Engine Efficiency Research Articles

Electrosynthesis of formate coupled green hydrogen production on the interface of CuMoO4 nanostructures: A novel electrocatalyst for hybrid water electrolysis system

Developing affordable/efficient catalysts for electrolytic co-production of green hydrogen and value-added products is a prime interest. However, efficient electronic structure engineering of transition metal-based catalysts remains challenging. Herein, we develop high-valent capsule-like copper molybdate (c-CMO) via ultrasonication-assisted strategy. XPS, XANES, KPFM, and DFT studies suggest strong Mo-Cu interaction in c-CMO alters its electronic structure, reduces work function, and lowers ∆GH*. In HER, c-CMO/PNF electrode achieved 130 mV@10 mA/cm² with higher MA and TOF than CO/PNF and MO/PNF electrodes and superior methanol-tolerance than Pt/C. MOR investigations suggest c-CMO/PNF requires 1.39 V@10 mA/cm², 0.239 V lower than OER. Qualitative/quantitative 1H NMR confirms impressive HCOO− selectivity with ∼96 % Faradaic efficiency. The assembled hybrid AEM water-electrolyzer (HER+MOR) demonstrates 1 A/cm²@2 V (at 60 °C), outperforming HER+OER (2.25 V). The stability test of HAEMWE modeled/predicted using Time-Series-Analysis reveals statistically significant lags, indicating zero autocorrelation. This study emphasizes the development of efficient TMO based catalyst for HAEMWE.

Numerical Investigation of the Effect of Intake Closing Timing on Flow Field and Combustion Process in an Elliptical Rotary Engine

Abstract The aim of this research is to investigate the effect of intake closing timing (ICT) on the flow field and combustion process in elliptical rotary engines. The model that can accurately describe the working process of the elliptical rotary engine was established, five kinds of ICTs were designed, and the influence of ICT on the flow field and combustion process was studied. The results show that the advance of the ICT can increase the intake mass flowrate and reduce the back flowrate, the volumetric efficiency is 86.1% at a 145-deg crank angle (°CA) before top dead center (BTDC), which is 7.6% higher than 125 °CA BTDC. The advance of the ICT improves the consumption speed, makes the combustion reaction more intense, and shortens the combustion time. When the ICT is 145 °CA BTDC, the crank angle when the burned mass fraction is 90% (CA90) is 19.4 °CA earlier than 125 °CA BTDC, the peak mass of hydroxy in a cylinder is 41.6% higher, and the peak pressure in a cylinder is 25.9% higher. With the advance of the ICT, the pressure and heat release in the cylinder are significantly increased, the peak temperature in the cylinder is increased, the rate of carbon monoxide generation is accelerated, and the mass of nitrogen oxide emission is significantly increased. However, advancing the ICT cannot improve the indicated thermal efficiency of the elliptical rotary engine. This analysis provides a comprehensive understanding of the ICT of elliptical rotary engines.

Assessment of altitude effects based on the consumption behavior of a piston-prop engine by entropy approach

PurposeThe altitude and weather conditions affect directly fuel consumption and engine efficiency of the aircraft engines. The thermo-physical properties of the weather of altitude play a significant role in this process. Unfortunately, engine performance based on altitude conditions also causes waste heat and environmental pollution due to engine entropy generation. However, environmental impact assessment is needed to improve environmental sustainability. This study aimed to analyse the energy and environmental performance of a piston engine based on altitude conditions.Design/methodology/approachThis study is based on the entropy approach, and it aims to assess the environmental impact of the engine. Exergy analysis with together two new indices to evaluate the environmental effects caused by the engine under altitude conditions was used.FindingsThe analysis reveals that the exergy efficiency of the piston engine is 23.9% on average for the three referenced altitudes, while the exergy efficiency difference between altitude boundary conditions is 11%. In addition, the entropy production of the engine is on average 10.55 kW/K. In this case, the environmental pollution potential resulting from the entropy production of the engine is on average 3.29 times higher due to reversible conditions, while the improvement rate was found to be 58%.Originality/valueThis analysis shows that engine efficiency increases as altitude increases. Similarly, it can also be said that the environmental impacts are reduced and the improvement of the engine has opportunities for operational processes. Besides, in the study, some suggestions for motor performance impact analysis were presented.

