Search Results

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.

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.

This work presents the results of an experimental investigation on a GDI injector, in order to analyze fuel injection process and atomization phenomenon, correlating imaging and vibro-acoustic diagnostic techniques. A single-hole, axially-disposed, 0.200 mm diameter GDI injector was used to spray commercial gasoline in a test chamber at room temperature and atmospheric backpressure. The explored injection pressures were ranged from 5.0 to 20.0 MPa. Cycle-resolved acquisitions of the spray evolution were acquired by a high-speed camera. Simultaneously, the vibro-acoustic response of the injector was evaluated. More in detail, noise data acquired by a microphone sensor were analyzed for characterizing the acoustic emission of the injection, while a spherical loudspeaker was used to excite the spray injection at a proper distance detecting possible fuel spray resonance phenomena.

In recent years, great interest on NVH characteristics of vehicles has been paid by all the big automotive manufacturers. Interior acoustic comfort is now one of the main key factors in vehicle development process, since it contributes to improved product overall quality. Therefore, in automotive industry advanced NVH refinement needs to work in synergy with all research activities. Assessing the level of experienced noise in interior cabin requires particular arrangements for ensuring adequate measurement accuracy (AC system off, closed window, etc.). The use of parameters such as the level of seat vibration, not affected by the acoustic field conditions inside the vehicle, could facilitate experiments in parallel with engine/vehicle calibration activities.

The paper describes the challenges and results achieved in developing a new high-speed Diesel combustion system capable of exceeding the imaginative threshold of 100 kW/l. High-performance, state-of-art prototype components from automotive diesel technology were provided in order to set-up a single-cylinder research engine demonstrator. Key design parameters were identified in terms boost, engine speed, fuel injection pressure and injector nozzle flow rates. In this regard, an advanced piezo injection system capable of 3000 bar of maximum injection pressure was selected, coupled to a robust base engine featuring ω-shaped combustion bowl and low swirl intake ports. The matching among the above-described elements has been thoroughly examined and experimentally parameterized.

The characteristics of the intake system affect both engine power output and gas-dynamic noise emissions. The latter is particularly true in downsized VVA engines, where a less effective attenuation of the pressure waves is realized, due to the intake line de-throttling at part-load. For this engine architecture, a refined air-box design is hence requested. In this work, the Transmission Loss (TL) of the intake air-box of a commercial VVA engine is numerically computed through a 3D FEM approach. Results are compared with experimental data, showing a very good correlation. The validated model is then coupled to an external optimizer (ModeFRONTIERTM) to increase the TL parameter in a prefixed frequency range. The improvement of the acoustic attenuation is attained through a shape deformation of the inner structure of the base device, taking into account constraints related to the device installation inside the engine bay.

In an Internal Combustion Engine, the design of the intake system is a very critical aspect since it affects both the engine power output and noise emissions at the intake side. In particular, downsized VVA engines typically produce higher gas-dynamic noise levels since, due to the intake line de-throttling at part-load, a less effective attenuation of the pressure waves is realized. In this work, the acoustic performance of the intake air filter of a commercial VVA engine is numerically and experimentally analyzed. In particular, a FEM model of the system is realized in order to compute the Transmission Loss (TL) parameter of the base device. The numerical analysis accounts of fluid-structure interaction, which gives the possibility to determine the effect of structure participation on the TL profile. Contemporarily, the experimental tests are performed on an acoustic test bench based on the multi-microphone technique for the evaluation of the acoustic parameters.

Gasoline direct injection (GDI) combustion with un-throttled lean stratified operation allows to reduce engine toxic emissions and achieve significant benefits in terms of fuel consumption. However, use of gasoline stratified charges can lead to several problems, such as a high cycle-to-cycle variability and increased particle emissions. Use of multiple injection strategies allows to mitigate these problems, but it requires the injection of small fuel amounts forcing the traditional solenoid injectors to work in their “ballistic” region, where the correlation between coil energizing time and injected fuel amount becomes highly not linear. In the present work a closed-loop control system able to manage the delivery of small quantities of fuel has been introduced. The control system is based on a particular feature found on the coil voltage command signal during the de-energizing phase.

