Search Results (1,991)

The heat release rate in internal combustion engines obtained from in-cylinder pressure data is a fundamental method to analyse the combustion characteristics of engines. As the measured in-cylinder pressure is lower than the pressure in the absence of heat loss to the walls, the methodology typically leads to the apparent rate of heat release as the heat loss to the cylinder walls cannot be segregated. Heat loss can then be inferred by reference to the chemical fuel energy expected to be released by the fuel. Typically, in engine thermodynamic analysis, the lower heating value is used to determine the energy released by the fuel. However, in this article, we argue that when detailed comparison with validated combustion modelling was done, it was concluded that the higher heating value is the more appropriate calorific value. In this research, the analysis of heat release rate and its determination using the first law of thermodynamics with constant ratio of specific heats γ and also varying γ is discussed. It was noted that the use of the “3rd term” (term due to the dγ/dϑ) in the heat release rate is advisable as it gives a more reasonable heat loss even in the compression stroke. Full article

With rising global energy demand and the gradual depletion of petroleum-based resources, interest in alternative fuels for internal combustion diesel engines (ICDEs) has increased. In ICDEs, firing-related and mechanical excitations may result in adverse vibration and noise responses. This study examines whether incorporating sour cherry pit pyrolysis oil (SCPO) with n-butanol and 2-ethylhexyl nitrate (2-EHN) may reduce vibration and noise under constant-load, steady-state operating conditions compared with neat diesel (D100). For the experimental tests, five fuel types were prepared: one neat diesel fuel and four blended fuels with a constant diesel fraction of 40% and a fixed 2-ethylhexyl nitrate (2-EHN) content of 5%, while the SCPO and n-butanol fractions were varied (D40/SCPO0/B55/2-EHN5, D40/SCPO5/B50/2-EHN5, D40/SCPO10/B45/2-EHN5, and D40/SCPO15/B40/2-EHN5). Experiments were performed using a single-cylinder ICDE at a fixed load of 10 Nm under steady-state conditions at engine speeds of 1500, 1800, 2400, 3000, and 3600 rpm. For each operating condition, vibration and noise data were recorded over a 10.4 s window. Experimental findings indicate that D40/SCPO10/B45/2-EHN5 yielded the lowest mean overall RMS vibration, with a 37.5% reduction relative to neat diesel (D100), and the lowest equivalent sound level (LAeq) among the tested fuels. Under the investigated steady-state constant-load conditions, the D40/SCPO10/B45/2-EHN5 fuel blend demonstrates the potential to achieve lower measured vibration and noise levels than neat diesel. Full article

Transport decarbonization and electrification are the current concepts of sustainable logistics. The European Green Deal aims to remove internal combustion engine vehicles from the roads and make the continent climate neutral by 2050. However, there is much debate about the means to achieve this goal and the rivalry between diesel and electric vehicles. This article aims to analyze the impact of the energy efficiency of diesel and electric vehicles on the sustainability of urban logistics and the benefits for the average transport user—the driver. The study uses scientific literature, statistical, comparative, SWOT analysis methods, and experimental research methods. In addition, a qualitative study was conducted with the help of experts, and the problematic relationships between diesel and electric vehicles were analyzed. The results of the study showed that even an old diesel vehicle is not inferior to a new electric vehicle in terms of energy efficiency and operation for the average user but does not meet the theoretical sustainability standards for urban logistics. Therefore, broader apolitical discussion and practical experiments are needed to ensure that the results of future research are unbiased. Full article

In this article operational problems associated with the use of landfill biogas as an alternative fuel in cogeneration systems, with particular emphasis on micro-installations based on the Perkins 4008-30 TRS2 combustion engine are presented. Such installations are commonly used in cogeneration systems, whose importance in obtaining stable electric and thermal energy is growing, especially when taking into account the additional reduction in environmental impact through biogas combustion. Reducing emissions of biogas, which consists of approximately 60% methane and approximately 35% carbon dioxide, directly reduces emissions of a greenhouse gas (GHG) with a high global warming potential (GWP). In this study the characteristics of the landfill, the biogas purification system, the measurement system and the energy balance of the entire process, biogas production → electric energy → thermal energy, are presented and the importance of this type of installation in the context of a low-carbon economy is discussed. Attention is also drawn to the operational problems of the cogeneration system, which led to its failure, requiring comprehensive repairs of the internal combustion engine. Full article