Enhancing diesel engine efficiency and emission performance through oxygenated and non-oxygenated additives: A comparative study of alcohol and cycloalkane impacts on diesel-biodiesel blends

This study evaluates the impact of renewable fuel additives on diesel engine performance, combustion, and emissions. Safflower seed oil was converted into biodiesel (BD) through transesterification, achieving a 94.12 % conversion yield, verified by spectroscopic analysis. Test fuels were prepared by adding 5 %, 15 %, and 25 % n-pentanol (PE, oxygenated) and cyclohexane (CHx, non-oxygenated) to diesel fuel (DF) and BD. These blends were tested in a single-cylinder diesel engine under varying loads. At maximum load, BSFC values were 0.251 for DF, 0.333 for 25 % PE, and 0.269 kg/kWh for 25 % CHx. BTE values were 32.184 % for DF, 27.028 % for 25 % PE, and 31.147 % for 25 % CHx. The peak in-cylinder pressure and net heat release for the 25 % PE blend, which were the highest among the test fuels, were 58.148 bar and 37.010 J/°CA, respectively. Average NOx emissions were 171 for DF, 135.75 for 25 % PE, and 170.50 ppm for 25 % CHx. CO emissions were 171 for DF, 149.25 for 25 % PE, and 170.25 ppm for 25 % CHx. Smoke opacity values were 0.75 for DF, 0.308 for 25 % PE, and 0.675 m-1 for 25 % CHx. Despite higher costs, CHx offers reduced environmental impact without significantly compromising engine performance.

A 3D CFD-FEA co-simulation study of low thermal effusivity TBCs applied to the piston and valves of an SI engine

When applied on combustion chamber walls, thermal barrier coatings (TBCs) with low thermal effusivity provide a pathway for reducing heat transfer and improving SI engine efficiency. A 3D CFD-1D FEA co-simulation routine was employed to study the effects of a proprietary TBC on SI engine performance under different permutations of coating the piston, exhaust valves, and intake valves. Marginal reductions (<0.1% points) in total heat transfer and improvements to efficiency were observed when all the three components were coated with the proprietary TBC. Two hypothetical TBC materials with ideally low thermal effusivities were formed by modifying the current material properties and their effect on engine performance was similarly studied at three engine loads at the same engine speed. It was found that coating all the three components with the lowest thermal effusivity TBC offers the largest improvements (∼0.5% points) in net fuel conversion efficiency accompanied by largest reduction (∼1.1% points) in total heat transfer, thus establishing expectations from future TBC materials.

Tribological properties under dry and lubricated sliding conditions of TiSiN and AlTiCrN coatings deposited on gray cast iron

In internal combustion engines, the majority of friction losses and wear occur between the cylinder liners and piston rings. Hard coatings applied to cylinder liners can increase the efficiency of internal combustion engines by improving tribological properties. The gray cast iron cylinder liner was coated with TiSiN and AlTiCrN employing the cathodic arc deposition process. The coatings were examined using nanoindentation tests, scratch tests, an optical profilometer, a scanning electron microscope, an X-ray diffractometer, and energy dispersive analysis to assess their hardness, adhesion, and structural characteristics. The reciprocating test was carried out to assess the coatings' wear and friction characteristics under lubricated and dry sliding with a ball at varying normal loads. The hardness of the TiSiN and AlTiCrN coatings was 45 GPa and 18 GPa, respectively. The cohesion strength, adhesion strength, and crack propagation resistance of AlTiCrN coating were approximately 2, 1.3 and 2.5 times higher than those of TiSiN coating, respectively. Both coatings exhibited remarkable wear performance at high normal loads. Under dry sliding conditions at 25 N normal load, the wear rate of AlTiCrN and TiSiN coatings were nearly 33 and 20 times, respectively, lower than the uncoated substrate. Under dry sliding conditions, the TiSiN coating exhibited the lowest wear rate at low normal loads (5 N and 15 N), while the AlTiCrN coating performed best at high normal loads (25 N). In lubricated sliding conditions, the AlTiCrN coating consistently showed the lowest wear rate across all normal loads.

