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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 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.

In the last decades, the locomotion of wheeled and tracked vehicles on soft soils has been widely investigated due to the large interest in planetary, agricultural, and military applications. The development of a tire-soft soil contact model which accurately represents the micro and macro-scale interactions plays a crucial role for the performance assessment in off-road conditions since vehicle traction and handling are strongly influenced by the soil characteristics. In this framework, the analysis of realistic operative conditions turns out to be a challenging research target. In this research work, a semi-empirical model describing the interaction between a tire and homogeneous and fine-grained soils is developed in Matlab/Simulink. The stress distribution and the resulting forces at the contact patch are based on well-known terramechanics theories, such as pressure-sinkage Bekker’s approach and Mohr-Coulomb’s failure criterion.

Ammonia is a new type of carbon-free fuel with low cost, clean and safe. The research and application of zero-carbon fuel internal combustion engines has become the mainstream of future development. However, there still exist problems should be solved in the application of ammonia fuel. Due to the lower flame laminar speed and higher ignition temperature, ammonia may have unstable combustion phenomena. In this work, the characteristics of ammonia combustion have been investigated, based on controllable thermal activated atmosphere burner. The ignition delay has been used to analyze the ammonia combustion characteristics. With the increase in co-flow temperature, the ignition delay of ammonia/air has an obvious decline. In order to investigate the emission characteristics of ammonia, CHEMKIN is used to validate the different chemical reaction mechanisms and analyse the ammonia emissions.

Ride comfort assessment is undoubtedly related to the interaction between the vehicle tires and the road surface. Indeed, the road profile represents the typical input for tire vertical load estimation in durability analysis and for active/semi-active suspension controller design. However, the road profile evaluation through direct experimental measurements involves long test time and excessive cost required by professional instrumentations to detect the road irregularities with sufficient accuracy. An alternative is shifting attention towards efficient and robust algorithms for indirect road profile evaluation. The object of this work aims at providing road profile estimation starting from vehicle dynamics measurements, through accessible and traditional sensors, with the application of a linear Kalman filter algorithm.

In this paper, a numerical and experimental assessment of post injection potential for soot emissions mitigation in an off-road diesel engine is presented, with the aim of supporting hardware selection and engine calibration processes. As a case study, a prototype off-road 3.4 liters 4-cylinder diesel engine developed by Kohler Engines was selected. In order to explore the possibility to comply with Stage V emission standards without a dedicated aftertreatment for NOx, the engine was equipped with a low pressure cooled Exhaust Gas Recirculation (EGR), allowing high EGR rates (above 30%) even at high load. To enable the exploitation of such high EGR rates with acceptable soot penalties, a two-stage turbocharger and an extremely high-pressure fuel injection system (up to 3000 bar) were adopted. Moreover, post injections events were also exploited to further mitigate soot emissions with acceptable Brake Specific Fuel Consumption (BSFC) penalties.

Vehicle dynamics is a fundamental part of vehicle performance. It combines functional requirements (i.e. road safety) with emotional content (“fun to drive”, “comfort”): this balance is what characterizes the car manufacturer (OEM) driving DNA. To reach the customer requirements on Ride & Handling, integration of CAE and testing is mandatory. Beside of cutting costs and time, simulation helps to break down vehicle requirements to component level. On chassis, the damper is the most important component, contributing to define the character of the vehicle, and it is defined late, during tuning, mainly by experienced drivers. Usually 1D lookup tables Force vs. Velocity, generated from tests like the standard VDA, are not able to describe the full behavior of the damper: different dampers display the same Force vs. Velocity curve but they can give different feeling to the driver.

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.

Modern vehicles have several active systems on board such as the Electronic Stability Control. Many of these systems require knowledge of vehicle states such as sideslip angle and yaw rate for feedback control. Sideslip angle cannot be measured with the standard sensors present in a vehicle, but it can be measured by very expensive and large optical sensors. As a result, state observers have been used to estimate sideslip angle of vehicles. The current state of the art does not present an algorithm which can robustly estimate the sideslip angle for vehicles with all-wheel drive. A deep learning network based sideslip angle observer is presented in this article for robust estimation of vehicle sideslip angle. The observer takes in the inputs from all the on board sensors present in a vehicle and it gives out an estimate of the sideslip angle. The observer is tested extensively using data which are obtained from proving grounds in high tire-road friction coefficient conditions.

A model-based approach to control BMEP (Brake Mean Effective Pressure) and NOx emissions has been developed and assessed on a FPT F1C 3.0L Euro VI diesel engine for heavy-duty applications. The controller is based on a zero-dimensional real-time combustion model, which is capable of simulating the HRR (heat release rate), in-cylinder pressure, BMEP and NOx engine-out levels. The real-time combustion model has been realized by integrating and improving previously developed simulation tools. A new discretization scheme has been developed for the model equations, in order to reduce the accuracy loss when the computational step is increased. This has allowed the required computational time to be reduced to a great extent.

To comply with Stage IV emission standard for off-road engines, Kohler Engines has developed the 100kW rated KDI 3.4 liters diesel engine, equipped with DOC and SCR. Based on this engine, a research project in collaboration between Kohler Engines, Ricardo, Denso and Politecnico di Torino was carried out to exploit the potential of new technologies to meet the Stage IV and beyond emission standards. The prototype engine was equipped with a low pressure cooled EGR system, two stage turbocharger, high pressure fuel injection system capable of very high injection pressure and DOC+DPF aftertreatment system. Since the Stage IV emission standard sets a 0.4 g/kWh NOx limit for the steady state test cycle (NRSC), that includes full load operating conditions, the engine must be operated with very high EGR rates (above 30%) at very high load.

