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The dynamic model is built in Siemens Simcenter Amesim platform and simulates the performances on track of JUNO, a low energy demanding Urban Concept vehicle to take part in the Shell Eco-Marathon competition, in which the goal is to achieve the lowest fuel consumption in covering some laps of a racetrack, with limitations on the maximum race time. The model starts with the longitudinal dynamics, analysing all the factors that characterize the vehicle’s forward resistance, like aerodynamic forces, altimetry changes and rolling resistance. To improve the correlation between simulation and track performances, the model has been updated with the implementation of a Single-Track Model, including vehicle rotation around its roll axis, and a 3D representation of the racetrack, with an automatic trajectory following control implemented. This is crucial to characterise the vehicle’s lateral dynamics, which cannot be neglected in simulating its performances on track.

Different hybrid powertrains for a European mid-size passenger car were evaluated in this paper through numerical simulation. Different degrees of hybridizations, from micro to mild hybrids, and different architectures and power sources management strategies were taken into account, in order to obtain a preliminary assessment of the potentialities of different hybrid systems for the European passenger car market. Both diesel and gasoline internal combustion engines were considered: a 1.6 dm₃ Common Rail turbocharged diesel, and a 1.4 dm₃ spark ignition turbocharged engine, equipped with an innovative Variable Valve Actuation system. Diesel hybrid powertrains, although being subject to NOx emissions constraints that could jeopardize their benefits, offered substantial advantages in comparison with gasoline hybrid powertrains. Potentialities for fuel consumption reductions up to 25% over the NEDC were highlighted, approaching the 2020 EU 95 g/km CO₂ target.

The application of computational methods for the development of the whole engine-vehicle system has been evaluated in this paper, to highlight the potential of computer simulation techniques applied to the analysis of engine-vehicle matching. First, engine performance was simulated using a one-dimensional fluid dynamic code, and predicted data were compared to experimental results, to assess the accuracy of the engine computer model not only as far as gross engine performance parameters are concerned, but also for the prediction of pressure values at several locations inside the engine. The simulation was also extended to the whole engine operating range, including part-load operating conditions. Afterwards, a vehicle simulation code was employed, to predict vehicle performance and fuel consumption.

Feed-forward low-throughput models have been developed to predict MFB50 and to control SOI in order to achieve a specific MFB50 target for diesel engines. The models have been assessed on a GMPT-E Euro 5 diesel engine, installed at the dynamic test bench at ICEAL-PT (Internal Combustion Engine Advanced Laboratory at the Politecnico di Torino) and applied to both steady state and transient engine operating conditions. MFB50 indicates the crank angle at which 50% of the fuel mass fraction has burned, and is currently used extensively in control algorithms to optimize combustion phasing in diesel engines in real-time. MFB50 is generally used in closed-loop combustion control applications, where it is calculated by the engine control unit, cycle-by-cycle and cylinder by-cylinder, on the basis of the measured in-cylinder pressure trace, and is adjusted in order to reduce the fuel consumption, combustion noise and engine-out emissions.

Nowadays stringent emission regulations are pushing towards new air management strategies like LP-EGR and HP/LP mix both for passenger car and heavy duty applications, increasing the engine control complexity. Within a project in collaboration between Kohler Engines EMEA, Politecnico di Torino, Ricardo and Denso to exploit the potential of EGR-Only technologies, a 3.4 liters KDI 3404 was equipped with a two stage turbocharging system, an extremely high pressure FIS and a low pressure EGR system. The LP-EGR system works in a closed loop control with an intake oxygen sensor actuating two valves: an EGR valve placed downstream of the EGR cooler that regulates the flow area of the bypass between the exhaust line and the intake line, and an exhaust flap to generate enough backpressure to recirculate the needed EGR rate to cut the NOx emission without a specific aftertreatment device.

A new test bench has been set up and equipped in order to analyze the air mean motion and turbulence quantities in the combustion system of an automotive diesel engine with one helicoidal intake duct and a conical type in-piston bowl. A sophisticated HWA technique employing single- and dual-sensor probes was applied to the in-cylinder flow investigation under motored conditions. The anemometric probe was also operated as a thermometric sensor. An analytical-numerical procedure, based on the heat balance equations for both anemometric and thermometric wires, was refined and applied to compute the gas velocity from the anemometer output signal. The gas property influence, the thermometric sensor lag and the prong temperature effects were taken into account with this procedure. The in-cylinder velocity data were reduced using both a cycle-resolved approach and the conventional ensemble-averaging procedure, in order to separate the mean flow from the fluctuating motion.

