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A precise estimation of the recirculated exhaust gas rate and oxygen concentration as well as a predictive evaluation of the possible EGR unbalance among cylinders are of paramount importance, especially if non-conventional combustion modes, which require high EGR flow-rates, are implemented. In the present paper, starting from the equation related to convergent nozzles, the EGR mass flow-rate is modeled considering the pressure and the temperature upstream of the EGR control valve, as well as the pressure downstream of it. The restricted flow-area at the valve-seat passage and the discharge coefficient are carefully assessed as functions of the valve lift. Other models were fitted using parameters describing the engine working conditions as inputs, following a semi-physical and a purely statistical approach. The resulting models are then applied to estimate EGR rates to both conventional and non-conventional combustion conditions.

The paper deals with the virtual and experimental analysis of two commercial Mechanical Brake Assist systems. They are described in detail, then modeled and experimentally evaluated through a Hardware-In-the-Loop test bench and road tests. Three different kinds of drivers are compared, from the point of view of the performance increase promised by Brake Assist during an emergency brake maneuver. The three driver types are based on the measurement of the behavior of real drivers, as it is presented in specific research activities in literature.

In Motorsports the understanding of the real engine performance within a complete circuit lap is a crucial topic. On the basis of the telemetry data the engineers are able to monitor this performance and try to adapt the engine to the vehicle's and race track's characteristics and driver's needs. However, quite often the telemetry is the sole analysis instrument for the Engine-Vehicle-Driver (EVD) system and it has no prediction capability. The engine optimization for best lap-time or best fuel economy is therefore a topic which is not trivial to solve, without the aid of suitable, reliable and predictive engineering tools. A complete EVD model was therefore built in a GT-SUITE™ environment for a Motorsport racing car (STCC-VW-Scirocco) equipped with a Compressed Natural Gas (CNG) turbocharged S.I. engine and calibrated on the basis of telemetry and test bench data.

Vehicle dynamics estimation has been the subject of study for some years now. If on-board vehicle control systems can be provided with information such as side slip angle, lateral force etc. then stability of the vehicle can be improved. To estimate these dynamic variables different observers have been used e.g., sliding mode, fuzzy logic, neural networks etc. In this article the authors propose an extended Kalman filter to estimate vehicle side slip angle. Roll angle is estimated using vertical loads as input. First, a linear Kalman filter is used to filter out the vertical forces and estimate roll angle. This information is then used to estimate the vehicle side slip angle. To take into account the nonlinearities concerning lateral vehicle dynamics, Pacejka magic formula is used to model lateral forces. Estimated results are then compared with simulations, showing good accuracy.

Active Roll Control (ARC) is one of the most promising active systems to improve vehicle comfort and handling. This paper describes the simulation based procedure adopted to conceive a double-channel Active Roll Control system, characterized by the hydraulic actuation of the stabilizer bars of a sedan. The first part of the paper presents the vehicle model adopted for this activity. It is Base Model Simulator (BMS), the 14 Degrees-of-Freedom vehicle model by Politecnico di Torino. It was validated through road tests. Then the paper describes the development of the control algorithm adopted to improve the roll dynamics of the vehicle. The implemented control algorithm is characterized by a first subsystem, capable of obtaining the desired values of body roll angle as a function of lateral acceleration during semi-stationary maneuvers.

The frequency spectral structure of turbulence spatial components was investigated in the cylinder of an automotive diesel engine with a high-squish reentrant in-piston bowl of the conical type and a helical inlet port. A sophisticated HWA technique using single- and dual-sensor probes was applied for instantaneous air velocity measurements along the injector axis at practical engine speeds, up to 3000 rpm, under motored conditions. The investigation was carried out for both cycle-resolved and conventional turbulence components, as were determined by different wire orientations, throughout the induction, the compression and the early stage of the expansion stroke. The anisotropy of turbulence spectral structure and its temporal evolution during the engine cycle were examined by evaluating the autospectral density functions and the time scales of each turbulence component in consecutive correlation crank-angle intervals.

The potential of an electric assisted turbocharger for a heavy-duty diesel engine has been analyzed in this work, in order to evaluate the turbo-lag reductions and the fuel consumption savings that could be obtained in an urban bus for different operating conditions. The aim of the research project was to replace the current variable geometry turbine with a fixed geometry turbine, connecting an electric machine which can be operated both as an electric motor and as an electric generator to the turbo shaft. The electric motor can be used to speed up the turbocharger during the acceleration transients and reduce the turbo-lag, while the generator can be used to recover the excess exhaust energy when the engine is operated near the rated speed, in order to produce electrical power that can be used to drive engine auxiliaries. In this way the engine efficiency can be improved and a kind of “electric turbocompounding” can be obtained.

The DEXA Cluster consisted of three closely interlinked projects. In 2003 the DEXA Cluster concluded by demonstrating the successful development of critical technologies for Diesel exhaust particulate after-treatment, without adverse effects on NOx emissions and maintaining the fuel economy advantages of the Diesel engine well beyond the EURO IV (2000) emission standards horizon. In the present paper the most important results of the DEXA Cluster projects in the demonstration of advanced particulate control technologies, the development of a simulation toolkit for the design of diesel exhaust after-treatment systems and the development of novel particulate characterization methodologies, are presented. The motivation for the DEXA Cluster research was to increase the market competitiveness of diesel engine powertrains for passenger cars worldwide, and to accelerate the adoption of particulate control technology.