A Comparative Analysis of Friction and Energy Losses in Hydrogen and CNG Fueled Engines: Implications on the Top Compression Ring Design Using Steel, Cast Iron, and Silicon Nitride Materials.

Optimizing the design of the top compression ring holds immense importance in reducing friction across both traditional Internal Combustion (IC) engines and hybrid power systems. This study investigates the impact of alternative fuels, specifically hydrogen and CNG, on the behavior of top piston rings within internal combustion (IC) engines. The goal of this approach is to understand the complex interplay between blow-by, fuel type, material behavior, and their effects on ring friction, energy losses, and resulting ring strength. Two types of IC engines were analyzed, taking into account flow conditions derived from in-cylinder pressures and piston geometry. Following ISO 6622-2:2013 guidelines, thick top compression rings made from varying materials (steel, cast iron, and silicon nitride) were investigated and compared. Through a quasi-static ring model within Computational Fluid Dynamics (CFD), critical tribological parameters such as the minimum film and ring friction were simulated, revealing that lighter hydrogen-powered engines with higher combustion pressures could potentially experience approximately 34.7% greater power losses compared to their heavier CNG counterparts. By delving into the interaction among the fuel delivery system, gas blow-by, and material properties, this study unveils valuable insights into the tribological and structural behavior of the top piston ring conjunction. Notably, the silicon nitride material demonstrates promising strength improvements, while the adoption of Direct Injection (DI) is associated with approximately 10.1% higher energy losses compared to PFI. Such findings carry significant implications for enhancing engine efficiency and promoting sustainable energy utilization.

Particle Acceleration in Relativistic Alfvénic Turbulence

Strong magnetically dominated Alfvénic turbulence is an efficient engine of nonthermal particle acceleration in a relativistic collisionless plasma. We argue that in the limit of strong magnetization, the type of energy distribution attained by accelerated particles depends on the relative strengths of turbulent fluctuations δ B 0 and the guide field B 0. If δ B 0 ≪ B 0, the particle magnetic moments are conserved, and the acceleration is provided by magnetic curvature drifts. Curvature acceleration energizes particles in the direction parallel to the magnetic field lines, resulting in log-normal tails of particle energy distribution functions. Conversely, if δ B 0 ≳ B 0, interactions of energetic particles with intense turbulent structures can scatter particles, creating a population with large pitch angles. In this case, magnetic mirror effects become important, and turbulent acceleration leads to power-law tails of the energy distribution functions.

Feasibility analysis of the veil convection business using value engineering for cost efficiency

The veil business is a business that operates in the veil manufacturing industry. The products produced vary according to consumer demand and the stock produced. This headscarf product has spread to several areas of Aceh, such as Banda Aceh, Lhokseumawe, and Langsa, especially the Bireuen City area, and has collaborated with several Islamic boarding schools. The headcarf models released by this company greatly influence consumer demand. The better the material, model, and quality, the more consumer demand for convection will increase. This research aims to analyze the feasibility of developing a veil convection business using a value engineering method and financial feasibility. The research results were obtained using the analytical hierarchy process method and vacuum engineering. The chosen alternative is model 1, with a weight of 0.53, a square hijab type, standard material, soft colors, and zipper accessories according to consumer demand. And the results of the financial aspect calculations show that the Ita Hijab convection business has a positive NPV of IDR 29,373,042, with a BEP of 480 units. The payback period for investment capital is 5 months. If you look at the payback period calculation with a BCR value > 1, then the veil convection business is said to be worthy of investment