This paper reports 1D and 3D CFD analyses aiming to improve the gas-dynamic noise emission of a downsized turbocharged VVA engine through the re-design of the intake air-box device, consisting in the introduction of external or internal resonators. Nowadays, modern spark-ignition (SI) engines show more and more complex architectures that, while improving the brake specific fuel consumption (BSFC), may be responsible for the increased noise radiation at the engine intake mouth. In particular VVA systems allow for the actuation of advanced valve strategies that provide a reduction in the BSFC at part load operations thanks to the intake line de-throttling. In these conditions, due to a less effective attenuation of the pressure waves that travel along the intake system, VVA engines produce higher gas-dynamic noise levels.

The present paper reports 1D and 3D CFD analyses of the air-filter box of a turbocharged VVA engine, aiming to predict and improve the gas-dynamic noise emissions through a partial re-design of the device. First of all, the gas-dynamic noise at the intake mouth is measured during a dedicated experimental campaign. The developed 1D and 3D models are then validated at full load operation, based on experimental data. In particular, 1D model provides a preliminary evaluation of the radiated noise and simultaneously gives reliable boundary conditions for the unsteady 3D CFD simulations. The latter indeed allow to better take into account the geometrical details of the air-filter and guarantee a more accurate gas-dynamic noise prediction. 3D CFD analyses put in evidence that sound emission mainly occur within a frequency range of 350 to 450 Hz.

During the last years, a number of techniques aimed at the experimental identification of the knocking onset in Spark-Ignition (SI) Internal Combustion Engines have been proposed. Besides the traditional procedures based on the processing of in-cylinder pressure data in the frequency domain, in the present paper two innovative methods are developed and compared. The first one is based on the use of statistical analysis by applying an Auto Regressive Moving Average (ARMA) technique, coupled to a prediction algorithm. It is shown that such parametric model, applied to the instantaneous in-cylinder pressure measurements, is highly sensitive to knock occurrence and is able to identify soft or heavy knock presence in different engine operating conditions. An alternative, more expensive procedure is developed and compared to the previous one.

This study aims at building efficient and robust artificial neural networks (ANN) able to reconstruct the in-cylinder pressure of Diesel engines and to identify engine conditions starting from the signal of a low-cost accelerometer placed on the engine block. The accelerometer is a perfect non-intrusive replacement for expensive probes and is prospectively suitable for production vehicles. In this view, the artificial neural network is meant to be efficient in terms of response time, i.e. fast enough for on-line use. In addition, robustness is sought in order to provide flexibility in terms of operation parameters. Here we consider a feed-forward neural network based on radial basis functions (RBF) for signal reconstruction, and a feed-forward multi-layer perceptron network with tan-sigmoid transfer function for signal classification. The networks are trained using measurements from a three-cylinder real engine for various operating conditions.

The paper describes an experimental activity on the spatial and temporal liquid- and vapor-phase distributions of diesel fuel at engine-like conditions. The influence of the k-factor (0 and 1.5) of a single-hole axial-disposed injector (0.100 mm diameter and 10 L/d ratio) has been studied by spraying fuel in an optically-accessible constant-volume combustion vessel. A high-speed imaging system, capable of acquiring Mie-scattering and Schlieren images in a near simultaneous fashion mode along the same line of sight, has been developed at the Michigan Technological University using a high-speed camera and a pulsed-wave LED system. The time resolved pair of schlieren and Mie-scattering images identifies the instantaneous position of both the vapor and liquid phases of the fuel spray, respectively. The studies have been performed at three injection pressures (70, 120 and 180 MPa), 23.9 kg/m3 ambient gas density and 900 K gas temperature in the vessel.

Modern VVA systems offer new potentialities in improving fuel consumption for spark-ignition engines at low and medium load, meanwhile they grant a higher volumetric efficiency and performance at high load. Recently introduced systems enhance this concept through the possibility of modifying the intake valve opening, closing and lift, leading to the development of almost ‘throttle-less’ engines. However, at low loads, the absence of throttling, while improving the fuel consumption, also produces an increased gas-dynamic noise at the intake mouth. Wave propagation inside the intake system is in fact no longer absorbed by the throttle valve and directly impact the radiated noise. In the paper, 1D and 3D simulations of the gas-dynamic noise radiated by a production VVA engine are performed at full load and in two part-load conditions. Both models are firstly validated at full load, through comparisons with experimental data.

