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Mathematical models of a torque sensor equipped crankshaft in a light-duty diesel engine are identified, validated, and compared. The models are based on in-cylinder pressure and crankshaft torque data collected from a 5-cylinder common-rail diesel engine running at multiple operating points. The work is motivated by the need of a crankshaft model in a closed-loop combustion control system based on crankshaft torque measurements. In such a system a crankshaft model is used in order to separate the measured crankshaft torque into cylinder individual torque contributions. A method for this is described and used for IMEP estimation. Not surprisingly, the results indicate that higher order models are able to estimate crankshaft torque more accurately than lower order models, even if the differences are small. For IMEP estimation using the cylinder separation method however, these differences have large effects on accuracy.

The paper describes a novel method for calculating the residual gas fraction and the trapping efficiency in a 2 stroke engine. Assuming one dimensional compressible flow through the inlet and exhaust ports, the method estimates the instantaneous mass flowing in and out from the combustion chamber; later the residual gas fraction and trapping efficiency are estimated combining together the perfect displacement and perfect mixing scavenging models. It is assumed that when the intake port opens, the fresh mixture is pushing out the burned charge without any mixing and after a multiple of the time needed for the largest eddy to perform one rotation, the two gasses are instantly mixed up together and expelled. The result is a very simple algorithm that does not require much computational time and is able to estimate with high level of precision the trapping efficiency and the residual gas fraction in 2 stroke engines.

This paper presented a part of results from an ongoing project for pedestrian protection, which is carried out at Chalmers University of Technology in Sweden. A validated pedestrian mathematical model was used in this study to simulate vehicle-pedestrian impacts. A large number of simulations have been carried out with various parameters. The injury-related parameters concerning head, chest, pelvis and lower extremities were calculated to evaluate the effect of impact speed and vehicle front structure on the risk of pedestrian injuries. The effect of following vehicle parameters was studied: stiffness of bumper, hood edge, hood top, windscreen frame, and shape of vehicle front structures. A parameter study was conducted by modelling vehicle-pedestrian impacts with various sizes of cars, mini vans, and light trucks. This choice represents the trends of new vehicle fleet and their frequency of involvement in real world accidents.

A comparison of scanning mobility particle sizer (SMPS) and laser-induced incandescence (LII) measurements of diesel particulate matter (PM) was performed. The results reveal the significance of the aggregate nature of diesel PM on interpretation of size and volume fraction measurements obtained with an SMPS, and the accuracy of primary particle size measurements by LII. Volume fraction calculations based on the mobility diameter measured by the SMPS substantially over-predict the space-filling volume fraction of the PM. Correction algorithms for the SMPS measurements, to account for the fractal nature of the aggregate morphology, result in a substantial reduction in the reported volume. The behavior of the particulate volume fraction, mean and standard deviation of the mobility diameter, and primary particle size are studied as a function of the EGR for a range of steady-state engine speeds and loads for a turbocharged direct-injection diesel engine.

A two-state forward dynamic programming algorithm is evaluated in a series hybrid drive-train application with the objective to minimize fuel consumption when look-ahead information is available. The states in the new method are battery state-of-charge and engine speed. The new method is compared to one-state dynamic programming optimization methods where the requested generator power is found such that the fuel consumption is minimized and engine speed is given by the optimum power-speed efficiency line. The other method compared is to run the engine at a given operating point where the system efficiency is highest, finding the combination of engine run requests over the drive-cycle that minimizes the fuel consumption. The work has included the engine torque and generator power as control signals and is evaluated in a full vehicle-simulation model based on the Volvo Car Corporation VSIM tool.

Flow visualization techniques are widely used in aerodynamics to investigate the surface trace pattern. In this experimental investigation, the surface flow pattern over the rear end of a full-scale passenger car is studied using tufts. The movement of the tufts is recorded with a DSLR still camera, which continuously takes pictures. A novel and efficient tuft image processing algorithm has been developed to extract the tuft orientations in each image. This allows the extraction of the mean tuft angle and other such statistics. From the extracted tuft angles, streamline plots are created to identify points of interest, such as saddle points as well as separation and reattachment lines. Furthermore, the information about the tuft orientation in each time step allows studying steady and unsteady flow phenomena. Hence, the tuft image processing algorithm provides more detailed information about the surface flow than the traditional tuft method.

This paper reports on a fast predictive combustion tool employing detailed chemistry. The model is a stochastic reactor based, discretised probability density function model, without spatial resolution. Employing detailed chemistry has the potential of predicting emissions, but generally results in very high CPU costs. Here it is shown that CPU times of a couple of minutes per cycle can be reached when applying detailed chemistry, and CPU times below 10 seconds per cycle can be reached when using reduced chemistry while still catching in-cylinder in-homogeneities. This makes the tool usable for efficient engine performance mapping and optimisation. To meet CPU time requirements, automatically load balancing parallelisation was included in the model. This allowed for an almost linear CPU speed-up with number of cores available.