A unified benchmark for deep reinforcement learning-based energy management: Novel training ideas with the unweighted reward

Deep reinforcement learning stands as a powerful force in the realm of intelligent control for hybrid power systems, yet some imperfections persist in the positive progression of learning-based strategies, necessitating the proposal of essential solutions to address these flaws. Firstly, a public and reliable benchmark model for hybrid powertrains and the optimization results of energy management strategies are essential. Hence, two Python-based standard deep reinforcement learning agents and four Simulink-based hybrid powertrains are employed, forming a co-simulation training approach as the reliable solution. Secondly, a detailed analysis from the perspectives of range, magnitude, and importance reveals that the optimization terms in traditional reward functions can mislead the agent during the training process and require cumbersome weight tuning. Accordingly, this paper proposes a novel training idea that combines the rule-based engine start-stop with an unweighted reward tailored for optimizing engine efficiency and facilitating training progress. Finally, a hardware-in-the-loop test is performed, treating the P2 hybrid electric vehicle as the target. The results show that two deep reinforcement learning-based energy management strategies achieved fuel economies of 6.537 L/100 km and 6.330 L/100 km, respectively, and more efficient and reasonable control sequences ensure the working state of the engine as well as the state of charge of batteries.

OIL DUST INDICATOR

An oil dust indicator is a crucial component in maintaining the efficiency and longevity of machinery and engines. It serves the dual purpose of monitoring both oil level and contamination levels, particularly from dust and particulate matter. The indicator typically consists of a sensor, a processor unit, and a display or alert mechanism. The sensor, often a combination of optical and pressure sensors, continuously monitors the oil. clarity and level. When dust or other contaminants accumulate in the oil, the sensor detects changes in clarity and triggers an alert. The processor unit interprets these signals and activates the display or alert mechanism, informing operators of the need for maintenance. In addition to indicating the need for oil replacement or cleaning, advanced oil dust indicators can also provide data on the severity of contamination, allowing for proactive maintenance planning. This capability can significantly reduce downtime and maintenance costs while optimizing the performance and lifespan of machinery and engines. Oil dust indicators find applications in various industries, including automotive, manufacturing, and power generation. They play a vital role in ensuring the smooth operation of critical machinery and equipment, making them indispensable tools for maintenance professionals and operators alike. This study proposes an advanced oil dust indicator that incorporates sensors for total dissolved solids (TDS), color, and pH levels to provide comprehensive monitoring of oil quality. Keywords: oil dust detector can sense dust in oil.

Quantum Heat Engines with Spin‐Chain‐Star Systems

AbstractThis study investigates a theoretical model of a Quantum Otto Cycle (QOC) that utilizes a working fluid spin‐chain‐star model. The system consists of a central atom interacting with multiple Heisenberg spin chains. Employing unitary transformations, the spin‐chain‐star system is transformed into a spin‐star model. The work done and heat transferred for three distinct working fluid configurations: the , , and cases are discussed. The efficiency of the heat engine is examined, and a comparative study between the efficiencies of the three configurations is presented. The study assumes two interaction scenarios for the central atom: either with a single chain (resulting in a two‐qubit system after transformation) or with three Heisenberg chains. The results demonstrate that increasing the ratio between the central atom's frequency in the hot bath and the cold bath leads to an enhancement in positive work performed for the and cases. In the case, the magnitude of this enhancement exhibits a dependence on the system's temperature. The QOC employing the configuration working fluid exhibits superior efficiency compared to the other two configurations. Moreover, increasing the central atom's relative frequency improves efficiency for all three cases.

