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.     

Adaptive neuron control using an integrated error approach with application to active suspensions

This paper proposes a new neuron control strategy for an active vehicle suspension system, with the emphasis on the study of multivariable and uncertain suspension characteristics. The novelty of this strategy is in the use of integrated error, which consists of multiple output errors in the regulated plant. By combining the integrated error approach with the traditional neuron control (TNC), integrated error neuron control (IENC) is presented. It provides a direct control to the multiple outputs of the control plant simultaneously. Taking a quarter-car model as an example, the proposed control strategy is applied and comparative simulations are carried out with various vehicle parameters and road input conditions. Simulation results prove the effectiveness and robustness of the proposed IENC method. In addition, the newly proposed neuron scheme provides a simple yet efficient new possibility for the control of a class of uncertain multivariable systems similar to an active vehicle suspension.     

Analysis of the capabilities of a two-stage turbocharging system to fulfil the US2007 anti-pollution directive for heavy duty diesel engines

This article presents a two-stage turbocharged heavy-duty diesel (HDD) engine designed to fulfil the US2007 anti-pollution directive. This directive imposes very restrictive limits on the NOx and particle emissions of HDD engines. In this work, the possibility of combining particle traps in the exhaust line to reduce soot emissions with very high EGR rates to reduce NOx emissions is considered. This new generation engine implements two-stage turbocharging in order to improve the bsfc when the engine is working on steady conditions as well as to optimize the engine transient response. After carrying out the tests, the results were analyzed and the engine settings were adjusted to maximise its behaviour and minimise pollutant emissions. NOx and soot emission peaks were also analyzed at engine transient conditions in order to keep them under certain levels, and thus maintain the overall pollutant emissions to a level that is as low as possible. In summary, a double-stage turbocharging configuration can greatly improve engine driveability (between 23% and 36% depending on engine speed), while reducing NOx emissions during transient evolution without increasing opacity peaks beyond the stated limits.     

Simulation of city bus performance based on actual urban driving cycle in China

This paper establishes the simulation model of a city bus on the basis of the EQ6110 bus prototype and its experimental data. According to the actual urban driving cycle, the fuel economy and the traction performance of the EQ6110 city bus have been simulated, and factors such as the driving cycle, the loss of power to engine accessories, the gear-shifting strategy, the fuel shut-off strategy of the engine, etc., which influence on the bus’s fuel economy, are also quantitatively analyzed. Some conclusions are drawn as follows: (1) driving cycles have a great influence on the fuel economy of a city bus; (2) under the typical urban driving cycle of the public bus in China, the engine fuel shut-off strategy can save about 1 to 1.5 percent of the fuel consumption; and (3) the optimized gear-shifting rules can save 6.7 percent of the fuel consumption. Experimental results verify that the fuel economy for the EQ6110 public bus is improved by 7.2 pecent over the actual Wuhan urban driving cycle of the current public bus in China.     

3-D numerical and experimental analysis for airflow within a passenger compartment

People use cars so frequently that they always consider the air-conditioning, and thermal comfort of the driver and passenger when buying a new car. Therefore accurate simulation of the thermal performance of automobile air conditioners to improve human comfort has become increasingly important. In order to improve the thermal comfort of passengers, 3-D flow motion and thermal behavior within vehicles must be analyzed. In this paper, a numerical simulation was used to investigate thermal behavior in a vehicle. Because air temperature at an air vent is related to the cooling capacity of the air conditioner, the cooling capacity was calculated using ɛ-NTU (effective number of transfer unit) theoretical equations. Using the air temperature relationship between inlet and outlet vents as boundary conditions, a 3-D unsteady κ-ɛ turbulent model was used to give a transient analysis simulation of the temperature field and flow conditions in a vehicle’s passenger cabin. Cooling cycle analysis and conjugate heat transfer analysis at the inside surface of the cabin’s ceiling, floor and sides were also considered. The predicted temperature distributions in the vehicles passenger cabin were in good agreement with those obtained experimentally.     

