Search Results

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.

Minimizing the lap time for a given race track is the main target in racecar development. In order to achieve the highest possible performance of the vehicle configuration the mutual interaction at the level of assemblies and components requires a balance between the advantages and disadvantages for each design decision. Especially the major shift in the focus of racecar powerunit development to high efficiency powertrains is driving a development of lean boosted and rightsized engines. In terms of dynamic engine behavior the time delay from requested to provided torque could influence the lap time performance. Therefore, solely maximizing the full load behavior objective is insufficient to achieve minimal lap time. By means of continuous predictive virtual methods throughout the whole development process, the influence on lap time by dynamic power lags, e.g. caused by the boost system, can be recognized efficiently even in the early concept phase.

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.

In this paper the effect of aerodynamic modifications that influence the unsteady aerodynamic properties of a vehicle on the response of the closed loop system driver-vehicle under side wind conditions is investigated. In today's aerodynamic optimization the side wind sensitivity of a vehicle is determined from steady state values measured in the wind tunnel. There, the vehicle is rotated with respect to the wind tunnel flow to create an angle of attack. In this approach however, the gustiness that is inherent in natural wind is not reproduced. Further, unsteady forces and moments acting on the vehicle are not measured due to the limited dynamic response of the commonly used wind tunnel balances. Therefore, a new method is introduced, overcoming the shortcomings of the current steady state approach. The method consists of the reproduction of the properties of natural stochastic crosswind that are essential for the determination of the side wind sensitivity of a vehicle.

Cooling air flow is an important factor when it comes to vehicle performance and operating safety. In addition, it is closely linked to vehicle aerodynamics. In recent years more and more effort is being spent to optimize the losses generated by the flow through the vehicle. Grille shutters, better sealing and ducting are only some examples for innovations in this field of work, resulting in a lower contribution of the cooling air flow to overall drag. But cooling air not only affects the internal flow of the vehicle but also changes the flow around it. This paper will show changes in the flow field around the generic DrivAer model resulting from cooling air flow, especially in the wake behind the car and in the region around the front wheels. The results were gathered using PIV measurements, multi-hole-probe measurements and pitot tube measurements in the 1:4 model scale wind tunnel of IVK University of Stuttgart.

Automotive engineers use the wind tunnel to improve a vehicle’s aerodynamic properties on the road. However, a car driving on the road does not experience the steady-state, uniform flow characteristic of the wind tunnel. Wind, terrain and traffic all cause the flow experienced by the vehicle to be highly transient. Therefore, it is imperative to understand the effects of forces acting on the vehicle resulting from unsteady flow. To this end, the FKFS swing® installed in the University of Stuttgart’s model scale wind tunnel was used to create 36 different incident flow signals with time-resolved yaw angles. The cD values of five different 25% vehicle models, each with a notchback and a squareback configuration, were measured while under the influence of the aforementioned signals. The vehicle models were chosen to ensure a variety of different geometries, but at the same time also to enable isolated comparison of specific geometric properties.

The main objective of the FVV-project “Cylinder Module” was the development of a profoundly modular designed concept for object-oriented modeling of in-cylinder processes of internal combustion engines. It was designed in such a way, that it can either be used as a stand-alone real working-process calculation tool or in tools for whole vehicle simulations. It is possible to run the “Cylinder Module”-code inside the FVV-“GPA”-software for transient vehicle and driving cycle simulations and it is possible to use the graphical user interface “ATMOS” of the “GPA”-project. The code can also be used as a user-subroutine in 1-D-flow simulation codes. Much effort was spent on the requirements of flexibility and expandability in order to be well prepared to cope with the diversity of both today's and future tasks. The code is freely available for members of the German Research Association for Combustion Engines (FVV).

In addition to the analysis of human driving behavior or the development of new advanced driver assistance systems, the high simulation quality of today’s driving simulators enables investigations of selected topics pertaining to driving dynamics. With high reproducibility and fast generation of vehicle variants the subjective evaluation process leads to a better system understanding in the early development stages. The transfer of the original on-road test run to the virtual reality of the driving simulator includes the full flexibility of the vehicle model, the maneuver and the test track, which allows new possibilities of investigation. With the opportunity of a realistic whole-vehicle simulation provided by the Stuttgart Driving Simulator new analysis of the human’s thresholds of perception are carried out.

