Cylinder Head Research Articles

A feature and optimized RRT algorithm-based assembly path planning method of complex products

Currently, manufacturing enterprises lack strict regulations and plans for complex products. The actual assembly path mainly relies on technicians’ experience, leading to an unreasonable assembly path for each part at the workstation, an unreasonable transportation path across the workstation, and the problem of mutual interference between parts. To solve these problems, this paper studies the assembly path planning technology of complex products based on the basic geometric features and assembly sequence information. The complexity of assembly path planning is reduced by converting the assembly problem into a disassembly problem. The disassembly direction and distance of each part are determined based on the geometric feature type of each mating face, and the rapid disassembly of the assembly body is achieved. The Rapidly-exploring Random Trees (RRT) algorithm is optimized by target-tendency and double random tree strategy, and the optimal assembly path of each component is quickly generated by combining the path optimization method and interference checking method. Finally, the effectiveness of the proposed method and the superiority of the path planning algorithm are verified using the cylinder head of a Marine diesel engine (MDE) as a case study.

A computational parametric study of ducted fuel injection implementation in a heavy-duty diesel engine

Experiments have shown that ducted fuel injection (DFI) effectively reduces soot emissions from direct-injection diesel engines. Although many computational studies have evaluated DFI’s spray development and soot reduction mechanisms in constant volume chambers, only limited computational work on internal combustion engines exists. The DFI duct assembly changes the engine’s in-cylinder flow, spray, and combustion development. Therefore, current production engine designs might not be optimal for achieving the best engine performance with DFI. This work conducted an extensive numerical study to evaluate how parameter changes affect DFI performance. The parameters include swirl ratio, piston geometry, compression ratio (CR), number of injector orifices, split injection strategy, and exhaust gas recirculation (EGR) in a heavy-duty diesel engine utilizing DFI. The combustion and soot emission data from the Sandia compression ignition optical research engine were used for model validation. Simulations showed that an increased swirl ratio resulted in more intense jet flame-piston interaction, slowing down the combustion heat release during the late combustion stage and leading to lower indicated thermal efficiency (ITE) due to higher exhaust losses. A piston-bowl design with a reentrant inner piston edge yielded the highest thermal efficiency, due to the reduced cylinder head heat transfer loss. Additional injector orifices led to higher efficiency owing to a more advanced combustion phasing. Nevertheless, the maximum pressure rise rate (MPRR) and oxides of nitrogen (NOx) emissions also increased with the number of injector orifices due to more rapid heat release and higher combustion temperature. Implementation of a split injection strategy combined with a higher EGR rate effectively inhibited the excessive MPRR and NOx formation. In general, the study concluded that DFI is not sensitive to most parameter changes but will benefit from future parameter optimization.

Real-time prediction for temperature distribution on the cylinder head of dual-fuel engines via a novel deep learning framework

The mixture of dual fuels causes a complex in-cylinder combustion reaction for dual-fuel engines, which may result in an excessively high thermal load for the cylinder head. Whereafter, the cylinder head is more prone to failures such as thermal fatigue. Considering that temperature distribution on the fire-contact surface of the cylinder head is an important indicator characterizing the thermal load of the cylinder head, with the online pressure sensor data, a real-time prediction methodology based on a novel deep learning framework (UR-CNN) is proposed in this work to predict temperature distribution on the cylinder head. Therein, the feature information contained in the operating parameters of dual-fuel engines is considered by UR-CNN while establishing the relationship between the temperature distribution and pressure sensor data, thereby UR-CNN possesses a better generalization performance for new operating conditions. The results in case studies validate the effectiveness and superiority of UR-CNN in the prediction of temperature distribution on the cylinder head. Hence, the proposed method provides a new approach for the real-time prediction of temperature distribution on the cylinder head in engineering applications, which contributes to the real-time evaluation of whether the thermal load of the cylinder head exceeds the threshold specified by design guidelines.