A new procedure for diagnosing damage to the fuel injection system of marine engines, along with vibration acceleration signal symptoms, is explored with a related built, developed, and tested measuring system. This work fills an important gap given the current lack of a scientific solution to this problem. A vibration acceleration signal sensor, mounted on a holder elaborated on by the authors, is positioned on the injection pipe between the injection pump and the injector. The output signals from the sensor are sent to an acquisition and analysis system, which is used for processing the signals in the time, amplitude, frequency, and time–frequency domains. Experimental choices, using multiple parameters for a given signal analysis field, are based on the location of the optimal sensor, the direction of the sensor mounting, and the selection of a cumulative diagnostic symptom. The vibration acceleration signals recorded along the injection pipe are found to have the strongest magnitude. This article compares diagnostic values from these signals with previously determined upper and lower limits. As a result, the tested fuel injection system is classified as either able or disabled, using unparalleled tolerance ranges given for both the upper and lower limits. The values of the limits are determined based on the average value for an ability state plus or minus three times the standard error of this mean, which has not been reported in the literature previously. Multiple regression models are developed that relate identified symptoms to the state features of the fuel injection system. In addition, artificial neural networks and machine learning are used to detect developing damage. The probability of correctly classifying the states of the diagnostic parameters is 0.467, alongside a diagnostic accuracy of ≤±4%, with the network correctly classifying the state when the testing accuracy is at least 70.0%. Full article

The automotive sector is currently undergoing a rapid and complex transition from classic internal combustion engines to hybrid or fully electric propulsion systems, at the core of which is the battery pack. Currently, the battery packs of almost all electric vehicles on the road consist of lithium-ion cells. The thermal management of these cells represents a complex and fundamental challenge, essential not only to ensure optimal vehicle performance but also to guarantee passenger safety. Therefore, this paper examines and compares four main systems used for battery thermal management, highlighting their strengths, weaknesses, and overall effectiveness. First, a standard module comprising 21700 cylindrical cells, representative of automotive applications, is designed. Subsequently, computational fluid dynamics (CFD) thermal analyses of this module are performed to evaluate four different cooling methods: forced air cooling, bottom cold plate cooling, liquid tube cooling, and immersion cooling combined with tab cooling. Finally, an experimental validation is conducted by testing these systems on a physical module, which is subjected to the same electrical discharge profile simulated in the CFD analyses, to verify the effectiveness of the four considered methods. Full article

Engine oil degradation critically influences the performance, efficiency, and longevity of internal combustion engines. Conventional mileage or time-based replacement schedules often result in premature oil changes or delayed servicing, both of which compromise engine health and increase costs. This review examines recent advances in real-time oil condition monitoring and evaluates the feasibility of a low-cost microcontroller-based system that integrates physical sensors with machine learning models for continuous on-board oil health assessment. Drawing on established techniques from industrial lubrication monitoring, we propose an experimental framework that leverages electrical engineering principles, including sensor interface, analog front-end design, signal acquisition, and embedded AI deployment to enable accurate, affordable, and scalable oil health diagnostics. The review highlights opportunities for innovation in embedded systems and electrical engineering design, positioning AI-driven monitoring as a practical solution for predictive automotive maintenance. Full article

Artificial neural networks (ANNs) are widely used to approximate nonlinear mappings, yet their ability to capture thermodynamic behaviour in dynamic physical systems remains insufficiently characterised. This study investigates how representational capacity influences surrogate modelling accuracy for a crank-angle-resolved internal combustion engine (ICE) simulation with a maximum dynamic state dimension of six. Two feedforward ANN configurations are evaluated: a low-capacity 5–5 architecture containing 84 trainable parameters and a high-capacity 25–25–25 architecture containing 1554 parameters (18.5× larger). Both networks approximate the nonlinear mapping from five embedded operating parameters to four peak thermodynamic outputs (maximum pressure, pressure phasing, maximum temperature, and temperature phasing). Evaluation across 53,178 operating points demonstrates that the high-capacity configuration reduces root mean squared error by factors of 30–50× relative to the low-capacity network, decreasing peak temperature error from 17.68 K to 0.36 K and peak pressure error from 0.116 MPa to 0.0025 MPa. Although both models achieve coefficients of determination exceeding 0.99, the low-capacity network exhibits heavy-tailed residual distributions and regime-dependent error amplification, whereas the high-capacity model reduces both central dispersion and extreme-case error. These results demonstrate that high correlation alone does not guarantee engineering reliability in nonlinear thermodynamic systems. Distribution-level analysis, including percentile and extreme-case characterisation, is required to evaluate engineering robustness. The findings provide a quantitative framework linking ANN capacity, nonlinear dynamic system representation, and predictive robustness. Full article

