Search Results

Bushing elasticity is one of the most important compliance factors that significantly influence driving behavior. The deformations of the bushings change the wheel orientations under external forces. Another important factor of bushing compliance is to provide a comfortable driving experience by isolating the vibrations from road irregularities. However, the driving comfort and driving dynamics are often in conflict and need to be balanced in terms of bushing compliance design. Specifically, lateral force steer and brake force steer are closely related to safety and stability and comprises must be minimized. The sensitivity analysis helps engineers to understand the critical bushing for certain compliance attributes, but optimal balancing is complicated to understand. The combination of individual bushing stiffness must be carefully set to achieve an acceptable level of all the attributes.

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.

Heavy-duty vehicles are primarily powered by diesel fuel, emitting CO2 emissions regardless of the exhaust after-treatment system. Contrastingly, a hydrogen engine has the potential to decarbonize the transportation sector as hydrogen is a carbon free, renewable fuel. In this study, a multi-physics 1D simulation tool (GT-Power) is used to model the gas exchange process and performance prediction of a two-stroke hydrogen engine. The aim is to establish a maximum torque-level for a four-stroke hydrogen engine and then utilize different methods for two-stroke modeling to achieve similar torque by optimizing the gas exchange process. A camless engine is used as base, enabling the flexibility to utilize approximately square valve lift profiles. The preliminary step is the GT-Power model validation, which has been done using diesel and hydrogen engines (single-cylinder heavy-duty) experiments at different operating points (871 rpm, 1200 rpm, 1259 rpm, and 1508 rpm).

Wind tunnels are an essential tool in vehicle development. To simulate the relative velocity between the vehicle and the ground, wind tunnels are typically equipped with moving ground and boundary layer control systems. For passenger vehicles, wind tunnels with five-belt systems are commonly used as a trade-off between accurate replication of the road conditions and uncertainty of the force measurements. To allow different tyre sizes, the wheel drive units (WDUs) can often be fitted with belts of various widths. Using wider belts, the moving ground simulation area increases at the negative cost of larger parasitic lift forces, caused by the connection between the WDUs and the balance. In this work, a crossover SUV was tested with 280 and 360mm wide belts, capturing forces, surface pressures and flow fields. For further insights, numerical simulations were also used.

Squeak and rattle (S&R) are nonstationary annoying and unwanted noises in the car cabin that result in considerable warranty costs for car manufacturers. Introduction of cars with remarkably lower background noises and the recent emphasis on electrification and autonomous driving further stress the need for producing squeak- and rattle-free cars. Automotive manufacturers use several road disturbances for physical evaluation and verification of S&R. The excitation signals collected from these road profiles are also employed in subsystem shaker rigs and virtual simulations that are gradually replacing physical complete vehicle test and verification. Considering the need for a shorter lead time and the introduction of optimisation loops, it is necessary to have efficient and inclusive excitation load cases for robust S&R evaluation.

This paper presents a model based control strategy aimed to reduce noise and wear during gearshifts in conventional and hybrid Dual Clutch Transmissions (DCT and DCTH) and Automated Manual Transmissions (AMT). The control strategy is based on a newly developed dog teeth position sensor layout at China Euro Vehicle Technology AB (CEVT), a detailed simulation model for gear engagement and already existing speed sensors in the transmission. The details of dog teeth position sensor and simulation model are also presented in this paper. During gear shifting, noise is generated because of impacts between the sleeve teeth and the idler gear dog teeth after speed synchronization. Besides noise, these impacts are also responsible for delaying the completion of shift and contribute to wear in the dog teeth, hence reducing the lifespan of the transmission. The simulation model for gear engagement can simulate these impacts.

Modelling is widely used for the development of hybrid electric vehicle (HEV) powertrain technologies, since it can provide accurate prediction of fuel consumption and CO₂ emissions, for a fraction of the resources required in experiments. For comparison of different technologies or powertrain parameters, the results should be accurate relative to each other, since powertrains are simulated under identical model details and simulation parameters. However, when CO₂ emissions of a vehicle model are simulated under a driving cycle, significant deviances may occur between actual tests and simulation results, compromising the integrity of simulations. Therefore, this paper investigates the effects of certain modelling and simulation parameters on CO₂ emission results, for a parallel HEV under three driving cycles (NEDC, WLTC and RTS95 to simulate real driving emissions (RDE)).

