Review on characterization of nano-particle emissions and PM morphology from internal combustion engines: Part 1

This paper is review of the characterization of exhaust particles from state-of-the-art internal combustion engines. We primarily focus on identifying the physical and chemical properties of nano-particles, i.e., the concentration, size distribution, and particulate matter (PM) morphology. Stringent emissions regulations of the Euro 6 and the LEV III require a substantial reduction in the PM emissions from vehicles, and improvements in human health effects. Advances in powertrains with sophisticated engine control strategies and engine after-treatment technologies have significantly improved PM emission levels, motivating the development of new particle measurement instruments and chemical analysis procedures. In this paper, recent research trends are reviewed for physical and chemical PM characterization methods for gasoline and diesel fueled engines under various vehicle certification cycles and real-world driving conditions. The effects of engine technologies, fuels, and engine lubricant oils on exhaust PM morphology and compositions are also discussed.     

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.     

Node-based scheduling method for easy migration from CAN to FlexRay in in-vehicle networking systems

As vehicles become more intelligent, in-vehicle networking (IVN) systems such as controller area network (CAN) are essential for the convenience and safety of drivers. To expand the applicability of IVN systems, attention is currently being focused on chassis networking systems that require increased network capacity and real-time capabilities. FlexRay was developed to replace CAN protocol in chassis networking systems, to remedy the shortage of transmission capacity and unsatisfactory real-time transmission delay of conventional CAN. However, FlexRay network systems require a complex scheduling method, which is a barrier to their implementation as chassis networking systems. In particular, if we want to migrate from a CAN network to a FlexRay network using the well-defined CAN message database, which has been specifically constructed for chassis networking systems by automotive vendors, a new type of scheduling method is necessary to reduce scheduling efforts during the software development process. This paper presents a node-based scheduling method for easy migration from a CAN network to a FlexRay network system. To demonstrate the feasibility of the technique, its performance is evaluated in terms of various software complexity indices.     

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.     

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.     

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.     

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.     

Road boundary detection and tracking for structured and unstructured roads using a 2D lidar sensor

Road boundaries can give useful information for evaluating safe vehicle paths in intelligent vehicles. Much previous research has studied road boundary detection, using different types of sensors such as vision, radar, and lidar. Lidar sensors, in particular, show advantages for road boundary extraction including high resolution and wide field of view. However, none of the previous studies examined the problem of detecting road boundaries when roads could be either structured or unstructured. In this study, we developed a road boundary detection and tracking algorithm using lidar sensing for both structured and unstructured roads. The algorithm extracts road features as line segments in polar coordinates relative to the lidar sensor. The extracted road features are then tracked with respect to a vehicle’s local coordinates using a nearest neighbor filter. The proposed algorithm accurately detected the road boundaries regardless of the road type.     

Finite element analysis of overlay incorporating stress absorbing membrane interlayers against reflective cracking

A wheel tracking test was modelled to gain better understanding of the deflection and stress-strain distribution in an overlaid cracked pavements with and without membrane interlayer （SAMI）. For this purpose, commercial finite element software Abaqus 6.7-1 was used. Two different models were considered, one incorporating stress absorbing membrane interlayers （SAMIs） and the other without SAMI. In the study, full bond condition was assumed for the boundaries between the layers, and a linear elastic model was used for the analysis. The results show that introduction of SAMI caused greater deflection of the pavement. It is found that although with SAMIs, low stiffness is required, a very low stiffness may yield undesirable results. The results show that the introduction of SAMIs results in high strain concentration around the crack region, whilst the strain in the overlay is smaller than the values predicted in the models without SAMIs.     

Analysis of travel activity determinants using robust statistics

This study investigates travel behavior determinants based on a multiday travel survey conducted in the region of Ghent, Belgium. Due to the limited data reliability of the data sample and the influence of outliers exerted on classical principal component analysis, robust principal component analysis (ROBPCA) is employed in order to reveal the explanatory variables responsible for most of the variability. Interpretation of the results is eased by utilizing ROSPCA. The application of ROSPCA reveals six distinct principal components where each is determined by a few variables. Among others, our results suggest a key role of variable categories such as journey purpose-related impedance and journey inherent constraints. Surprisingly, the variables associated with journey timing turn out to be less important. Finally, our findings reveal the critical role of outliers in travel behavior analysis. This suggests that a systematic understanding of how outliers contribute to observed mobility behavior patterns, as derived from travel surveys, is needed. In this regard, the proposed methods serve for processing raw data typically used in activity-based modelling.