Optimizing the defect engineering of MnCo2O4 spinel structure through Zn-substitution as a cathode for high-performance Zinc-ion batteries

Zinc-ion batteries are regarded as an effective alternative for energy storage because of their low flammability, affordability, inherent safety, and high theoretical capacity. However, manganese-based materials are limited due to a relatively narrow tunneling pathway, causing low-rate capacity and low life cycle stability. Hence, an effective strategy using defect-engineered crystal structure promoted by Zn-substituted MnCo2O4 to achieve a high-performance ZIB is proposed. The microspheres, assembled with interconnected micro- and nanoflake structures of ZnxMn1-xCo2O4 (with the Zn-substitution of x = 0, 0.2, 0.4, 0.6, and 0.8), are hydrothermally synthesized, followed by calcination, which serves as the cathode for ZIBs. At the optimal Zn0.4Mn0.6Co2O4 cathode, ZIBs battery possesses a superior discharged specific capacity of 660 mAh g-1 at 0.05 A g-1, a high-rate performance (energy density of 260–528 Wh kg−1 at a power density of 800–40 W kg−1), and good capacity retention of 70 mAh g-1 after 800 cycles at 0.2 A g–1. Ex-situ SEM-EDX and XPS results through charge/discharge cycles confirm the high stability and reversibility of Zn0.4Mn0.6Co2O4 in its electron state. Such improved rate capacity and long-life cycles originate from efficient defect engineering using Zn-substitution and oxygen vacancies. These lead to improved ion insertion and Zn2+ transport kinetics, along with enhanced electrical conductivity, resulting in the reversibility reactions of Mn4+/Mn2+ and Co2+/Co3+ upon Zn2+insertion/extraction.

The Role of Smart Materials, Sustainable Engineering Practices, and IoT Integration in Advancing Engineering Solutions

This study explores the role of smart materials, sustainable engineering practices, and Internet of Things (IoT) integration in advancing modern engineering solutions. The primary objective is to qualitatively analyze the literature on how these innovative components contribute to the development of efficient, sustainable, and intelligent engineering systems. The research employs a qualitative literature review methodology, examining a broad range of academic articles, technical reports, and case studies related to smart materials, sustainable engineering, and IoT applications. The literature review methodology involves systematically collecting and analyzing relevant scholarly sources to identify key trends and insights. The study categorizes the literature into major themes, such as the properties and applications of smart materials, the principles and benefits of sustainable engineering, and the impact of IoT integration on engineering processes. By synthesizing findings from diverse sources, the research provides a comprehensive overview of the advancements and challenges associated with these technologies. The findings reveal that smart materials, such as shape-memory alloys, piezoelectric materials, and self-healing composites, offer significant potential for enhancing the functionality and durability of engineering systems. Sustainable engineering practices, including the use of renewable materials and energy-efficient designs, are critical for reducing environmental impact and promoting long-term sustainability. IoT integration enables real-time monitoring, data-driven decision-making, and improved system efficiency, thus transforming traditional engineering approaches.

Computational analysis of ammonia-hydrogen blends in homogeneous charge compression ignition engine operation

Ammonia (NH3) is considered a promising alternative fuel due to its renewable and carbon-free nature. The addition of hydrogen (H2) significantly improves its flammability, making it suitable for use in internal combustion engines. The homogeneous charge compression ignition (HCCI) technique offers a practical solution for high-efficiency NH3-H2 operation, but it is not extensively discussed in existing literature. To enhance the understanding of NH3-H2 HCCI engines, this study employs a zero-dimensional model validated against experimental results to investigate engine efficiency and nitrogen oxides (NOx) emissions. The results indicate that an ammonia-dedicated HCCI mode would misfire at a 22:1 compression ratio and an engine speed of 1500 rpm if the intake pressure and temperature are insufficient. Hydrogen addition can help overcome the misfire issue and reduce the intake pressure and temperature required for combustion initiation. However, higher hydrogen addition ratios decrease thermal efficiency and increase NOx emission levels. In lean NH3-H2 HCCI operation, NOx emissions are primarily driven by fuel-borne mechanisms and peak at an equivalence ratio of around 0.5. A higher hydrogen addition ratio should be avoided as it increases the risk of ringing, thereby reducing the maximum allowable equivalence ratio and engine load. As a result, a moderate hydrogen addition ratio, such as 20 %, is preferable for NH3-H2 HCCI engines. Additionally, an equivalence ratio of approximately 0.3 is optimal, balancing multiple performance indicators such as thermal efficiency, NOx emission levels, and engine operating stability. These findings suggest that the operating range of NH3-H2 HCCI engines is limited, making them more suitable for off-road applications, such as power generation.

