Fatigue life prediction of a rubber material based on dynamic crack growth considering shear effect

This paper suggests a fatigue life calculation method (A fatigue life calculation method is suggested) for rubber components based on the dynamic crack growth considering shear effect. Dynamic tearing tests were carried out, and the crack length was measured using an optical microscope to calculate the dynamic crack growth rate which characterizes and determines the fatigue life. The algorithm was numerically implemented in finite element code, ABAQUS standard, by using the user subroutine and applied to several rubber components. In the finite element analysis, deformation mode of an element was classified into tension and shear, and a weighting factor was multiplied to a strain energy density according to the degree of shear strain. Tension and compression of an elliptic dumbbell specimen was simulated in order to verify the material parameters of the suggested fatigue life prediction equation and to enhance the reliability of the algorithm. Finally, the fatigue life of a vehicle suspension bushing was calculated and compared with test. There were good agreements in the failure location and the magnitude of the fatigue life.     

Preview suspension control for a full tracked vehicle

In this study, preview control algorithms for the active and semi-active suspension systems of a full tracked vehicle (FTV) are designed based on a 3-D.O.F model and evaluated. The main issue of this study is to make the ride comfort characteristics of a fast moving tracked vehicle better to keep an operator’s driving capability. Since road wheels almost trace the profiles of the road surface as long as the track doesn’t depart from the ground, the preview information can be obtained by measuring only the absolute position or velocity of the first road wheel. Simulation results show that the performance of the sky-hook suspension system almost follows that of full state feedback suspension system and the on-off semi-active system carries out remarkable performance with the combination of 12 on-off semi-active suspension units. The results simulated with 1^st and 2^nd weighting sets mean that the suspension system combined with the soft type of inner suspension and hard type of outer suspension can carry out better ride comfort characteristics than that with identical suspensions. The full tracked vehicle (FTV) system is uncontrollable and the system is split into controllable and uncontrollable subspace using singular value decomposition transformation. Frequency response curves to four types of inputs, such as heaving, pitching, rolling, and warping inputs, also demonstrate the merits of preview control in ride comfort. All the frequency characteristic responses confirm the continuous time results.     

Methodology for bus structure torsion stiffness and natural vibration frequency prediction based on a dimensional analysis approach

Engineering bus design requires testing of bus structures prototypes in order to guarantee a certain level of strength and an appropriate static and dynamic behavior of the bus superstructure when exposed to road loads. However, experimental testing of real bus structures is very expensive as it requires expensive resources and space. If testing is done on a scale bus model the previous required expenses are considerably reduced. Therefore, a novel methodology based on dimensional analysis applied to bus structure prediction to evaluate the bus structure static and dynamic performance is proposed. The static performance is evaluated attending to torsion stiffness and the dynamic in terms of the natural vibration frequencies and rollover threshold. A scale bus has been manufactured and dimensionless parameters have been defined in order to project the results obtained in the scale bus model to a larger model. Validation of the proposed methodology has been carried out under experimental and finite element analysis.     

Vehicle velocity estimation using effective inertia for an in-wheel electric vehicle

In this study, a vehicle velocity estimation algorithm for an in-wheel electric vehicle is proposed. This algorithm estimates the vehicle velocity using the concept of effective inertia, which is based on the motor torque, the angular velocity of each wheel and vehicle acceleration. Effective inertia is a virtual mass that changes according to the state of a vehicle, such as acceleration, deceleration, turning or driving on a low friction road. The performance of the proposed vehicle velocity estimation algorithm was verified in various conditions that included straight driving, circle driving and low friction road driving using the in-wheel electric vehicle that was equipped with an in-wheel system in each of its rear wheels.     

Comparison study on characteristics of nano-sized particle number distribution by using condensation particle counter calibrated with spray and soot type particle generation methods

In the year 2011, the Particle Measurement Program (PMP) in Europe started the regulation of the diesel vehicle’s nano-sized particle number density (PN) due to its high degree of harm to the human body. Concretely, the standard level of PN emission was introduced in the Euro 5+ and 6 emissions regulation with a limit (<6.0 × 10¹¹#/km) for diesel light-duty vehicle. Therefore, the determination of suitable and sophisticated instruments for reliable particle sampling and analysis was essential in taking exact experimental data. Now, among the PN emission measuring devices suggested by the PMP, condensation particle counter (CPC) is a key equipment for measuring the particle number density in real time and it has been used extensively. However, CPC can cause different results depending on operating conditions of the saturator and condensation that induce different rates of particle growth. This study was conducted to analyze the effect of CPC calibrated by a two-particle generator with spray and soot type methods applied on the nano-sized particle distribution’s parameters such as number concentration and linearity. Also, in order to ensure the reliability for particle sensor system named as PPS, which had emerged as a useful diagnostic to making spatially and temporally resolved quantitative measurements of diesel PN concentration, it was compared with calibrated CPC system. As a result, nano-sized particle measuring system with CPC calibrated by spray type particle generator had a much higher counting efficiency, indicating a larger nano size available than soot type particle generator. And, comparative experimental results on the correlation between the particle number of CPC to a reflectance PPS system showed that above 5,000 #/cm ³ in number concentrations measured by CPC as well as PPS were found to be similar with good linear relationship.     