Turbocharged SI-DI-engines in combination with a reduction of engine displacement (“Downsizing”) offer the possibility to remarkably reduce the overall fuel consumption. In charged mode it is possible to scavenge fresh unburnt air into the exhaust system if a positive slope during the overlap phase of the gas exchange occurs. The matching of the turbo system in SI-engines always causes a trade-off between low-end torque and high power output. The higher mass flow at low engine speeds of an engine using scavenging allows a partial solution of this trade-off. Thus, higher downsizing grades and fuel consumption reduction potential can be obtained. Through scavenging the global fuel to air ratio deviates from the local in-cylinder fuel to air ratio. It is possible to use a rich in-cylinder fuel to air ratio, whereas the global fuel to air ratio remains stochiometrical. This could be very beneficial to reduce the effect of catalytic aging on the one hand and engine knock on the other hand.

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.

This paper deals with the development of a Lap Time Simulator in order to carry out a first approximate evaluation of the potential benefits related to the adoption of the Kinetic Energy Recovery System (KERS). KERS will be introduced in the 2009 Formula 1 Season. This system will be able to store energy during braking and then use it in order to supply an extra acceleration during traction. Different technologies (e.g. electrical, hydraulic and mechanical) could be applied in order to achieve this target. The lap time simulator developed by the authors permits to investigate the advantages both in terms of fuel consumption reduction and the improvement of the lap time.

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.

In the face of growing concerns about environmental sustainability and urban congestion, the integration of eco-driving strategies has emerged as a pivotal solution in the field of the urban transportation sector. This study explores the potential benefits of a CAV functioning as a virtual eco-driving controller in an urban traffic scenario with a group of following human-driven vehicles. A computationally inexpensive and realistic powertrain model and energy management system of the Chrysler Pacifica PHEV are developed with the field experiment data and integrated into a forward-looking vehicle simulator to implement and validate an eco-driving speed planning and energy management strategy assuming longitudinal automation. The eco-driving algorithm determines the optimal vehicle speed profile and energy management strategy.

The hybrid power train technology offers various prospects to optimize the engine efficiency in order to minimize the CO₂ emissions of an internal-combustion-engine-powered vehicle. Today different types of hybrid architectures like parallel, serial, power split or through-the-road concepts are commonly known. To achieve lowest fuel consumption the following hybrid electric vehicle drive modes can be used: Start/Stop, pure electric/thermal driving, recuperation of brake energy and the hybrid mode. The high complexity of the interaction between those power sources requires an extensive investigation to determine the optimal configuration of a natural-gas-powered SI engine within a parallel hybrid power train. Therefore, a turbocharged 1.0-liter 3-cylinder CNG engine was analyzed on the test bench. Using an optimized combustion strategy, the engine was operated at stoichiometric and lean air/fuel ratio applying both high- and low-pressure EGR.

Sustainable and energy-efficient consumption is a main concern in contemporary society. Driven by more stringent international requirements, automobile manufacturers have shifted the focus of development into new technologies such as Hybrid Electric Vehicles (HEVs). These powertrains offer significant improvements in the efficiency of the propulsion system compared to conventional vehicles, but they also lead to higher complexities in the design process and in the control strategy. In order to obtain an optimum powertrain configuration, each component has to be laid out considering the best powertrain efficiency. With such a perspective, a simulation study was performed for the purpose of minimizing well-to-wheel CO2 emissions of a city car through electrification. Three different innovative systems, a Series Hybrid Electric Vehicle (SHEV), a Mixed Hybrid Electric Vehicle (MHEV) and a Battery Electric Vehicle (BEV) were compared to a conventional one.

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.

Driving simulators allow the testing of driving functions, vehicle models and acceptance assessment at an early stage. For a real driving experience, it's necessary that all immersions are depicted as realistically as possible. When driving manually, the perceived haptic steering wheel torque plays a key role in conveying a realistic steering feel. To ensure this, complex multi-body systems are used with numerous of parameters that are difficult to identify. Therefore, this study shows a method how to generate a realistic steering feel with a nonlinear open-loop model which only contains significant parameters, particularly the friction of the steering gear. This is suitable for the steering feel in the most driving on-center area. Measurements from test benches and real test drives with an Electric Power Steering (EPS) were used for the Identification and Validation of the model.