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Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

The world of automotive engineering shows a clear direction for upcoming development trends. Stringent fleet average fuel consumption targets and CO2 penalties as well as rising fuel prices and the consumer demand to lower operating costs increases the engineering efforts to optimize fuel economy. Passenger car engines have the benefit of higher degree of technology which can be utilized to reach the challenging targets. Variable valve timing, downsizing and turbo charging, direct gasoline injection, highly sophisticated operating strategies and even more electrification are already common technologies in the automotive industry but can not be directly carried over into a motorcycle application. The major differences like very small packaging space, higher rated speeds, higher power density in combination with lower production numbers and product costs do not allow implementation such high of degree of advanced technology into small-engine applications.

This paper describes an analysis of the Diesel Oil Surrogate (DOS) model used at Chalmers University (Sweden), including 70 species participating in 310 reactions, and subsequent improvements prompted by the model's systematic tendency to under-predict the combustion intensity in simulations of kinetically-driven combustion modes, e.g. Homogeneous Charged Compression Ignition (HCCI). Key bases of the model are the properties of a model Diesel fuel with the molecular formula C14H28. In the vapor phase, a global reaction decomposes the starting fuel, C14H28, into its constituent components; n-heptane (C7H16) and toluene (C7H8). This global reaction was modified to yield a higher n-heptane:toluene ratio, due to the importance of preserving an n-heptane-like cetane number.

The incorporation of a detailed engine process calculation that takes into account thermal behavior of the engine and exhaust system is essential for a realistic simulation of transient vehicle operation. This is the only possible way to have a precise preliminary calculation of fuel consumption and emissions. Therefore, a comprehensive thermal network of the engine based on the lumped capacity method has been developed. The model allows the computation of component temperatures in steady state operation as well as in transient engine studies, e.g. investigations of engine warm-up. The model is integrated in a co-simulation environment consisting of a detailed vehicle and engine cycle simulation code. The paper describes the procedure of the co-simulation and presents several examples of warm-up simulations.

The aim of this study was to examine the influence of computer manikin users' background and knowledge for the results of a computer manikin simulation. Subjects taking part in the study were either production engineers or ergonomists. A manual task that presented production and ergonomics problems was used. The task was simulated prior to the subjects' sessions, using the computer manikin software Jack. During the sessions, the animated simulation was shown to the test subject. Results show that there are differences in how production engineers and ergonomists interpret results from a manikin simulation. Depending on the user's background, certain aspects that are difficult to visualise with the computer manikin were interpreted differently, regarding e.g. detected problems and holistic perspectives.

The well-to-wheel CO2 emissions and energy use of internal combustion engines (diesel and gasoline) are compared to fuel cell automotive propulsion systems. The fuel cell technologies investigated are polymer electrolyte fuel cell (PEFC), alkaline fuel cell (AFC) and solid oxide fuel cell (SOFC). The fuels are assumed to be produced from either crude oil or natural gas. The comparison is based on driving cycle simulations of a mid-class passenger car with an inertia test weight of 1350 kg. The study shows that the optimized diesel drive train (downsized mated to an integrated starter generator) achieves the best overall energy efficiency. The lowest CO2 emissions are produced by compressed natural gas (CNG) vehicles. Fuel cell propulsion systems achieve similar or even better CO2 emission values under hot start conditions but suffer from high energy input required during warm-up.

In order to improve the accuracy of vehicle simulation under transient cycle conditions and thus predict performance and fuel consumption, consideration of the complete system engine/drivetrain/vehicle is necessary. The coupling of otherwise independent simulation programs is therefore necessary for the vehicle and engine. The description of thermally transient processes enables the calculation of the heat balance of the engine, which in turn enables the simulation of warming up operation. Through consideration of the engine warming up process, the quality of the prediction of fuel consumption and emissions is improved. The combination of the simulation programs CRUISE and BOOST to determine the engine heat balance has proven to be successful for the analysis of transient drive cycles.

The ability to adapt to rapidly evolving market demands continues to be the one of the key challenges in the automation of assembly processes in the aerospace industry. To meet this challenge, industry and academia have made efforts to automate flexible fixturing. LOCOMACHS (Low Cost Manufacturing and Assembly of Composite and Hybrid Structures) - a European Union funded project with 31 partners - aims to address various aspects of aero-structure assembly with a special attention directed to the development of a new build philosophy along with relevant enabling technologies. This paper aims to present the results on the developed wing box build philosophy and the integration of automated flexible tooling solutions into the assembly process. The developed solution constitutes the use of synchronized hexapods for the assembly of front spar to upper cover whereas another hexapod was developed to install a rib by using of a force feedback sensor.

An engine model for use in computer simulation of transient behavior in drivetrain and vehicle systems is presented. Two elements, important for deviation (e.g. turbo-lag) from steady state characteristics, are the inertia of the supercharging unit (turbo shaft) and the fuel injection control system. No extensive combustion calculations are carried out within the model. Instead it uses condensed results from existing combustion models and measurements. The model is semi-empirical. Some of the engine specific properties needed for simulation are (e.g. for a turbocharged diesel): engine data in steady state operation, mappings of compressor and turbine performance, inertia of the engine components condensed to the crankshaft, turbo shaft inertia, displacement, compression ratio and the essentials of the fuel injection control strategy. Input parameters to the computer program based on the model are accelerator pedal position and external torque acting on the flywheel.