Impact technique for measuring global dynamic stiffness of engine mounts

Engine mounts are used for engine vibration isolation. The dynamic performance of the mount depends on the orientation. Measurements of the dynamic properties of engine mounts are usually performed in the axial direction because of the problem related to actuator loading direction and set up costs. Impact technique is developed here to measure the dynamic driving point stiffness and driving point shear stiffness of engine mount in a single setup. The compressive and shear frequency-dependent stiffnesses are obtained in the vertical orientation. A transformation matrix is used to calculate the frequency-dependent stiffnesses and loss factors in other orientations. Three different designs of engine mounts are used to verify the accuracy of the transformation model. The correlation coefficient between calculation and measurement results show R²≥ 0.995 along the X- and Y-axes. For the Z-axis, mounts B and C showed R²≥ 0.95 and mount A 0.687 ≤ R²≤ 0.791.     

Cycle-simulation turbulence modelling of IC engines

Numerical simulations of IC engines are of high interest for automotive engineers worldwide. The simulation models should be as fast as possible, low-computational effort and predictive tool. The correct prediction of turbulence level inside the combustion chamber of spark ignition engines is the most important factor influencing to the engine working cycle. This paper presents a development of the k-ε turbulence model applied to the commercial cycle-simulation software with the high emphasis on the intake part. The validation was performed on two engine geometries with the variation of engine speed and load comparing the cycle-simulation results of the turbulent kinetic energy and in-cylinder temperature with 3-D CFD results. In order to apply the cycle-simulation turbulence model for the simulation of entire engine map, the parameterization model of turbulence constants was proposed. The parameterized turbulence model was optimized using NLPQL optimization algorithm where the single set of turbulence model parameters for each engine was found. A good agreement of the turbulent kinetic energy during the expansion was achieved when the turbulence affects the flame front propagation and combustion rate as well.     

Real-time empirical NO<Subscript>x</Subscript> model based on In-cylinder pressure measurements for light-duty diesel engines

This paper proposes a real-time empirical model of NO_x emissions for diesel engines. The proposed model predicts the level of NO_x emissions using an empirical model developed based on the thermal NO formation mechanism, the extended Zeldovich mechanism. Since it is difficult to consider the exact physical NO formation phenomena in real-time applications, the proposed algorithm adapts the key factors of the NO formation mechanism from the extended Zeldovich mechanism: temperature of the burned gas, concentration of the gas species, and combustion duration where NO is generated. These factors are considered in a prediction model as four parameters: exhaust gas recirculation rate (EGR rate), crank angle location of 50 % of mass fraction burned (MFB50), exhaust lambda value, and combustion acceleration. The proposed prediction model is validated with various steady engine experiments that showed a high linear correlation with the NO_x emission measured by a NO_x sensor. Furthermore, it is also validated for transient experiments.     

Resource-aware integration of AUTOSAR-compliant ECUs with an empirical wcet prediction model

This paper presents an integration method of AUTOSAR-compliant ECUs which can evaluate resource constraints in an early-stage of development. There are three types of resources for an ECU (timing, memory, and interface) which should be carefully managed for successful ECU integration. The proposed method consists of three steps: measurement, prediction, and evaluation. In the first step, a method to measure resource factors for AUTOSAR-compliant software architecture is introduced. Based on the method, a worst-case execution cycle of a runnable, memory section usages of a software component, and interface of legacy ECUs can be obtained. In the second step, the obtained factors are quantitatively predicted according to the architectural designs of the integration ECU. In the case of the timing resource, the worst-case execution time of the integration ECU can be precisely predicted by a proposed empirical model. In the last step, the resource constraints such as CPU, memory, network utilizations can be evaluated with predicted resource factors before implementation. The proposed method was applied to the integration of an in-house engine management system composed of two ECUs. The method successfully provided quantitative measures to evaluate architectural designs of three different integration scenarios.     

Topological analysis of powertrains for refuse-collecting vehicles based on real routes–Part I: Hybrid hydraulic powertrain

In this two-part paper, a topological analysis of powertrains for refuse-collecting vehicles (RCVs) based on the simulation of different architectures (internal combustion engine, hybrid electric, and hybrid hydraulic) on real routes is proposed. In this first part, a characterization of a standard route is performed, analyzing the average power consumption and the most frequent working points of an internal combustion engine (ICE) in real routes. This information is used to define alternative powertrain architectures. A hybrid hydraulic powertrain architecture is proposed and modelled. The proposed powertrain model is executed using two different control algorithms, with and without predictive strategies, with data obtained from real routes. A calculation engine (an algorithm which runs the vehicle models on real routes), is presented and used for simulations. This calculation engine has been specifically designed to analyze if the different alternative powertrain delivers the same performance of the original ICE. Finally, the overall performance of the different architectures and control strategies are summarized into a fuel and energy consumption table, which will be used in the second part of this paper to compare with the different architectures based on hybrid electric powertrain. The overall performance of the different architectures indicates that the use of a hybrid hydraulic powertrain with simple control laws can reduce the fuel consumption up to a 14 %.