In the frame of the space food production research activities conducted in the Thales Alenia Space Italia (TAS-I) Advanced Life Support Research and Development laboratory (RecycLAB, [6]), and with the contribution of a degree thesis developed in collaboration with the Politecnico of Torino, a rack-like facility for ground research on Life Support Systems based on Plants has been designed, developed, integrated, verified and tested in TAS-I. The new facility, called EDEN EPISODE 2, is a significant evolution of a previous TAS-I project (EDEN EPISODE 1) and takes benefit from other lower size TAS-I demonstrators (CUBE). It aims at realizing a completely closed and controlled environment for crop production, while a mobile lighting panel allows to maximize the delivered light in each phase of the plant life cycle. Hydroponic and aeroponic techniques have been implemented in the project for nutrient delivery to the plant roots.

Despite the legislation targets set by several governments of a full electrification of new light-duty vehicle fleets by 2035, the development of innovative, environmental-friendly Internal Combustion Engines (ICEs) is still crucial to be on track toward the complete decarbonization of on road-mobility of the future. In such a framework, the PHOENICE (PHev towards zerO EmissioNs & ultimate ICE efficiency) project aims at developing a C SUV-class plug-in hybrid (P0/P4) vehicle demonstrator capable to achieve a -10% fuel consumption reduction with respect to current EU6 vehicle while complying with upcoming EU7 pollutant emissions limits. Such ambitious targets will require the optimization of the whole engine system, exploiting the possible synergies among the combustion, the aftertreatment and the exhaust waste heat recovery systems.

Active tire pressure control (ATPC) is an automatic central tire inflation system (CTIS), designed, prototyped, and tested at the Politecnico di Torino, which is aimed at improving the fuel consumption, safety, and drivability of passenger vehicles. The pneumatic layout of the system and the designed solution for on board integration are presented. The critical design choices are explained in detail and supported by experimental evidence. In particular, the results of experimental tests, including the characterizations of various pneumatic components in working conditions, have been exploited to obtain a design, which allows reliable performance of the system in a lightweight solution. The complete system has been tested to verify its dynamics, in terms of actuation time needed to obtain a desired pressure variation, starting from the current tire pressure, and to validate the design.

Meticulous design of the energy management control algorithm is required to exploit all fuel-saving potentials of a hybrid electric vehicle. Equivalent consumption minimization strategy is a well-known representative of on-line strategies that can give near-optimal solutions without knowing the future driving tasks. In this context, this paper aims to propose an adaptive real-time equivalent consumption minimization strategy for a multi-mode hybrid electric powertrain. With the help of road recognition and vehicle speed prediction techniques, future driving conditions can be predicted over a certain horizon. Based on the predicted power demand, the optimal equivalence factor is calculated in advance by using bisection method and implemented for the upcoming driving period. In such a way, the equivalence factor is updated periodically to achieve charge sustaining operation and optimality.

The issue of greenhouse gas (GHG) emissions from the transportation sector is widely acknowledged. Recent years have witnessed a push towards the electrification of cars, with many considering it the optimal solution to address this problem. However, the substantial battery packs utilized in electric vehicles contribute to a considerable embedded ecological footprint. Research has highlighted that, depending on the vehicle's size, tens or even hundreds of thousands of kilometers are required to offset this environmental burden. Human-powered vehicles (HPVs), thanks to their smaller size, are inherently much cleaner means of transportation, yet their limited speed impedes widespread adoption for mid-range and long-range trips, favoring cars, especially in rural areas. This paper addresses the challenge of HPV speed, limited by their low input power and non-optimal distribution of the resistive forces.

The use of Ducted Fuel Injection (DFI) for attenuating soot formation throughout mixing-controlled diesel combustion has been demonstrated impressively effective both experimentally and numerically. However, the last research studies have highlighted the need for tailored engine calibration and duct geometry optimization for the full exploitation of the technology potential. Nevertheless, the research gap on the response of DFI combustion to the main engine operating parameters has still to be fully covered. Previous research analysis has been focused on numerical soot-targeted duct geometry optimization in constant-volume vessel conditions. Starting from the optimized duct design, the herein study aims to analyze the influence of several engine operating parameters (i.e. rail pressure, air density, oxygen concentration) on DFI combustion, having free spray results as a reference.

To comply with the stringent fuel consumption requirements, many automobile manufacturers have launched vehicle electrification programs which are representing a paradigm shift in vehicle design. Looking specifically at powertrain calibration, optimization approaches were developed to help the decision-making process in the powertrain control. Due to computational power limitations the most common approach is still the use of powertrain calibration tables in a rule-based controller. This is true despite the fact that the most common manual tuning can be quite long and exhausting, and with the optimal consumption behavior rarely being achieved. The present work proposes a simulation tool that has the objective to automate the process of tuning a calibration table in a powertrain model. To achieve that, it is first necessary to define the optimal reference performance.