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 real-time approach has been developed and assessed to control BMEP (brake mean effective pressure) and MFB50 (crank angle at which 50% of fuel mass has burnt) in a Euro 6 1.6L GM diesel engine. The approach is based on the use of feed-forward ANNs (artificial neural networks), which have been trained using virtual tests simulated by a previously developed low-throughput physical engine model. The latter is capable of predicting the heat release and the in-cylinder pressure, as well as the related metrics (MFB50, IMEP - indicated mean effective pressure) on the basis of an improved version of the accumulated fuel mass approach. BMEP is obtained from IMEP taking into account friction losses. The low-throughput physical model does not require high calibration effort and is also suitable for control-oriented applications. However, control tasks characterized by stricter demands in terms of computational time may require a modeling approach characterized by a further lower throughput.

A method for estimating the sideslip angle of a Formula SAE vehicle with torque vectoring is presented. Torque vectoring introduces large tire longitudinal forces which lead to a reduction of the tire lateral forces. A novel tire model is utilized to represent this reduction of the lateral forces. The estimation is realized using an extended Kalman filter which takes in standard sensor measurements. The developed algorithm is tested by simulating slalom and figure eight maneuvers on a validated VI-CarRealTime vehicle model. Results indicate that the algorithm is able to estimate the sideslip angle of the vehicle reliably on a high friction surface track.

The predictive capabilities of an innovative multizone combustion model DIPulse, developed by Gamma Technologies, were assessed in this work for a last generation common rail automotive diesel engine. A detailed validation process, based on an extensive experimental data set, was carried out concerning the predicted heat release rate, the in-cylinder pressure trace, as well as NOx and soot emissions for several operating points including both part load and full load points. After a preliminary calibration of the model, the combustion model parameters were then optimized through a Latin Hypercube Design of Experiment (DoE), with the aim of minimizing the RMS error between the predicted and experimental burn rate of several engine operating points, thus achieving a satisfactory agreement between simulation and experimental engine combustion and emissions parameters.

New methodologies have been developed to optimize EGR rate and injection timing in diesel engines, with the aim of minimizing fuel consumption (FC) and NOx engine-out emissions. The approach entails the application of a recently developed control-oriented engine model, which includes the simulation of the heat release rate, of the in-cylinder pressure and brake torque, as well as of the NOx emission levels. The engine model was coupled with a C-class vehicle model, in order to derive the engine speed and torque demand for several driving cycles, including the NEDC, FTP, AUDC, ARDC and AMDC. The optimization process was based on the minimization of a target function, which takes into account FC and NOx emission levels. The selected control variables of the problem are the injection timing of the main pulse and the position of the EGR valve, which have been considered as the most influential engine parameters on both fuel consumption and NOx emissions.

A challenging task that is required to modern injection systems is represented by the enhanced control of the injected quantities, especially when small injections are considered, such as, pilot and main shots in the context of multiple injections. The propagation of the pressure waves triggered by the nozzle opening and closure events through the high-pressure hydraulic circuit can influence and alter the performance of the injection apparatus. For this reason, an investigation of the injection system fluid dynamics in the frequency domain has been proposed. A complete lumped parameter model of the high-pressure hydraulic circuit has been applied to perform a modal analysis. The visualization of the main vibration modes of the apparatus allows a detailed and deep comprehension of the system dynamics. Furthermore, the possible resonances, which are induced by the action of the external forcing terms, have been identified.

Time-resolved mass injection rates of an outward opening piezo-actuated and a solenoid actuated multi-hole GDI injector were measured to investigate (1) the influence of both hardware and software settings and (2) the influence on the injection rates from a wide range of operational parameters and (3) discuss limitations and issues with this measurement technique. The varied operating parameters were fuel pressure, back-pressure, electrical pulse width, single/double injection and injection frequency. The varied hardware/software parameters were injector protrusion, upstream fuel pressure condition and the cut-off frequency of the software's low-pass filter. Signal quality was found to be dependent on both hardware and software settings, especially the cut-off frequency of the low-pass filter. Measurements with high signal quality were not possible for back-pressures lower than 0.5 MPa.

Sustainable mobility has become a major issue for internal combustion engines and has led to increasing research efforts in the field of alternative fuels, such as bio-fuel, CNG and hydrogen addition, as well as into engine design and control optimization. To that end, a thorough control of the air-to-fuel ratio appears to be mandatory in SI engine in order to meet the even more stringent thresholds set by the current regulations. The accuracy of the air/fuel mixture highly depends on the injection system dynamic behavior and to its coupling to the engine fluid-dynamic. Thus, a sound investigation into the mixing process can only be achieved provided that a proper analysis of the injection rail and of the injectors is carried out. The present paper carries out a numerical investigation into the fluid dynamic behavior of a commercial CNG injection system by means of a 0D-1D code.

Aim of this work is the development of a lumped parameters simulation model of single-vane vacuum pumps for pneumatically actuated brake boosters. Kinematic and fluid-dynamic models are integrated in a simulation environment to create a tool aimed at evaluating the vacuum pump performance and at guiding the designer during the prototype development. The paper describes extensively the mathematical model, the time domain simulation and experimental analyses performed on a camshaft mounted unit. Great emphasis is placed on the evaluation of the geometric quantities of the control volumes into which the vacuum pump has been divided. For each control volume the mass and energy conservation equations lead to the determination of the instantaneous pressure. The volume of each variable chamber and the respective angular derivative are calculated as function of the shaft position starting from the stator track profile supplied as a generic closed polyline.