Approximately one quarter of the European Union’s (EU’s) CO₂ emissions originate from the transport sector, of which road transport, such as cars and heavy-duty vehicles, contributes roughly 72%. Moreover, according to the European Automobile Manufacturers’ Association, 92% of cars in the EU are internal combustion engine vehicles powered by fossil fuels. Therefore, boosting the adoption of Electric Vehicles (EVs) is considered one of the most prominent solutions for reducing GHG emissions and achieving the EU’s climate targets. To increase EV adoption and fulfil the demand of EV users, adequate EV Charging Stations (EVCSs) are required. Nevertheless, since most EVCSs are supplied by electricity grids that remain predominantly fossil fuel-based, their operation entails substantial indirect GHG emissions. A prominent approach to reducing grid-related emissions is integrating renewable energy sources (RESs) with EVCSs, thereby lowering emissions and alleviating grid stress. Although promising, the energy, economic, and environmental (3E) benefits of this integration remain insufficiently explored. Therefore, this study develops and applies a 3E optimisation framework to assess the feasibility and performance of RES-powered EVCS at NOVA University Lisbon (UNL). Data was collected from the UNL parking area, such as time of arrival, and time of departure. Also, a rule-based algorithm was developed to curate data and estimate the EVCS load profile. Furthermore, HOMER optimisation software was employed to evaluate four scenarios, including (i) an EVCS based on PV, Wind Turbine (WT), and the grid, (ii) an EVCS based on PV and the grid, (iii) an EVCS based on WT and the grid, and (iv) an EVCS based only on energy withdrawal from the grid (base scenario). Under the adopted techno-economic assumptions, in the most optimised scenario, economic and environmental analyses illustrate significant improvements over the base scenario: CO₂ emissions are five times lower, and cost of energy is significantly lower, resulting in significantly lower EV charging costs for users. The results demonstrate that, through developed feasibility studies, researchers, decision-makers, and stakeholders can reach better conclusions about EVCS planning and management. Full article

The structural reliability of pistons operating under severe thermo-mechanical loading strongly depends on the properties of the selected Al–Si alloy. This study presents an integrated experimental–numerical investigation of hypereutectic Al–Si alloys intended for piston applications. Phase constitution and silicon morphology were characterized by metallography and X-ray diffraction, while tensile testing provided mechanical properties for finite element modeling. The experimentally determined parameters were implemented in a three-dimensional piston model to evaluate stress distribution, deformation, and safety margins under maximum combustion pressure and maximum engine speed. The simulations revealed maximum von Mises stresses up to 150 MPa, with inter-alloy differences below 0.3%, indicating geometry-dominated stress behavior. The maximum displacement did not exceed 76 µm, varying by approximately 3% between alloys. In contrast, the minimum factor of safety ranged from 1.20 to 1.35, showing differences of up to 12%, primarily governed by yield strength and microstructural homogeneity. The results demonstrate that piston performance under combustion-dominated loading is strength-controlled rather than stiffness-controlled. The study provides quantitative insight into the structure–properties–performance relationship of hypereutectic Al–Si alloys and supports informed material selection for preliminary piston design. Full article

Hydrogen combustion is known to be fast compared to traditional hydrocarbon fuels. The fast combustion leads to a higher thermal efficiency. In this research a 600 cc single cylinder hydrogen engine was tested at 1250 rpm, lambda = 2 and 3, and three load levels (load was represented by Manifold Absolute Pressure (MAP); MAPs tested were 75, 95 and 120 kPa) and compared to operation with gasoline and propane. The fast burn duration (Mass Fraction Burnt MFB10% to MFB90%) and the MFB 50% were determined and analyzed. The hydrogen MFB50% location for Minimum Timing for Best Torque (MBT) was found to occur at around the typical 8 Crank Angle Degrees (CADs) After Top Dead Center (ATDC). Measurements of ignition delay based on the fast data direct measurement of spark ignition coil current drop to the change in polarity of net heat release are presented. With shifts towards direct injection and higher injection pressures, consideration was given to the hydrogen pressurization penalty, where it was calculated that pressurizing hydrogen to 100 bar at the flow required for lambda = 2 operation is 2.3 bar, i.e., higher than the Friction Mean Effective Pressure (FMEP)! Furthermore, hydrogen is widely cited to have a higher heat loss than typical hydrocarbon fuels. In this paper, detailed analyses at lambda 2 and lambda 3 showed that hydrogen in fact has lower heat losses. Full article

