In this study, emissions of compression ignition engine fueled by diesel fuel with nanoparticle additives was modeled by regression analysis, artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS) methods. Cetane number (CN) and engine speed (rpm) were selected as input parameters for estimation of carbon monoxide (CO), oxides of nitrogen (NOx), and carbon dioxide (CO2) emissions. The results of estimation techniques were compared with each other and they showed that regression analysis was not accurate enough for prediction. On the other hand, ANN and ANFIS modelling techniques gave more accurate results with respect to regression analysis; linear and non-linear. Especially ANFIS models can be suggested as estimation method with minimum error compared to experimental results.

Growing awareness of climate change concerns and the environmental impacts of fossil fuel vehicles has heightened interest in electric vehicles (EVs). Therefore, EVs represent a significant component of sustainable transportation solutions. Additionally, with advancements in battery technology, EVs now have longer ranges and are offered at more competitive prices. With their notable features such as high energy density, lightness, low maintenance requirement, and long life, lithium-ion batteries (LiBs) appear to be the most suitable battery option for EVs. Nevertheless, current LiB technology faces battery costs, energy storage capacity, charging times, and safety issues. In this context, it is clear that future research and development will focus on improving the efficiency of LiB technology and making these batteries more sustainable, reliable, and economical. This study aims to provide an evaluation of the LiBs used in the automotive sector by examining the historical development, basics of operational principles, various geometric types, cost evaluation, and their advantages and disadvantages. By covering these aspects, the study seeks to offer a comprehensive assessment of the LiBs employed in the automotive industry, spanning from their historical evolution to their presentday utilization. The study also intends to serve as a reference source for researchers planning to conduct studies on LiBs in EVs by providing fundamental concepts and evaluations related to these batteries.

The energy that powers electric vehicles comes directly from their high-performance batteries, serving as the heart of their operation. They convert stored chemical energy into mechanical energy to propel vehicles. One of the most vital parts of an electric vehicle is a battery pack. Superior advantages such as higher energy density, longer life cycles, and the fast-charging ability of lithium-ion batteries set them apart from the others. However, battery performance and longevity exhibit a high degree of temperature sensitivity. In other words, operating batteries below and above the specified temperature range values causes problems such as decreased lifespan, safety issues, and performance losses. In electric vehicles, varying power demands during driving cause different current levels to be drawn from the battery packs. This leads to fluctuations in battery temperatures due to chemical reactions occurring. Besides that, regional and seasonal temperature variations also affect the operating temperatures of batteries. Therefore, maintaining the batteries within the specified temperature range, typically between 25 and 40 °C, is only achievable with an adequate battery thermal management system. This review intends to guide researchers working on designing more efficient thermal management systems by providing refined information about previous efforts in this field. The designs found in the literature have been illustrated with simplified figures. Cooling inlet and outlet locations are indicated in blue and red, enabling easier comparison and better understanding of different cooling designs. Air-cooling studies in the literature show that a well-designed system can keep the T_max and ΔT values of LiB cells ~305 K and 2.8 K during 3C discharge at a T_ambient of about 298.15 K. When liquid cooling systems are examined, a 50% glycol–water mixture can maintain pouch cells at nearly 30.3 °C with a ΔT of 2.78 °C under similar 3C and 25 °C conditions. Overall, the results demonstrate that well-designed BTMS configurations including optimized airflow or coolant–flow arrangements are capable of keeping LiBs safely within their optimal thermal operating conditions.