Thermal analysis by numerical simulations of a multilayered coating applied on a heavy-duty diesel engine piston

A methodology to numerically study the impact of a thin, multi-layer coating applied on the piston crown surface of an internal combustion engine is proposed. It relies on a loose thermal coupling between 3D-RANS simulations of the combustion chamber and 3D conduction simulations of the piston. The approach allows to characterize the transient thermal behavior of the piston, which is crucial to capture the thermal swing effect of the coating, as well as its potential impact on the combustion, heat transfer and engine efficiency. This methodology is used to simulate the impact of a 200-µm, 3-layer coating, applied on the piston crown surface of a single-cylinder, heavy-duty Diesel engine, for one operating point. No gain in terms of efficiency is observed with the coated piston (the decrease in heat losses through the piston surface due to the coating is counter-balanced by an increase in heat losses through the non-coated cylinder head). However, the methodology proves capable of predicting a coherent thermal behavior of the coated piston (decrease in piston body temperature of 5 K, average bowl surface temperature swing amplitude of 60 K, <5 K temperature swing at the interface between the metallic substrate and the coating) and is able to provide insightful information regarding the impact of coating on volumetric efficiency, heat losses, combustion but also on the coating reliability itself, for a reduced computational cost compared to a fully coupled approach. It can then be employed to evaluate the effect of a coating applied not only on the piston but also on the cylinder head, which would certainly have a more significant impact on the engine efficiency.

Structure-based reshaping of a new ketoreductase from Sphingobacterium siyangense SY1 toward α-haloacetophenones

Ketoreductases play an indispensable role in the asymmetric synthesis of chiral drug intermediates, and an in-depth understanding of their substrate selectivity can improve the efficiency of enzyme engineering. In this endeavor, a new short-chain dehydrogenase/reductase (SDR) SsSDR1 identified from Sphingobacterium siyangense SY1 by gene mining method was successfully cloned and functionally expressed in Escherichia coli. Its activity against halogenated acetophenones has been tested and the results illustrated that SsSDR1-WT exhibits high activity for 3,5-bis(trifluoromethyl)acetophenone (1f), an important precursor in the synthesis of aprepitant. In addition, SsSDR1-WT showed obvious substrate preference for acetophenones without α-halogen substitution compared to their α-halogen analogs. To explore the structural basis of substrate selectivity, the X-ray crystal structures of SsSDR1-WT in its apo form and the complex structure with NAD were resolved. Taking 2-chloro-1-(3, 4-difluorophenyl) ethanone (1i) as the representative α-haloacetophenone, the key sites affecting substrate selectivity of SsSDR1-WT were identified and through the rational remodeling of the cavities C1 and C2 of SsSDR1, an excellent mutant I144A/S153L with significantly improved activity against α-halogenated acetophenones was obtained. The asymmetric catalysis of 1f and 1i was performed at the scale of 50 mL, and the space-time yields (STY) of the two were 1200 and 6000 g/L∙d, respectively. This study not only provides valuable biocatalysts for halogenated acetophenones, but also yields insights into the relationship between the substrate-binding pocket and substrate selectivity.