Tensile Strength Prediction of Gray Cast Iron for Cylinder Head Based on Microstructure and Machine Learning

The ultimate tensile strength (UTS) of gray cast iron (GCI) can be affected by numerous parameters due to its complex microstructures. To further understand the UTS of GCI, it is necessary to evaluate the impact of various parameters. Herein, a UTS prediction method based on microstructure features and machine learning (ML) algorithms is proposed. The six regression algorithms, namely, Bayesian Ridge, Linear Regression, Elastic Net Regression, Support Vector Regression, Gradient Boosting Regressor (GBR), and Random Forest Regressor are used to develop the prediction models. The predicted results show that the GBR has the best prediction performance for the predicted UTS and the error bands within 5%. The feature importance indicates that matrix hardness has the greatest effect on the UTS in the ML models.

Investigation on topology-optimized compressor piston by metal additive manufacturing technique: Analytical and numeric computational modeling using finite element analysis in ANSYS

Abstract Air compressors are widely used in factories to power automation systems and store energy. Several studies have been conducted on the performance of reciprocating and screw compressors. Advancements in design and manufacturing techniques, such as generative design and topology optimization, are leading to improved performance and turbomachinery growth. This work presents a methodology to design and manufacture air compressor pistons using topology optimization and metal additive manufacturing. The existing piston is converted to 3D CAD data and topology optimization is conducted to reduce material in stress concentration regions. Thermal and mechanical loads are considered in boundary conditions. The results show reduced material and improved efficiency, which is validated using ANSYS fluent. The optimized 3D model of the piston is too complex for conventional subtractive manufacturing, so laser sintering 3D printing is proposed. Honeycomb pattern infill patterns are used in 3D printing. This investigation is a step toward researching similar methods in other reciprocating compressor components such as cylinder, cylinder head, piston pins, crankshaft, and connecting rods, which will ultimately lead to improved compressor efficiency.

Performance and Emission Analysis of Biodiesel Blends in a Low Heat Rejection Engine with an Antioxidant Additive: An Experimental Study.

The rapid depletion of crude oil and environmental degradation necessitate the search for alternative fuel sources for internal combustion engines. Biodiesel is a promising alternative fuel for compression ignition (CI) engines due to its heat content and combustion properties. Biodiesel blends are used in various vehicles and equipment, such as cars, trucks, buses, off-road vehicles, and oil furnaces. Biodiesel can reduce emissions from CI engines by up to 75% and improve engine durability due to its high lubricity. However, biodiesel has some drawbacks, including a performance reduction and increased nitrogen oxide emissions. Therefore, this study aims to investigate using environmentally available biodiesel in a low-heat rejection engine and an antioxidant additive to enhance the performance and reduce nitrogen oxide emissions. India currently has several biodiesel sources, including mango seed oil, mahua oil, and pongamia oil, which can be effectively utilized in CI engines by adding l-ascorbic acid. The experimental work involves a single-cylinder 4-stroke water-cooled direct injection CI engine with a power output of 5.2 kW. The engine's cylinder head, piston head, and valves are coated with lanthanum oxide using the plasma spray coating technique, with a thickness of 0.5 mm. The coated and uncoated engines are tested with different proportions of mahua oil, mango seed oil, and pongamia oil. The results show that the engine's performance is significantly improved compared to the baseline engine at all loads. Additionally, these biodiesels exhibit a notable reduction in nitrogen oxide emissions when combined with l-ascorbic acid.

MITDCNN: A multi-modal input Transformer-based deep convolutional neural network for misfire signal detection in high-noise diesel engines

The accurate detection of faults in diesel engines is crucial for extending their operational lifespan, ensuring safety, and yielding significant economic and societal benefits. However, existing detection methodologies encounter difficulties in the presence of substantial environmental noise and lack generalizability across various operating conditions. Traditional fault diagnosis models also predominantly rely on single data detection schemes, such as one-dimensional data input for anomaly analysis, which may not account for the inherent correlations and distribution discrepancies within the same data source presented in different formats. To tackle these challenges, we proposed a novel multi-modal input Transformer-based convolutional neural network (MITDCNN) for misfire detection in diesel engines under significant environmental noise and diverse working conditions. We collected vibration signals from engine cylinder heads at different speeds and extracted both one-dimensional amplitude vector features and two-dimensional image properties. These features were input into the multi-modal feature extraction network and subsequently processed and identified by the cross-channel feature fusion detection network. Our fusion module incorporated a dual-dimension spatial and channel attention mechanism to suppress vibration noise interference effectively, so that the network is able to counteract the impact of environmental noise and varying operating conditions on the final detection outcomes. We validated the efficacy of the proposed approach through a curated dataset and benchmark comparisons with the established algorithms. Our results demonstrate that MITDCNN's accuracy and noise robustness are notably superior to other available methods. Across four datasets generated under distinct working conditions, our approach achieves a minimum accuracy of 99.008%, even with a signal-to-noise ratio of −4dB, greatly surpassing other methods.