Reducing friction in the piston ring–cylinder liner contact is a key area for improving the efficiency of internal combustion engines. While tribological studies commonly focus on the top dead centre region using linear tribometers, the mid-stroke regime—with its higher sliding velocities—remains experimentally inaccessible to most conventional test methods. This study presents a rotating ring-on-liner tribometer that enables investigations at constant relative speed by transitioning the motion from oscillating to rotating. A cylindrical substitution geometry for the piston ring specimen is derived through a coupled elastohydrodynamic and asperity contact simulation approach to reproduce realistic load-sharing behaviour. Experimental results from starved lubrication tests demonstrate stable contact conditions with a low coefficient of variation in wear, confirming good reproducibility. Stepwise performed Stribeck tests at 40 °C and 100 °C reveal characteristic friction–velocity behaviour, including the transition from mixed to hydrodynamic lubrication. Although the test rig’s maximum sliding speed and steady-state thermal conditions differ from fired engine environments, the methodology closes an important gap between low-speed linear tribometers and complex floating-liner systems. The presented approach provides a flexible and robust platform for controlled parametric studies of ring-on-liner contacts under application-relevant lubrication regimes. Full article

The non-repeatability of the internal combustion engine’s cycle-by-cycle (CCN-R) operation directly affects pollutant emissions, fuel consumption, and energy efficiency. Reducing this non-repeatability is an important part of efforts to improve the environmental performance of power units. Cycle variability analysis allows the identification of engine operating areas that promote unstable combustion and increased emissions of harmful exhaust components. The aim of the study was to quantitatively assess the cycle-to-cycle non-repeatability COV of selected operating parameters of the Perkins 1104D-E44TA diesel engine. The analyses covered the maximum cylinder pressure (p_max), the mean indicated pressure (IMEP), and the crankshaft rotation angle corresponding to the occurrence of maximum pressure (α). The measurements were carried out on an engine dynamometer at 25 operating points, covering speeds 1000–2200 r./min and load torques 200–400 N × m, recording 500 consecutive operating cycles at each point. The results showed that the most stable engine operation occurred at medium rotational speeds and moderate loads, where COV_pmax values did not exceed 0.5% and COV_IMEP values were lower than 1.0%. Increased pmax non-repeatability (up to 2.10%) and very high α angle variability (up to 100–140%) were observed at high rotational speeds and high loads. Only in the case of COV_IMEP was a significant reduction in repeatability observed compared to idling. The results obtained from cycle-by-cycle non-repeatability analyses can ultimately, after being supplemented with exhaust gas composition testing, be used as tools to support engine control optimization in order to reduce pollutant emissions and improve combustion efficiency. Full article

This study numerically investigates the conversion of a Heavy-Duty (HD) Spark-Ignition (SI) Compressed Natural Gas (CNG) engine to operate with hydrogen-rich syngas produced from waste plastic pyrolysis. The engine was modeled with a one-dimensional simulation tool. Fuel-specific properties were included through a tabulated Laminar Flame Speed (LFS) approach, and knock occurrence was predicted with a Tabulated Kinetic of Ignition (TKI) model. Full-load simulations revealed that direct substitution of CNG with syngas leads to abnormal combustion. With adjusted values of Spark Advance (SA) to avoid knock, syngas operation resulted in average reductions of approximately 15% in brake torque and 6% in total efficiency compared to the CNG baseline. Parametric analyses showed that Late Intake Valve Closing (LIVC) provides no benefits, whereas increasing the Compression Ratio (CR) partially recovers performance and efficiency, with knock being a limiting factor. Lastly, a complete engine map of the converted configuration was generated, reporting Brake-Specific Fuel Consumption (BSFC) and emissions. Overall, the study demonstrates that HD SI engines can be operated on hydrogen-rich syngas at the cost of moderate performance penalties. Moreover, it provides a robust modeling framework to support system-level and well-to-wheel assessments of syngas-based powertrains. Full article

This study introduces and compares online rule-based and optimization-based energy management strategies for a mild hybrid electric vehicle, with their performance evaluated against an offline Dynamic Programming benchmark. A structured rule-based strategy is proposed to enforce engine operation along its optimal efficiency line, while the remaining power demand is balanced by the electric motor. To achieve charge-sustaining battery operation, a soft state of charge regulation mechanism is incorporated. An Equivalent Consumption Minimization Strategy (ECMS) is also developed using a precise formulation of battery equivalent fuel consumption computed from instantaneous engine and electric path efficiencies, instead of constant efficiencies used in the literature. DP, which provides a globally optimal solution over the entire driving cycle, is employed as a benchmark for assessing the rule-based and ECMS strategies. The control strategies are compared under charge-sustaining conditions, considering engine and motor operation characteristics, overall fuel consumption, and battery usage intensity. Furthermore, the influence of load shifting between the internal combustion engine and the electric motor on overall vehicle performance is analyzed. Fuel consumption decreases by 13.5% relative to the engine-only baseline with the proposed ECMS with precise equivalent fuel consumption, and DP yields an additional 1.6% benefit. Compared with the developed rule-based controller, ECMS nearly halves the battery usage intensity, and DP provides 3.1% further reduction relative to ECMS. Full article