Perbandingan Efisiensi Bahan Bakar Pada Kendaraan Low MPV Dengan Metode Copras

Low multi-purpose vehicles have become a popular choice in the automotive market due to their combination of ample space and improved fuel efficiency. In the context of increasing environmental awareness and ever-increasing fuel costs, this study aims to compare the fuel efficiency of various low multi-purpose vehicles using the Complex Proportional Assessment (COPRAS) method. The Copras method, as a multi-criteria decision analysis tool, is used to evaluate vehicle alternatives based on a number of predefined criteria. In this study, the main criteria considered include engine efficiency, aerodynamics, vehicle weight, and fuel technology used. The identification of these criteria is important as fuel efficiency is influenced by various complex technical factors. Relevant data was collected for the low multi-purpose vehicles to be evaluated. Once the data was collected, a Copras analysis was conducted to determine the relative ranking of each vehicle based on its fuel efficiency. This method allowed the researcher to identify vehicles that stood out in terms of fuel efficiency. The results of this study are expected to provide valuable insights for both consumers and vehicle manufacturers. Consumers can use this information to make smarter decisions when choosing a vehicle that suits their needs, taking into account the important aspect of fuel efficiency. On the other hand, manufacturers can use these findings to develop more fuel-efficient vehicles, as well as to strengthen their position in an increasingly competitive market. In addition, this study also has significant implications in an environmental context. By choosing more fuel-efficient vehicles, consumers can contribute to the reduction of greenhouse gas emissions and reduce other negative impacts on the environment. As such, this research not only provides economic benefits but also supports efforts to maintain environmental sustainability

Experimental study on combustion instability characteristics in a pre-chamber natural gas engine under lean burn conditions

Pre-chamber jet ignition is a key technology for future high-efficiency natural gas (NG) engines. It can achieve fast and stable combustion through excellent ignition performance. However, there are still some challenges, such as high combustion instability near the lean burn limit and the narrow engine operating range. Therefore, this paper investigates the combustion instability of a pre-chamber NG engine under ultra-diluted conditions by experimental method. At two engine loads, experiments are carried out with different jet ignition intensity schemes to study the effect of jet ignition intensity on the cyclic combustion variations. Then, the combustion instability characteristics of the pre-chamber NG engine are studied by cyclic variation analysis and phase space reconstruction. The results show that with the increase in the jet ignition intensity, the cyclic combustion variations decrease, and the cyclic variation coefficient of the indicated mean effective pressure decreases to below 2%. The lean burn limit of the pre-chamber natural gas engine is extended to an excess air ratio of 2.0. The operation instability of the pre-chamber NG engine is mainly due to cyclic variations in the ignition and combustion process. The nonlinear dynamic analysis shows that the combustion process in the lean burn pre-chamber NG engine behaves with chaotic characteristics under the operating conditions of low jet ignition intensity. As the jet ignition intensity increases, the combustion stability is improved and the cycle-to-cycle variations change from fairly deterministic to more stochastic behavior. The chaotic characteristics of the combustion process become weaker. In conclusion, it is of great importance to generate stable and high ignition intensity jets for reducing combustion instability and improving combustion efficiency in lean burn pre-chamber NG engines.

Modeling electric Vehicle's and improving battery lifetime using AI tools case study: Postal cars

The rapid development in the field of electric vehicles requires a careful evaluation of the design process. The presence of a simulation model of the electric vehicle can effectively detect many faulty areas during the development process without risks. The MATLAB and Simulink environment is considered one of the most important tools used in the simulation process. In this paper, we will present the model of electric car used for transporting postal parcels (postal cars). The model includes simulating the operation of a permanent magnet synchronous electric motor. We will assume that the car is moving according to a driving cycle. The results will show the torque forces required to achieve the required speed. We will further calculate the traction and the resistance forces during the driving cycle and the engine efficiency in addition. Perhaps the most important problem facing electric car designers is calculating the amount of energy consumed from the battery or hydrogen fuel, and this is what was achieved as the result of the simulation process in this research. In the end, use one of the artificial intelligence tools (fuzzy controller) to improve battery life by providing the electric car driver with an alert system that will increase the ability to monitor the battery condition and thus increase battery life. The benefit of this paper emerges in realizing the importance of modeling and using simulation using artificial intelligence in developing the design of the electric car, specially the electric motor and battery size, and thus achieving one of the most important goals of the United Nations of preserving the environment and reducing carbon emissions.