Production optimization in the automotive industry using check sheet to reduce unscheduled downtime

The study was developed in an automotive industry, due to the increase in unscheduled stops in the cylinder head production line and the lack of information and records. Therefore, the verification sheet was applied as a methodology, as it is a quality tool that aims to evaluate the production inefficiency index, in order to guarantee improvements in the indicators. With the help of indicators and in order to increase productivity and reduce costs and waste, the analysis of stops in the production process was divided into four sectors, namely maintenance activities, tooling problems, preparation and the production process itself. After this analysis, it was necessary to quantify the hours lost over the three months. Therefore, after the study, improvement was achieved in filling out the verification sheet, records and complete and correct information, trained employees in addition to a significant reduction in downtime and a significant increase in production.

Dynamic crushing behaviors and failure of cylindrical lithium-ion batteries subjected to impact loading

The mechanical property and failure prediction play a significant role in engineering applications of lithium-ion batteries (LIBs), but with great difficulties due to their complicated internal structures. This paper mainly focused on dynamic crushing behaviors and internal failure mechanisms of cylindrical LIBs subjected to different impact loadings for the safety assessment and protection design. A series of dynamic experiments were conducted on typical 18650 LIBs using the drop weight impact test system. The force-electric-thermal responses and impact failure modes of the cells with state of charge (SOC) dependence were experimentally explored under different impactor types. The finite element (FE) model was also established to reveal the failure mechanisms of the battery under high-velocity impact, and its accuracy was validated by the comparison between the experimental and corresponding FE results. Furthermore, the dynamic failure mechanisms of cylindrical cells using the stress wave theory were also explored in this work. It was shown that except from impact velocities, there were significant effects of the SOCs and impactor types on dynamic responses and internal failure modes of LIBs. The failure displacement of the cell will decrease with the increase of impact velocity, but it was insensitive under low-velocity crushing. Based on the FE results, the relationships between failure displacement and impact velocity and impactor diameter were established under flat-end cylinder head impacting. This work can provide some references for multi-functional dynamic integrity design and safety assessment of LIBs.

Tribological Examination of Anodized Al-356 for Automotive Use

The A356 alloy is commonly used in the foundry industry to produce high-stressed automotive components, such as motor frames and cylinder heads. The aim of this work was to investigate how the mechanical and tribological properties of this alloy can be improved by applying an anodizing process. The properties of the oxide layer formed by anodizing using oxalic acid at low temperatures were characterized by different analytical and tribological methods. The combination of tribological methods with standard measurement techniques—such as hardness measurement, layer thickness measurement, as well as the analysis of the morphological characteristics—was used to track the layer evolution during wear developments.

Exhaust gas recirculation in a compression-ignition engine with nano coated Al2O3-TiO2 and ethanol fuel

Ethanol is a fuel that is sustainable, made from biomaterials, and oxygenated. It has the potential to lower the amount of particle emissions produced by diesel engines, as well as the amount of CO2 produced during its life cycle. Even though it was indicated by the exhaust gas recirculation (EGR) approach, the pistons, valves, and cylinder heads of the CI engine were coated in a ceramic compound composed of Al2O3 and TiO2. The exhaust gas recirculation (EGR) technology allows for the cooling and redirection of exhaust gas that has been removed from the cylinders of the exhaust system. Following the application of thermal coating to the piston, the performance of the engine's combustion system improved. The elimination of carbon monoxide, hydrocarbons, and smoke is a direct result of the addition of ethanol. According to the findings, there is a decrease in the amount of NOX emissions up to 11.72 g/kWh and 9.49 g/kWh produced by the cooled EGR engine.

