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.     

High-strain-rate fracture of adhesively bonded composite joints in DCB and TDCB specimens

Double-cantilever beam (DCB) and tapered double-cantilever beam (TDCB) specimens are the test configurations most commonly used to measure the fracture toughness of composites and adhesive joints. Strain rates of 1 to 18.47 m/s were applied to the test specimens via high-speed hydraulic test equipment. Because the fracture occurs through the adhesively bonded joints and the cracks grow rapidly, the crack length and beam displacement were recorded by a high-speed camera. An energy range from 0 to 10 J was often observed in the high-strain-rate fracture experiments for nonlinear plastic behavior of the dynamically loaded adhesively bonded DCB and TDCB specimens. The range of energy release rates (fracture energy) for TDCB specimen was 2 to 3 times higher than that of a DCB specimen for all high strain rates. The fracture energy of automotive adhesive joints can be estimated using the experimental results in this study for the fracture toughness (G_IC) under high rates of loading. The crack grows as the applied fracture energy exceeds the value of the critical energy release rate (G_IC) at the crack tip. The energy release rate was calculated using the fracture mechanics formula. The key fracture mechanics parameter, the fracture energy GIC, was ascertained as a function of the test rate and can be used to assess and model the overall joint performance.     

Improvement of exhaust gas pressure’s utilization for compressing the intake air in diesel engine’s cylinders

In order to improve the economical and environmental performances of the Diesel engines, the present paper aims to bring to the forefront solutions to increase the efficiency of the supercharging process carried out by the aggregates with Comprex type pressure waves. One solution to this is to drive the Comprex, not by the supercharged engine as it currently happens, but by a DC motor. The speed of the electric motor is modified, by means of an electronic management system, depending on the speed and load of the Diesel engine. The paper presents the experimental results obtained during the investigation of a supercharged Diesel engine by the Comprex driven type according to the proposed solution.     

不同稳定剂对SBS改性沥青稳定效果的对比研究

通过试验测试不同老化时间样品的针入度、软化点和延度比较其相容性和路用流变学性能指标的变化,分析体系宏观稳定性和稳定剂性能特征,并通过形态结构照片分析稳定剂改善的效果。结果表明,加入稳定剂后改性沥青的高温储存稳定性明显改善,同时加入FD-06无硫稳定剂的改性沥青在热储存过程中性能更加稳定,不易离析。沥青中的部分组份具有化学活性,利用其活性点,引入带有活性基团的反应物,并通过被引入分子的化学结构的调节改善SBS与沥青的相容性,从而制备储存稳定性良好的SBS改性沥青。化学改性技术的应用提高了路用改性沥青的性能/价格比。     

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.     

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.     

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.     

Automotive structure vibration with component mode synthesis on a multi-level

The recursive component mode synthesis method (RCMS) has been implemented for the finite element analysis model of an automobile structure as an efficient free vibration analysis tool. The RCMS method is intended to obtain a better performance relative to the block Lanczos method, which is a traditional method in the industry of obtaining eigenvalues, while obtaining the acceptable accuracy. A numerical example of the automobile finite element model demonstrates the outstanding performance of RCMS compared to the block Lanczos method.     

大跨径连续刚构桥的温度效应分析

以魏家洲特大桥为例,按照我国公路桥涵设计规范、英国BS5400规范、新西兰规范确定不同的计算模式,对大跨径连续刚构桥进行温度效应分析,得出：温度应力在大跨径连续刚构桥整个桥梁设计中占有很大的比重,且采用不同的温度梯度计算模式,所得到的梁内温度应力值相差较大,甚至出现异号的温度应力.