An unsupervised machine-learning technique, aimed at the identification of the optimal rule-based control strategy, has been developed for parallel hybrid electric vehicles that feature a torque-coupling (TC) device, a speed-coupling (SC) device or a dual-mode system, which is able to realize both actions. The approach is based on the preliminary identification of the optimal control strategy, which is carried out by means of a benchmark optimizer, based on the deterministic dynamic programming technique, for different driving scenarios. The optimization is carried out by selecting the optimal values of the control variables (i.e., transmission gear and power flow) in order to minimize fuel consumption, while taking into account several constraints in terms of NOx emissions, battery state of charge and battery life consumption.

A quasi-dimensional multizone combustion model, that was previously developed by the authors, has been refined and applied for the analysis of combustion and emission formation in a EURO V diesel engine equipped with a piezo indirect-acting injection system. The model is based on the integration of the predictive non-stationary variable-profile 1D spray model recently presented by Musculus and Kattke, with a diagnostic multizone thermodynamic model specifically developed by the authors. The multizone approach has been developed starting from the Dec conceptual scheme, and is based on the identification of several homogeneous zones in the combustion chamber, to which mass and energy conservation laws have been applied: an unburned gas zone, made up of air, EGR (Exhaust Gas Recirculation) and residual gas, several fuel/unburned gas mixture zones, premixed combustion burned gas zones and diffusive combustion burned gas zones.

Although the use of Exhaust Gas Recirculation (EGR) is nowadays mandatory for automotive diesel engines to achieve NOx emissions levels complying with more and more stringent legislation requirements, electronically controlled EGR systems still represent an expensive technology, often unsuitable for small diesel engines for off-road applications or for two/three wheelers. An interesting option for these categories of small diesel engines is the so-called “internal EGR”, which is obtained by modifying the intake or the exhaust valve lift profile, in order to increase the fraction of exhaust residuals at the end of the intake stroke. Different valve lift profiles were therefore evaluated for a 2 cylinders, 700 cc, Lombardini IDI diesel engine, equipping a light 4 wheelers vehicle.

The effects of using a B30 blend of ultra-low sulfur diesel and two different Fatty Acid Methyl Esters (FAME) obtained from both Rapeseed Methyl Ester (RME) and Jatropha Methyl Ester (JME) in a Euro 5 small displacement passenger car diesel engine on both full load performance and part load emissions have been evaluated in this paper. In particular the effects on engine torque were firstly analyzed, for both a standard ECU calibration (i.e., without any special tuning for the different fuel characteristics) and for a specifically adjusted ECU calibration obtained by properly increasing the injected fuel quantities to compensate for the lower LHV of the B30: with the latter, the same torque levels measured under diesel operation could be observed with the B30 blend too, with lower smoke levels, thus highlighting the potential for maintaining the same level of performance while achieving substantial emissions benefits.

This paper presents a low-cost path for extending the range of small urban pure electric vehicles by hydraulic hybridization. Energy management strategies are investigated to improve the electric range, component efficiencies, as well as battery usable capacity. As a starting point, a rule-based control strategy is derived by analysis of synergistic effects of lead-acid batteries, high efficient operating region of DC motor and the hydraulic pump/motor. Then, Dynamic Programming (DP) is used as a benchmark to find the optimal control trajectories for DC motor and Hydraulic Pump/Motor. Implementable rules are derived by studying the optimal control trajectories from DP. With new improved rules implemented, simulation results show electric range improvement due to increased battery usable capacity and higher average DC motor operating efficiency. Presenter Xianke Lin

The sustainable use of energy and the reduction of pollutant emissions are main concerns of the automotive industry. In this context, Hybrid Electric Vehicles (HEVs) offer significant improvements in the efficiency of the propulsion system and allow advanced strategies to reduce pollutant and noise emissions. The paper presents the results of a simulation study that addresses the minimization of fuel consumption, NOx emissions and combustion noise of a medium-size passenger car. Such a vehicle has a parallel-hybrid diesel powertrain with a high-voltage belt alternator starter. The simulation reproduces real-driver behavior through a dynamic modeling approach and actuates an automatic power split between the Internal Combustion Engine (ICE) and the Electric Machine (EM). Typical characteristics of parallel hybrid technologies, such as Stop&Start, regenerative braking and electric power assistance, are implemented via an operating strategy that is based on the reduction of total losses.

Until 2017 in Europe the Type Approval (TA) procedure for light duty vehicles for the determination of pollutant emissions and fuel consumption was based on the New European Driving Cycle (NEDC), a test cycle performed on a chassis dynamometer. However several studies highlighted significant discrepancies in terms of CO2 emissions between the TA test and the real world, due to the limited representativeness of the test procedure. Therefore, the European authorities decided to introduce a new, up-to date, test procedure capable to closer represent real world driving conditions, called Worldwide Harmonized Light Vehicles Test Procedure (WLTP). This work aims to analyze the effects of the new WLTP on vehicle CO2 emissions through both experimental and simulation investigations on two different Euro 5 vehicles, a petrol and a diesel car, representatives of average European passenger cars.