development of the cavitation was found to be depending on the lift position of the ball valve and pressure of the flow around the ball valve during the valve opening and valve closing. Higher value of void fraction appeared in the flow when the lift of the ball valve was at a larger opening position. It was found that cavitation around the ball valve will affect the consistency and stability of the fuel flow. And cavitation erosion found at the valve seat from a simplified durability test appeared to be close to the place where cavitation appeared from simulation. Therefore, it is suggested that simulation work can be used to examine if cavitation occurs in the flow path of the control ball valve inside the injector in design phase and make necessary changes on the design to prevent the cavitation and the resulting damages to the control ball valve in the injector.

Influence of dwell time on the hydraulic behaviour utilizing multiple injection strategies and a piezoelectric diesel injector

The electric dwell time is defined as the duration between two electric pulse signals. It is a crucial parameter when multiple injection strategies are employed. The influence of electric dwell time on the hydraulic behaviour utilizing pilot injection strategy, split injection strategy, post injection strategy and a commercial piezoelectric diesel injector has been analysed experimentally. To do so, a sweep of electric dwell time from 1.15 ms up to 3 ms in all multiple injection strategies using rail pressures of 80, 100 and 120 MPa, and a back pressure of 5 MPa was performed. A fuel mass of 110 mg was injected in all cases analysed employing operating conditions defined from the characteristics curves of injected mass. The hydraulic behaviour was characterized through to measure the first and second hydraulic delay at opening and closing injector, the pressure oscillations generated during the first injection event, and injected fuel mass during second injection event in an injection discharge curve indicator, which is based on the Bosch tube method. In summary, the paper concludes that the hydraulic dwell time depends on the injected mass during the first injection event, and the dynamic response of injector. Moreover, a short electric dwell time causes an increase of injected fuel mass during second injection event, which can be attributed to combine two effects provoked by overlapping the first and second mass flow rate signals, namely, a reduction in the hydraulic delay at opening injector, and an increase in the hydraulic delay at closing injector. Finally, the present research provides information which can be employed to optimization the modulation of injection rate in a diesel engine.