Analysis of The Occurrence of Damage To Crane Operations on Board Km. Lotus Ungu

The smooth maintenance and repair of diesel main engines requires complete and adequate equipment. Hoist cranes are equipment used to lift and move engine components that cannot be moved by human labor. With a hoist crane on board, the machinist on board is easier to lift diesel main engine components such as cylinder heads, pistons, and cylinder liners when carrying out maintenance and repairs. To support the process of lifting diesel main engine components during maintenance and repair, the hoist crane must be in good condition. The main point of a good hoist crane is that the hoist crane can lift loads up to 4 tons. The method that the author uses to make this scientific work is to use a qualitative descriptive method. In this scientific work, the instruments used to produce descriptive data are observation, interviews and documentation. Carrying out these steps is expected to find the problems that cause damage to the hoist crane. Hoist crane damage caused by high temperature electromotor can be prevented by performing maintenance according to the planned maintenance system.

Study on different types of car coolant used in Libyan market: additives dropout

In this research, the effect of four types of coolants used in the local market, (namely Abrad, Freezetone, Algabl Green, and Algabl Red), on the rate of additive dropout quantity was studied, and the cylinder block alloy of the Chevrolet Optra engine car was used as the study material, The results of the chemical analysis technique show that the investigated material is Al-Si alloy. The cylinders have a rectangular cross-section. The samples were placed inside a glass container for each type of coolant, three samples were used. A sensitive balance was used with an accuracy of 1/10000 to measure the weight of the samples before testing and their weight after the immersion process for different periods of time to calculate the rate of additive dropout in g/h/cm2. Preliminary results showed that the additives were deposited on the samples surfaces in different quantities. In addition, after cleaning the samples with distilled water and drying them, these deposits remained stuck to the samples. Through the results obtained after weighing, it was found that the Algabl green coolant has the lowest rate of sedimentation. The additive dropout quantity was about 0.00000478 g/hr/cm2, followed by Freezetone with 0.00000713 g/hr/cm2, while the amount of additive dropout with the Abrad type was 0.00002543 g/hr/cm2. The additives dropout causing deteriorating cooling system performance, where deposit the additive on cylinder block wall will reduce the transferred heat generated inside composition chambers, cylinder heads and blocks are highly and dynamically loaded structures that transfer a lot of heat, so the choice of coolant type for engine is very important to ensure that engine is operating properly.

Effect mechanism and quantitative analysis of injector faults on diesel engine performance

The nozzle deterioration, caused by carbon deposition, cavitation erosion, and other reasons, has a great influence on the power performance, emissions, and thermal load of the direct injection (DI) engine. To understand the manifold effects of nozzle fault on engines, a systematic explanation for the diverse fault phenomena and effect mechanism of nozzle abnormality on the engine performance is needed. The joint action of orifice diameter and fuel spread direction on the performance of a double-swirl diesel engine are numerically revealed and decoupled. The results show that the engine power performance is mainly affected by the change of orifice diameter, while the abnormal spray direction has a great influence on the emissions and the piston surface thermal load. Insufficient spray tilt angle leads to a more concentrated fuel distribution because the fuel of the faulty orifice is not effectively channeled and dispersed by the circular ridge, which causes a 15.29% increase in NOx and an 8.73% increase in soot emissions. Spray circumferential offset leads to increased soot, decreased NOx, and slightly decreased power due to asymmetric fuel distribution. Some fuel is directly injected and burned in the clearance between the piston crown and cylinder head due to the abnormal spray direction, which causes the maximum heat flux at the piston crown to be about 1.8 times that under normal state, greatly increasing the possibility of piston damage. In contrast, the spray circumferential offset mainly causes the position change of the thermal load, but not the magnitude change.