The paper describes a feasibility test program on a 2 liter, 4 cylinder DI/TCI passenger car engine operated on the new alternative fuel Dimethyl Ether (DME, CH3 - O - CH3) with the aim of demonstrating its potential of meeting ULEV emissions (0.2 g/mi NOx in the FTP 75 test cycle) when installed in a full size passenger car. Special attention is drawn to the fuel injection equipment (FIE) as well as combustion system requirements towards the reduction of NOx and combustion noise while keeping energetic fuel consumption at the level of the baseline DI/TCI diesel engine. FIE and combustion system parameters were optimized on the steady state dynamometer by variation of a number of parameters, such as rate of injection, number of nozzle holes, compression ratio, piston bowl shape and exhaust gas recirculation.

This paper presents an overview of the results on heavy duty engines collected in the “PARTICULATES” project, which aimed at the characterization of exhaust particle emissions from road vehicles. The same exhaust gas sampling and measurement system as employed for the measurements on light duty vehicles [1] was used. Measurements were made in three labs to evaluate a wide range of particulate properties with a range of heavy duty engines and fuels. The measured properties included particle number, with focus separately on nucleation mode and solid particles, particle active surface and total mass. The sample consisted of 10 engines, ranging from Euro-I to prototype Euro-V technologies. The same core diesel fuels were used as in the light duty programme, mainly differentiated with respect to their sulphur content. Additional fuels were tested by some partners to extend the knowledge base.

The rapidly growing complexity and the growing cross linking of powertrain components leads to longer development times, especially in the vehicle calibration process. The number of systems which need to be fitted to each other and the number of parameters to be calibrated in the particular systems are increasing tremendously. The extensive use of simulation promises to reduce the calibration effort by providing pre-optimized parameter sets. This paper describes a new simulation methodology by the interlinking of advanced vehicle simulation and evaluation tools, in particular the AVL-tools CRUISE, VSM and DRIVE. This methodology allows to semi automatically pre-optimize powertrain and vehicle parameters before hardware is involved. So far the pre-calibration of vehicle and powertrain parameters by simulation was not satisfying because of the missing of a reliable evaluation tool for the produced simulation results.

For the development of complex control algorithms and strategies the engine and powertrain test bed offers a number of advantages over the development in the prototype vehicle. The paper discusses how state-of-the-art simulation techniques can contribute to a continuous development process, which is based upon offline simulation using hardware in the loop, the utilization of modern test bed technology up to vehicle adjustment. The integration of hardware-in-the-loop testing together with vehicle and transmission simulation on the testbed allows to speed up the optimization of fuel consumption, emissions and driveability in an early stage in the development process. The available software tools are presented and application examples are given.

Best fuel efficiency is one of the core requirements for commercial vehicles in India. Consequently it is a central challenge for commercial vehicle OEMs to optimize the entire powertrain, hence match engine, transmission and rear axle specifications best to the defined application. The very specific real world driving conditions in India (e.g. traffic situations, road conditions, driver behavior, etc.) and the large number of possible commercial powertrain combinations request an efficient and effective development methodology. This paper presents a methodology and tool chain to specify and develop commercial powertrains in a most efficient and effective way. The methodology is based on the measurement of real world driving scenarios, identification of representative Real World Driving Profiles and vehicle system simulation which allows extended analysis of the road topography, the traffic situation as well as the driver behavior.

Increasing powertrain complexity and the growing number of vehicle variants are putting a strain on current calibration development processes. This is particularly challenging for vehicle drivability calibration, which is traditionally completed late in the development cycle, only after mature vehicle hardware is available. Model-based calibration enables a shift in development tasks from the real world to the virtual world, allowing for increased system robustness while reducing development costs and time. A unique approach for drivability calibration was developed by incorporating drivability analysis software with online optimization software into a virtual engine test cell environment. Real-time, physics-based engine and vehicle simulation models were coupled with real engine controller hardware and software to execute automated drivability calibration within this environment.

The current work investigates a method in 1D modeling of cooling systems including discretized cooling package with non-uniform boundary conditions. In a stacked cooling package the heat transfer through each heat exchanger depends on the mass flows and temperature fields. These are a result of complex three-dimensional phenomena, which take place in the under-hood and are highly non-uniform. A typical approach in 1D simulations is to assume these to be uniform, which reduces the authenticity of the simulation and calls for additional calibrations, normally done with input from test measurements. The presented work employs 3D CFD simulations of complete vehicle in STAR-CCM+ to perform a comprehensive study of mass-flow and thermal distribution over the inlet of the cooling package of a Volvo FM commercial vehicle in several steady-state operating points.

The automotive industry continues to increase the utilization of computer-aided engineering. This put demands on finding reliable objective measures that correlate to subjective driver assessments on driving stability performance. However, the drivers’ subjective perception of driving stability can be difficult to quantify objectively, especially on test tracks where the wind conditions cannot be controlled. The advancement in driving simulator technology may enable evaluation of driving stability with high repeatability. The purpose of this study is to correlate the subjective assessment of driving stability to reliable objective measures and to evaluate the usefulness of a driving simulator for the subjective assessment. Two different driver clinic studies were performed in a state-of-the-art driving simulator. The first study included 38 drivers (professional, experienced and common drivers) and focused on crosswind gust sensitivity.

In vehicle development, a subjective evaluation of the vehicle’s behavior at high speeds is usually conducted by experienced drivers with the objective of assessing driving stability. To avoid late design changes, it is desirable to predict and resolve perceived instabilities early in the development phase. In this study, a mathematical model is developed from measurements during on-road tests to predict the driver’s ability to identify vehicle instabilities under excitations such as aerodynamic excitations. A vehicle is fitted with add-ons to create aerodynamic excitations and is driven by multiple drivers on a high-speed track. Drivers’ evaluation, responses, cabin motion, and crosswind conditions are recorded. The influence of yaw and roll rates, lateral acceleration, and steering angle at various frequency ranges when predicting the drivers’ evaluation of induced excitation is demonstrated. The drivers’ evaluation of vehicle behavior is influenced by driver-vehicle interactions.