Prediction of fatigue life and estimation of its reliability on the parts of an air suspension system

Air suspension systems have been implemented in various commercial vehicles, such as buses and special purpose trucks, because of the comfortable ride and easy height control. An evaluation of the durability of vehicle parts has been required for service life and safety starting in the early stages of design. The cyclic load applied to the vehicle can cause fatigue failure of parts, such as the suspension frame. This paper presents a method to predict the fatigue life of the suspension frame at the design stage of the air suspension system used in a heavy-duty vehicle. To estimate the fatigue life using the SN method, the Dynamic Stress Time History (DSTH) is necessary for the part of interest. DSTH can be obtained from the results of the flexible body dynamic analysis using the Belgian road simulation and the Modal Stress Recovery (MSR) method. Furthermore, the reliability of the predicted fatigue life can be evaluated by considering the variations in material properties. The probability and distribution of the expected life cycle can be obtained using experimental design with a minimum number of simulations. The advantage of using statistical methods to evaluate the life cycle is the ability to predict replacement time and the probability of failure of mass-produced parts. This paper proposes a rapid and simple method that can be effectively applied to the design of vehicle parts.     

Effect of fuel stratification on initial flame development: Part 2-low swirl condition

This paper is the second invstigation on the effect of fuel stratification on flame propagation. In the previous work, the characteristics under the no port-generated swirl condition, i.e., the conventional case was studied. In this work, the flame development under the low swirl condition was considered. For this purpose, the initial flame development and propagation were visualized under different axially stratified states in a modified optical single cylinder SI engine. The images were captured by an intensified CCD camera through the quartz window mounted in the piston. Stratification was controlled by the combination of the port swirl ratio and injection timing. These were averaged and processed to characterize the flame propagation. The flame stability was estimated by the weighted average of flame area and luminosity. The stability was also evaluated through the standard deviation of flame area and propagation distance and through the mean absolute deviation of the propagating direction. The results show that the flame-flow interaction determines the direction of flame propagation and that the governing roles of the two factors vary according to the stratified state and the location in the cylinder. In addition, the flame development and the initial flame stability are strongly dependent on the stratified conditions, and the initial flame stability is closely related to the engine stability and lean misfire limit. Lastly, there is no essential difference in gasoline and CNG flame propagation characteristics.     

On-road visual vehicle tracking using Markov chain Monte Carlo particle filtering with metropolis sampling

In this study, a method for vehicle tracking through video analysis based on Markov chain Monte Carlo (MCMC) particle filtering with metropolis sampling is proposed. The method handles multiple targets with low computational requirements and is, therefore, ideally suited for advanced-driver assistance systems that involve real-time operation. The method exploits the removed perspective domain given by inverse perspective mapping (IPM) to define a fast and efficient likelihood model. Additionally, the method encompasses an interaction model using Markov Random Fields (MRF) that allows treatment of dependencies between the motions of targets. The proposed method is tested in highway sequences and compared to state-of-the-art methods for vehicle tracking, i.e., independent target tracking with Kalman filtering (KF) and joint tracking with particle filtering. The results showed fewer tracking failures using the proposed method.     

A self-powering system based on tire deformation during driving

Tire intelligence is vital in the improvement of the safety of vehicles because the tire supports the car body and is the contact point between the vehicle and the road. To create an intelligent tire, sensors must be installed to measure the behavior of the tire. However, it is difficult to apply a wired sensor system on the wheel of the tire. Hence, it is necessary to implement a self-powering, wireless system (a type of energy harvesting system) that can be mounted inside the tire. The purpose of this study is to convert the strain energy caused by deformation of the tire while driving into useful electrical energy to supply the sensor system. A flexible piezofiber is utilized for the energy conversion. The variation in strain, due to changes in speed, load, and the internal pressure of the tire, was measured along two axial directions to evaluate the amount of available strain energy. The amount of strain changed from 0.15% to 0.8%. To predict the amount of available energy from a tire, we perform an analysis of the relationship between the strain and the voltage. In addition, experiments for impedance matching between piezofiber and related circuits were conducted to optimize the external loads for transferring energy efficiently. Based on the procedure mentioned above, at least 0.58 mJ of electrical energy can be generated by using the laterally oriented strain (1500 to 2500 micro strain). The result of this study is expected to enhance the potential realization of self-generating wireless sensor systems for so-called ??intelligent?? tires.     

Optimal synthesis of function generation in steering linkages

This paper presents an approach to optimize planar mechanisms for function generation synthesis. It is applied to the design of different steering linkages used in road vehicles where the Ackermann condition is formulated as the objective function. Four different mechanisms are kinematically defined and synthesized in terms of the proposed method. Limitations of the size of the elements are also considered by means of inequality constraints. Solutions are presented as the difference between desired behaviour, established by Ackermann, and actual generated performance. The results show that the accuracy achieved by the proposed procedure is satisfactory for working conditions in this type of linkages.