Study on Compression Ratio Optimization of M100 Methanol Engine

A turbocharged and intercooled diesel engine was transformed into an ignited M100 methanol engine by adding a spark plug to the cylinder head. A one-dimensional model of the methanol fuel engine was established using the bench test data as the boundary conditions, and the accuracy and accuracy of the model were verified. Methanol has better octane number and explosion resistance than traditional fuels, increasing the compression ratio of the engine will improve the power and fuel efficiency of the methanol engine. Based on the original compression ratio of 12, 8 compression ratio simulation schemes were selected, including 11.4, 11.7, 12, 12.3, 12.6, 12.9, 13.2, 13.5, etc., and the engine performance and the combustion state in the cylinder changed with the compression ratio were analyzed by simulation calculation, and the engine was optimized and improved. The results show that when the engine compression ratio reaches 12.9, the engine performance reaches the optimal value.

Enhancing Ergonomics in Automotive Cylinder Head Manual Lapping: Workstation Assessment and Design

Enhancing Ergonomics in Automotive Cylinder Head Manual Lapping: Workstation Assessment and Design

Improvement of diesel combustion with suppression of mutual fuel spray flame interactions with staggered nozzle hole arrangement and a spatially divided combustion chamber

A combination of a fuel injector with staggered nozzle hole arrangement with a combustion chamber divided into upper and lower layers by placing a lip at the middle of the side wall is proposed to improve diesel combustion with suppression of interactions among fuel spray flames. The fuel injector has twelve alternately arranged spray holes ( ϕ0.09 mm), staggered at two injection angles, 79° and 55° from the central axis of the injector. Two ordinary injectors with eight ( ϕ0.113 mm) and twelve ( ϕ0.092 mm) holes with an injection angle of 78° from the central axis with a conventional re-entrant combustion chamber were also examined as references. The experimental results showed that the improvements in thermal efficiencies and the reduction in smoke emissions can be established over a wide IMEP range with the proposed combination of the staggered nozzle hole injector and the divided combustion chamber. The exhaust loss is reduced with the combination of the injector and the combustion chamber while the cooling loss increases slightly. The rate of heat release from the combination of the injector and the combustion chamber has a more active main combustion and smaller afterburning than conventional systems. The three-dimensional CFD simulations showed that the combination of the injector and the combustion chamber can efficiently suppress the interactions among fuel spray flames at the combustion chamber wall after the impingement of fuel spray flames and also suitably distribute the fuel mixture, resulting in reductions in the afterburning and the smoke emissions. The slight increase in cooling loss with the proposed combination may be due to the increase in contact area of hot burned gas on the cylinder head; further improvements in thermal efficiency can be expected with optimization of the design factors related to the fuel injection and the combustion chamber configuration.

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.

Numerical Study of Different Steady-State Flow Rigs for the Tumble Motion Characterization of a Four-Valve Cylinder Head

It is widely accepted that in-cylinder airflow structure strongly affects the performance and combustion of internal combustion (IC) engines. In order to enhance turbulence levels at the time of combustion, modern spark ignition engines (SI) usually employ a tumbling motion inside the cylinder. The tumble generated during the intake phase is mainly controlled by the cylinder head, inlet valves and ports configuration. The use of steady-state flow rigs is a common method to characterize the tumble generating ability of a given configuration. The purpose of this study is to perform CFD numerical simulations of two widely used tumbling measuring steady-state flow rig configurations, in order to compare and correlate the tumble ratios obtained from each one of them. A typical modern four-valve shallow pentroof cylinder head is considered and the flow is simulated for various inlet valve lifts. The results highlight the mass flow rate and tumble ratio differences between the two configurations.

Review and evaluation of metals and alloy’s compatibility with hydrogen-fueled internal combustion engines

Hydrogen internal combustion engines (H2-ICEs) are being examined primarily owing to their low criteria pollutants and zero carbon dioxide emissions. However, there are many components and systems of a H2-ICE (including, i.e., gaskets, fuel injection system, piston, cylinder head, exhaust manifolds,…) that are exposed to direct or indirect high-pressure and temperature hydrogen that can lead to deterioration and degradation of the materials, in particular rubbers, metals and their alloys. In the present article, the implications on the characteristics of metals and their alloys exposed to a hydrogen atmosphere are examined with reference to the typical materials and respective operating conditions found in H2-ICEs. The effects of direct or indirect exposure of high pressure and low/high-temperature hydrogen on the properties including mechanical properties of metals and their alloys have been explored. Finally, based on the previous review, a critical assessment of their suitability for a safe and reliable operation on H2-ICEs is provided.