Temperature is a crucial parameter for ensuring the long lifespan and safe operation of lithium-ion batteries (LiBs). An efficient battery thermal management system (BTMS) tries to maintain temperature in between optimum limits. Despite some disadvantages, air-cooled BTMSs are still preferred due to their advantages such as light weight, simple design, low cost, and ease of maintenance. This study experimentally evaluated a fan-assisted BTMS for the purpose of cooling a 4S2P battery module that includes 18650 type cells. The battery module was initially tested with no cooling system to observe the temperature characteristics of the module, followed by testing with forced air cooling using a fan. Experiments were also conducted with perforated plates installed between the fan and the module to see their effects on the thermal behaviors. Tests were initiated when the ambient temperature was approximately 25 °C and the discharges were carried out by drawing constant currents of 4 A, 8 A, 12 A, and 16 A from the module via an electronic load. The results of this study highlighted the importance of an effective BTMS in ensuring battery safety and performance across different operational conditions. While all tested cooling configurations maintained acceptable temperature levels at lower discharge currents (4 A and 8 A), they struggled to do so at higher currents (12 A and 16 A). Among them, the Fan–HC mode demonstrated the highest efficiency, reducing the maximum temperature (T_max) by 38.82% at 12 A and 28.89% at 16 A compared to the no-cooling scenario. Moreover, it ensured a more uniform temperature distribution within the module. These findings emphasize the necessity of optimized cooling strategies, particularly for high-power applications.

In this study, a battery case was developed using a 3D (three dimensional)-printed composite of hexagonal boron nitride (hBN) and polylactic acid (PLA) to enhance the thermal performance of lithium-ion battery (LiB) modules. A 10 wt.% amount of hBN was incorporated into the PLA matrix to improve the composite’s thermal conductivity while maintaining electrical insulation. A 3S2P (3 series and 2 parallel) battery configuration was initially evaluated based on the results of a baseline study for comparison and subsequently subjected to a newly developed test procedure to assess the thermal behavior of the designed case under identical environmental conditions. Initially, X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses were utilized for material characterization, and their results verified the successful integration of hBN by confirming its presence in the hBN-PLA composite. In thermal tests, experimental results revealed that the fabricated hBN-PLA composite battery case significantly enhanced heat conduction and reduced surface temperature gradients compared to the previous baseline study with no case. Specifically, the maximum cell temperature (T_max) decreased from 48.54 °C to 45.84 °C, and the temperature difference (ΔT) between the hottest and coldest cells was reduced from 4.65 °C to 3.75 °C, corresponding to an improvement of approximately 20%. A 3S2P LiB module was also tested under identical environmental conditions using a multi-cycle charge–discharge procedure designed to replicate real electric vehicle (EV) operation. Each cycle consisted of sequential low and high discharge zones with gradually increased current values from 2 A to 14 A followed by controlled charging and rest intervals. During the experimental procedure, the average ΔT between the cells was recorded as 2.38 °C, with a maximum value of 3.50 °C. These results collectively demonstrate that the 3D-printed hBN-PLA composite provides an effective and lightweight passive cooling solution for improving the thermal stability and safety of LiB modules in EV applications.

In current study, exhaust emission, vibration and noise features of diesel engine with addition of metallic based nanoparticles into diesel fuels were investigated experimentally. Various nanoparticles called as silver (II) nitrate (AgNO3), manganese (II) nitrate hydrate (Mn(NO3)2. xH20) and nickel(II) nitrate hexahydrate (Ni(NO3)2.6H2O) were used as an additive to diesel fuel at 25 ppm and 50 ppm dosing level so as to obtain six different fuel samples. Diesel engine with air-cooled and a single cylinder were utilized for engine tests altering engine speed from 1200 to 2800 rpm at the intervals of 400 rpm. The results demonstrated that of the nanoparticle addition did not remarkably affect the physicochemical features of the diesel test blends. But, the addition of nanoparticles slightly raised viscosity, cetane number and the heating value of test fuels especially, at the higher nanoparticle concentrations. In all experiments, with nanoparticle added blend fuels, CO, HC, NOx emission values and brake specific fuel consumption (BSFC) declined in parallel with the increase in nanoparticle concentration. In addition, it was shown that the Sound Pressure Level (SPL) and vibration characteristics of the engine block also decreased with increasing nanoparticle concentration of test fuels. As a result, AgNO3 addition to diesel fuel has an effective role in both reducing emission and vibration values and reducing BSFC values.