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The interest of the vehicle producers in fulfillment emission legislations without adopting after treatment systems is driving to the use of non-conventional energy sources for modern engines. A previous test campaign dealing with the use of blends of diesel and propane in a CI engine has pointed out the potential of this non-conventional fuel for diesel engines. The soft adaptation of the common rail injection system and the potential benefits, in terms of engine performances and pollutant emissions, encourage the use of propane-diesel blends if an optimization of the injection strategies is performed. In this work, the performances of a propane-diesel mixture in a research diesel engine have been investigated. The injection strategies of Euro 5 calibration have been used as reference for the development of optimized strategies. The aim of the optimization process was to ensure the same engine power output and reduce the pollutant emissions.

The aim of this paper is to analyze the effects of different driving styles and patterns onboard battery packs (BPs) supplying electric vehicles. The analysis is carried out by using real urban driving cycles, acquired through vehicle On Board Diagnostic Port (OBDP), and a Matlab-Simulink scaled BP model, in which lithium BP has been parametrized and validated through specific experimental tests. The results have been mainly focused on the evaluations of BP State of Health (SoH) and capacity fading decreasing during its lifetime at several critical conditions. In particular, these evaluations have allowed critical driving and environmental operative conditions to be identified and highlighted. The obtained results provide useful information for both producers of Battery Electric Vehicle (BEV) Energy Storage Systems (ESS) in the design stage, and for artificial intelligence driver support systems, mainly focused on extending overall vehicle life.

The growing concern about Greenhouse Gas (GHG) emissions led institutions to further reduce the limits on vehicle-related CO2 emissions. Therefore, car manufacturers are developing vehicles with low environmental impact, like Hybrid-Electric Vehicles (HEVs), which in the series architecture employ an Internal Combustion Engine (ICE) coupled with an electric generator for battery recharging, thus extending the range of a Battery Electric Vehicle (BEV). For this kind of application, small four-stroke Spark Ignition (SI) engines are preferred, as they are a proven and reliable solution to increase the driving range with very low environmental impact. In series hybrid-electric powertrains, the ICE is decoupled from the drive wheels, then it can operate in a steady-state high-efficiency working point, regardless of the power required by the mission profile. The benefits of lean combustion can be exploited to increase efficiency and reduce CO2 and NOx emissions.

Gasoline direct injection (GDI) allows flexible operation of spark ignition engines for reduced fuel consumption and low pollutants emissions. The choice of the best combination of the different parameters that affect the energy conversion process and the environmental impact of a given engine may either resort to experimental characterizations or to computational fluid dynamics (CFD). Under this perspective, present work is aimed at discussing the assessment of a CFD-optimization (CFD-O) procedure for the highest performance of a GDI engine operated lean under both single and double injection strategies realized during compression. An experimental characterization of a 4-stroke 4-cylinder optically accessible engine, working stratified lean under single injection, is first carried out to collect a set of data necessary for the validation of a properly developed 3D engine model.

A growing number of electric vehicles (EV) and hybrid electric vehicles (HEV) in the present market depicts the rapid growing demand for energy storage systems. The battery’s main peculiarities must be the power density and reliability over time. The temperature strongly affects battery performance for low and high intensity. In particular, the management of the heat generated by the battery itself is one of the main aspects to handle to preserve the performance over time. The objective of this paper is to compare the surface temperature of the lithium-ion polymer battery at different discharging rates by infrared thermography. Thermal imaging is performed to detect the battery surface temperature distribution, focusing on its variation over time and the local inhomogeneity. Temperature measurements are then used to estimate the contributions of the different heat transfer mechanisms for the dissipation of the heat generated by the battery.

The battery efficiency is strongly affected by the operating temperature, granting the best performance in a limited range. Great attention is given to the design and the testing of materials for the battery heat dissipation. In the present study, the thermal behavior of a Li-polymer cell, which is part of a battery pack for electric vehicles, is investigated. The cell is provided with different coatings of carbon, graphene, and silicone, used in turn, to dissipate the heat generated during the operation in natural convection. The coating is placed only on one side of the battery while the other one is inspected via thermal imaging. Optical diagnostics in the infrared band are used to evaluate the bi-dimensional distribution of the battery surface temperature and the effect of the coatings. Different operating conditions are tested by varying the current demand.