In the present work, different combustion control strategies have been experimentally tested in a heavy-duty 3.0 L Euro VI diesel engine. In particular, closed-loop pressure-based and open-loop model-based techniques, able to perform a real-time control of the center of combustion (MFB50), have been compared with the standard map-based engine calibration in order to highlight their potentialities. In the pressure-based technique, the instantaneous measurement of in-cylinder pressure signal is performed by a pressure transducer, from which the MFB50 can be directly calculated and the start of the injection of the main pulse (SOImain) is set in a closed-loop control to reach the MFB50 target, while the model-based approach exploits a heat release rate predictive model to estimate the MFB50 value and sets the corresponding SOImain in an open-loop control. The experimental campaign involved both steady-state and transient tests.

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.

Simulation is becoming the fundamental tool to design the main components of a vehicle. The paper describes the shock absorber model which was implemented by the Vehicle Dynamics Research Team of Politecnico di Torino. It is a modular model which can be adopted both for mono-tube and twin-tube shock absorbers. It can be used at different levels of approximation, as a function of the kind of user and his/her targets. The main data which have to be inserted in the model are fluid properties, the basic dimensions of the component and the characteristics of the orifices of the shock absorber. An experimental test bench was conceived to obtain the diagrams plotting flow rate through an orifice of a shock absorber versus the pressure drop between input and output ports. The test rig and the procedure to perform the experimental tests and insert the results in the shock absorber model are described in detail.

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.

Designing automobile brake systems is generally complex and time consuming. Indeed, the brake system integrates several components and has to satisfy numerous conflicting government regulations. Due to these constraints, designing an optimal configuration is not easy. This paper consequently proposes a simple, intuitive and automated methodology that enables rapid optimal design of light vehicle hydraulic brake systems. Firstly, the system is modeled through cascaded analytical equations for each component. A large design space is then generated by varying the operational parameters of each component in its specific reasonable range. The system components under consideration include the brake pedal, the master cylinder, the vacuum-assisted booster, the brake line and the brake pistons. Successful system configurations are identified by implementing the requirements of the two most relevant safety homologation standards for light vehicle brake systems (US and EU legislations).

Given the ever-increasing concern about environmental issues, the automotive industry is focusing on the development of innovative technologies that allow reduction of gas emissions and fuel consumption. Over the last few years, Hybrid Electric Vehicles (HEV) and Fuel Cell Vehicles have been developed as the most promising alternative solutions for many car manufacturers. Although fuel cells are considered as the best technology to have zero emission, the impact on infrastructure for a large-scale deployment is not yet solved. For this reason, HEV represent a valid shorter-term alternative that guarantees drastic emissions reduction and reduced fuel consumption with a much lower infrastructural impact. This paper reports the results obtained by the optimization of the emissions and fuel performances of a hybrid electric city vehicle for urban transportation named XAM (eXtreme Automotive Mobility). In order to optimize these performances, a 1D model of the vehicle has been created.

A fuel-cell-based system's performance is mainly identified in the overall efficiency, strongly depending on the amount of power losses due to auxiliary devices to supply. In such a situation, everything that causes either a decrease of the available power output or an increment of auxiliary losses would determine a sensible overall efficiency reduction.

Electric vehicles comprising multiple motors allow the individual wheel torque allocation, i.e. torque-vectoring. Powertrain configurations with multiple motors provide additional degree of freedom to improve system level efficiencies while ensuring handling performances and active safety. However, most of the works available on this topic do not simultaneously optimize both vehicle dynamic performance and energy efficiency while considering the real-time implementability of the controller. In this work, a new and systematic approach in designing, modeling, and simulating the main layers of a torque-vectoring control framework is introduced. The high level control combines the actions of an adaptive Linear Quadratic Regulator (A-LQR) and of a feedforward controller, to shape the steady-state and transient vehicle response by generating the reference yaw moment. A novel energy efficient torque allocation method is proposed as a low level controller.

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.

An experimental investigation on a group of unleaded gasolines of different chemical composition has been carried out, in order to analyze their knock behaviour in a mass-produced engine at high revolution speed, to highlight possible inconsistencies with their standard Research and Motor octane numbers and to try to discover explanations for the abovementioned inconsistencies. The investigation has been focused on fuels containing oxygenated compounds, such as alcohols (methanol and ethanol) and ethers (MTBE), with the aim of pointing out the influence of the fuel composition on the octane rating, especially as far as the variation in the stoichiometric air/fuel ratio (due to oxygenated compounds blending) is concerned. In particular, the rating of all the fuels under the same relative air/fuel ratio has shown to be a mandatory condition in order to obtain a proper estimate of antiknock performances. The evaluations obtained are consistent with the standard Motor octane numbers.

The target for future cooling systems is to control the fluid temperatures and flows through a demand oriented control of the engine cooling to minimize energy demand and to achieve comfort, emissions, or service life advantages. The scope of this work is to create a complete engine thermal model (including both cooling and lubrication circuits) able to reproduce engine warm up along the New European Driving Cycle in order to assess the impact of different thermal management concepts on fuel consumption. The engine cylinder structure was modeled through a finite element representation of cylinder liner, piston and head in order to simulate the cylinder heat exchange to coolant or oil flow circuits and to predict heat distribution during transient conditions. Heat exchanges with other components (EGR cooler, turbo cooler, oil cooler) were also taken into account.

Hybrid electric vehicles (HEVs) represent a fundamental step in the global evolution towards transportation electrification. Nevertheless, they exhibit a remarkably complex design environment with respect to both traditional internal combustion engine vehicles and battery electric vehicles. Innovative and advanced design tools are therefore crucially required to effectively handle the increased complexity of HEV development processes. This paper aims at providing a comprehensive overview of past and current advancements in HEV powertrain design methodologies. Subsequently, major simplifications and limits of current HEV design methodologies are detailed. The final part of this paper defines research challenges that need accomplishment to develop the next generation HEV architecture design tools.