A wide investigation on powered two-wheelers (PTWs) is presented, aiming at the analysis of the influence of the driving characteristics on PTWs exhaust emissions and fuel consumption, a deeper comprehension of the engine and after-treatment system behavior within the cold start transient and the evaluation of cold start additional emissions for different two-wheelers classes. The study was developed with reference to an European context focusing on Euro 3 motorcycles and Euro 2 mopeds. An experimental investigation on instantaneous speed measurements was carried out with instrumented motorcycles, considering typical urban trips in the city of Genoa. A selection of speed profiles was then performed by processing experimental values.

This paper is based on a Research Project of the Department of Mechanical Engineering (DiME) in collaboration with Aprilia, the Italian motorbike manufacturer. In an attempt to simulate the functioning of the cooling plant of the Aprilia RSV-4 motorbike a numerical model was constructed using mono-dimensional and three-dimensional simulation codes. Our ultimate aim was to create a simulation model which could be of assistance to engine designers to improve cooling plant performance, thereby reducing research and development costs. The model allows to simulate the running conditions of the whole cooling circuit upon variations in environmental and running conditions. In particular, the centrifugal pump of the cooling plant was simulated by a 3D commercial software, while the whole circuit was built by a 1D commercial code which allows simulation of all the thermal exchanges and pressure drops in the cooling circuit.

In the paper a coupled Multi-Body and FEM-BEM methodology used to predict the noise radiated by a turbocharged 4-cylinder diesel engine prototype is described. A Multi-Body Dynamic Simulation (MBDS) of the engine has been carried out, simulating an engine speed sweep from 1500 to 4000 rpm, in order to determine the excitation force of the powertrain, and in particular to estimate the forces acting on the cylinder block. Thanks to the Multi-Body approach, the dynamics of the engine powertrain have been described taking into account both the effects of the burnt gas pressure during the combustion process and the inertia forces of the moving parts. Moreover to assess the real engine operating behaviour, both the crank and the block have been considered as flexible bodies.

In order to meet the stricter and stricter emission regulations, cleaner combustion concepts for Diesel engines are being progressively introduced. These new combustion approaches often requires closed loop control systems with real time information about combustion quality. The most important parameter for the evaluation of combustion quality in internal combustion engines is the in-cylinder pressure, but its direct measurement is very expensive and involves an intrusive approach to the cylinder. Previous researches demonstrated the direct relationship existing between in-cylinder pressure and engine block vibration signal and several authors tried to reconstruct the pressure cycle on the basis of information coming from accelerometers mounted on engine block. This paper proposes a method, based on the analysis of the engine vibration signal, for the diagnosis of combustion process in a Diesel engine.

This study aims at building an efficient and robust radial basis function (RBF) artificial neural network (ANN), to reconstruct the in-cylinder pressure of a diesel engine starting from the signal of a low-cost accelerometer placed on the engine block. The accelerometer is a perfect non-intrusive replacement for expensive probes and is prospectively suitable for production vehicles. The RBF network is trained using measurements from different engine operating conditions. Training data are composed of time series from the accelerometer and corresponding measured in-cylinder pressure signals. The RBF network is then validated using data not included in training and the results show good correspondence between measured and reconstructed pressure signal. Various network parameters are used to optimize the network quality.

Automotive exhaust systems give a major contribution to the sound quality of a vehicle and must be properly designed in order to produce acceptable acoustic performances. Obviously, noise attenuation is strictly related to the used materials and to its internal geometry. This last influences the wave propagation and the gas-dynamic field. The purpose of this paper is to describe advantages and disadvantages of different numerical approaches in evaluating the acoustic performance in terms of attenuation versus frequency (Transmission Loss) of a commercial two perforated tube muffler under different conditions. At first, a one-dimensional analysis is performed through the 1D GTPower® code, solving the nonlinear flow equations which characterize the wave propagation phenomena. The muffler is characterized as a network of properly connected pipes and volumes starting from 3D CAD information. Then, two different 3D analyses are performed within the commercial STS VNOISE® code.