In this paper a fast NOx model is presented which can be used for engine optimization, aftertreatment control or virtual mapping. A cylinder pressure trace is required as input data. High calculation speed is obtained by using table interpolation to calculate equilibrium temperatures and species concentrations. Test data from a single-cylinder engine and from a complete six-cylinder engine have been used for calibration and validation of the model. The model produces results of good agreement with emission measurements using approximately 50 combustion product zones and a calculation time of one second per engine cycle. Different compression ratios, EGR rates, injection timing, inlet pressures etc. were used in the validation tests.

Previous studies have shown that car seat properties play an important role for the occupant protection during various types of accidents. An improved understanding of the interaction between the occupant and the seat is therefore desirable, since this could lead to enhanced protective capacities of future car seats. In this work a test-rig has been developed and constructed, by means of which it is possible to study the response from various seats during frontal collisions. With small modifications the test-rig can be utilized to study other collision directions as well. The rig has been used in a test series, which comprises four car seats in altogether 14 tests. In order to evaluate the interaction between the seat and the dummy, measurements have been made on: the seat frame; the floor connections; the seat belt; the submarine-beam; and on several locations in the dummy.

This paper describes results from fault injection experiments using heavy ions in the time-triggered communication protocol for safety critical distributed systems (TTP/C, C1 implementation). The observed results show that arbitrary faults in one erroneous node could cause inconsistencies in the cluster and thus jeopardize correctly working nodes and the whole communication system. The described inconsistencies resulted from either asymmetric value faults or slightly out of specification timing faults. This system behavior can be partly explained by too strict constraints on the fault handling algorithms using the membership agreement protocol.

The shearing and bending injury mechanisms of the knee joint are recognised as two important injury mechanisms associated with car-pedestrian crash accidents. A study on shearing and bending response of the knee joint to a lateral impact loading was conducted with a 3D multibody system model of the lower extremity. The model consists of foot, leg and thigh with concentrated upper body mass. The body elements are connected by joints, including an anatomical knee joint unit that consists of the femur condyles, tibia condyles and tibia1 intercondylar eminence as well as ligaments. The biomechanical properties of the model were derived from literature data. The model was used to simulate two series of previously performed experiments with lower extremity specimens at lateral impact speeds of 15 and 20 km/h.

Worldwide, there is the demand to reduce harmful emissions from non-road vehicles to fulfill European Stage V+ and VI (2022, 2024) emission legislation. The rules require significant reductions in nitrogen oxides (NOx), methane (CH4) and formaldehyde (CH2O) emissions from non-road vehicles. Compressed natural gas (CNG) engines with appropriate exhaust aftertreatment systems such as three-way catalytic converter (TWC) can meet these regulations. An issue remains for reducing emissions during the engine cold start where the CNG engine and TWC yet do not reach their optimum operating conditions. The resulting complexity of engine and catalyst calibration can be efficiently supported by numerical models. Hence, it is required to develop accurate simulation models which can predict cold start emissions. This work presents a real-time engine model for transient engine-out emission prediction using tabulated chemistry for CNG.

48V mild hybrid powertrains are promising technologies for cost-effective compliance with future CO2 emissions standards. Current 48V powertrains with integrated belt starter generators (P0) with downsized engines achieve CO2 emissions of 95 g/km in the NEDC. However, to reach 75 g/km, it may be necessary to combine new 48V powertrain architectures with alternative fuels. Therefore, this paper compares CO2 emissions from different 48V powertrain architectures (P0, P1, P2, P3) with different electric power levels under various driving cycles (NEDC, WLTC, and RTS95). A numerical model of a compact class passenger car with a 48V powertrain was created and experimental fuel consumption maps for engines running on different fuels (gasoline, Diesel, E85, CNG) were used to simulate its CO2 emissions. The simulation results were analysed to determine why specific powertrain combinations were more efficient under certain driving conditions.

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.

We describe experiments and numerical modeling of snow surface contamination on two simplified automotive bluff bodies: The Ahmed body and a wedge. The purpose was twofold: 1) To obtain well defined experimental results of snow contamination on simple geometries; 2) To propose a numerical modeling approach for snow contamination. The experiments were performed in a climatic wind tunnel using a snow cannon at −15 °C and the results show that the snow accumulation depends on the aerodynamics of the studied bluff bodies. Snow accumulates on surfaces in proximity to the aerodynamic wakes of the bodies and characteristic snow patterns are obtained on side surfaces. The numerical modeling approach consisted of an aerodynamic setup coupled with Lagrangian particle tracking. Particles were determined to adhere or rebound depending on an adhesion model combined with a resuspension criterion.