The present paper aims at developing an innovative procedure to create a one-dimensional (1D) real-time capable simulation model for a heavy-duty diesel engine. The novelty of this approach is the use of the top-level engine configuration, test cell measurement data, and manufacturer maps as opposite to common practice of utilizing a detailed 1D engine model. The objective is to facilitate effective model adjustments and hence further increase the application of Hardware-in-the-Loop (HiL) simulations in powertrain development. This work describes the development of Fast Running Model (FRM) in GT-SUITE simulation software. The cylinder and gas-path modeling and calibration are described in detail. The results for engine performance and exhaust emissions produced satisfactory agreement with both steady-state and transient experimental data.

In order to meet emissions and power requirements, modern engine design has evolved in complexity and control. The cost and time restraints of calibration and testing of various control strategies have made virtual testing environments increasingly popular. Using Hardware-in-the-Loop (HiL), Volvo Penta has built a virtual test rig named VIRTEC for efficient engine testing, using a model simulating a fully instrumented engine. This paper presents an innovative Artificial Neural Network (ANN) based model for engine simulations in HiL environment. The engine model, herein called Artificial Neural Network Engine (ANN-E), was built for D8-600 hp Volvo Penta engine, and directly implemented in the VIRTEC system. ANN-E uses a combination of feedforward and recursive ANNs, processing 7 actuator signals from the engine management system (EMS) to provide 30 output signals.

In engine research and development there are often different engine parameters that produce similar effects on the end-point results. When calibrating modern engines, a huge number of parameters needs to be set, which also includes compensation parameters for model imperfections. In this context, simpler, more robust, and physically based models should be beneficial both for calibration work load and powertrain performance. In this study, we present an experimental methodology that uses intermediate (“intrinsic”) variables instead of engine parameters. By using simple thermodynamic models, the engine parameters EGR, IVC, and PBoost could be translated into oxygen concentration, temperature and gas density at the start of injection. The reason for this transformation of data is to “move” the Design of Experiment (DoE) closer to the situation of interest (i.e. the combustion) and to be able to construct simpler and more physically based models.

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.

Underhood Thermal Management has become an important topic for the majority of automotive OEM's. To keep combustion engines cool and manage waste heat efficiently is an important part in the design of vehicles with low fuel consumption. To be able to predict cooling performance and underhood airflow with good precision within a virtual design process, it is of utmost importance to model and simulate the cooling fan efficiently and accurately, and this has turned out to be challenging. Simulating the cooling fan in a vehicle installation involves capturing complex fluid dynamic interaction between rotating blades and stationary objects in the vicinity of the fan. This interaction is a function of fan rotation rate, fan blade profile, upstream and downstream installation components. The flow is usually highly turbulent and small geometry details, like the distance between the blade tip and the fan shroud, have strong impact on the fan performance characteristics.

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.

A common fan model to use in automotive under hood simulations is the Multiple Reference Frame (MRF) model and within the industry, for this specific application, this model is well known to under predict performance. In this paper we have examined the possibilities of correcting this deficiency with a simple “speed correction”. This is done by testing and simulating a production fan in the Volvo Fan Test Rig for two operating speeds, 1200 rpm and 2400 rpm. Pressure rise, fan power and static efficiency are presented as functions of volumetric flow rate. The simulations verify that using the MRF model the common behavior of under predicting pressure rise and performance of the fan occur. In addition, this work shows that; although the MRF is not predicting fan performance correctly it constitutes a reliable fan modeling strategy.

This paper presents results of a parametric CFD modeling study of a prototype Free Piston Engine (FPE), designed for application in a series hybrid electric vehicle. Since the piston motion is governed by Newton's second law, accounting for the forces acting on the piston/translator, i.e. friction forces, electrical forces, and in-cylinder gas forces, having a high-level control system is vital. The control system changes the electrical force applied during the stroke, thus obtaining the desired compression ratio. Identical control algorithms were implemented in a MATLAB/SIMULINK model to those applied in the prototype engine. The ignition delay and heat release data used in the MATLAB/SIMULINK model are predicted by the KIVA-3V CFD code which incorporates detailed chemical kinetics (305 reactions among 70 species).

This paper depicts the main topics of the experimental investigation on alcohol engine development field, aiming at the engineering targets for the emission levels. The first part of this study was focused on engine design optimization for running on ethanol mixed with poly-ethylene glycol (PEG) as ignition improver. It was shown that some design changes in compression ratio, turbine casing, injector nozzle configuration and exhaust pressure governor (EPG) activation, lead to a better engine thermodynamics and its thermochemistry. The second objective of this study was the investigation of engine performance and emission levels, when the ignition improver diethyl ether (DEE) would be generated on board via catalytically dehydration of ethanol, and used directly as soluble mixture or separately fumigated.