Hybrid electric vehicles are a suitable solution for the transition from fossil fuels-based transportation to electric mobility. They have the benefits of zero-emissions operation when only the electric engine is used preventing the typical range anxiety of full-electric vehicles. Also, they can have a low battery pack capacity and weight thanks to the continuous recharge from the internal combustion engine that becomes the only responsible for exhaust emissions. A practical solution to limit the combustion engine emissions is represented by the range extender configuration, where the engine works at a fixed operating point with the highest efficiency serving uniquely as a battery charger. In the face of the current world situation and future changes, research for alternative energy sources is crucial. Hydrogen can be used as an alternative fuel for common internal combustion engines; moreover, it has the great advantage of high efficiency (about 44%).

Many aspects of battery electric vehicles are very challenging from the engineering point of view in terms of safety, weight, range, and drivability. Commercial vehicle engines are often subjected to high loads even at low speeds and this can lead to an intense increment of the battery pack temperature and stress of the cooling system. For these reasons the optimal design of the battery pack and the relative cooling system is essential. The present study deals with the challenge of designing a battery pack that satisfies both the conditions of lowest weight and efficient temperature control. The trade-off between the battery pack size and the electrical stress on the cells is considered. The electric system has the aim to substitute a 3.0 liters compression ignition engine mainly for commercial vehicles.

Growing concerns about the emissions of internal combustion engines have forced the adoption of aftertreatment devices to reduce the adverse impact of diesel engines on health and environment. Diesel particulate filters are considered as an effective means to reduce the particle emissions and comply with the regulations. Research activity in this field focuses on filter configuration, materials and aging, on understanding the variation of soot layer properties during time, on defining of the optimal strategy of DPF management for on-board control applications. A model was implemented in order to simulate the filtration and regeneration processes of a wall-flow particulate filter, taking into account the emission characteristic of the engine, whose architecture and operating conditions deeply affect the size distribution of soot particles.

In this work, a dynamic 0-D electro-thermal model of a lithium-polymer battery for automotive applications is presented. The model predicts the battery temperature during its charging/discharging phases under different environmental and operating conditions, by considering the requested power or current, the coolant flow rate and its temperature as model inputs. The model was first validated with experimental data carried out at the test bench where only the convective heat transfer between the battery and the ambient air was considered. The accuracy of the internal heat generation model was experimentally assessed for different current discharge rates. Then, a liquid cooling system was designed on purpose, assembled, and installed on the battery at the test bench for the improvement of the model predictions in liquid convection conditions.

The analysis of heat losses in internal combustion engines (ICEs) is fundamental to evaluate and to improve engine efficiency. Detailed and reliable heat transfer models are required for more complex 1d-3d combustion models. At the same time, the thermal status of engine components, like pistons, is needed for an efficient design. Measurements of piston temperature during ICEs operation represent an important and challenging result to get for the aforementioned purposes. In the present work, temperature measurements collected at different engine speeds and loads, both in motored and fired modes, have been performed and used to set-up a theoretical correlation and 1d model of heat transfer through the optical window of the piston. The in-cylinder gas and external ambient temperature, together with the thermodynamic and material properties are given. The model has been first calibrated in some selected operating conditions and then validated in the remaining.

Internal combustion engines are characterized by high pressure and thermal loads on pistons and in cylinders. The heat generated by the combustion process is dissipated by means of water and oil cooling systems. For the best design and optimization of the engine components it is necessary to know the components temperature in order to estimate the thermal flows. The purpose of this work is to measure the piston sapphire window temperature in a research optically accessible engine by combining two different techniques: measurements with templugs and with thermography. The method is very simple and can provide a reliable value of temperature within a small interval. It fits well for applications inside the engine because of its low technical level requirements. It consists of application of temperature sensitive stickers on the target component that makes it a very robust method, not affected by piston movement.

The electrochemical performance of a lithium-ion battery is strongly affected by the temperature. During charge and discharge cycles, batteries are subjected to an increment of temperature that can accelerate aging and loss of efficiency if critical values are reached. Knowing the thermal parameters that affect the heat exchange between the battery surface and the surrounding environment (air, cooling fins, plates, etc…) is fundamental to their thermal management. In this work, thermal imaging is applied to a laminated lithium-polymers battery as a non-invasive temperature-indication method. Measurements are taken during the discharge phase and the following cooling down until the battery reaches the ambient temperature. The 2d images are used to analyze the homogeneity of the temperature distribution on the battery surface. Then, experimental results are coupled with mathematical correlations.