轨枕间距对钢轨波磨的影响

主要研究轨枕间距对钢轨波磨发展的影响。研究小半径曲线内轨的小矢跨比波磨。这些出现问题的曲线段属于西班牙毕尔巴鄂区域的地铁轨道,铺设着混凝土道床和两层STEDEF型支承垫层。当初始轨枕间距为1000mm时,仅有92万组轮对通过后所测得的波磨深度峰-峰值已经达到0.42mm。随后更换产生波磨的钢轨,比较列车通过时轨枕上方和轨间中部的内轨垂向、横向加速度。当轨枕间距为1000mm时,轨间中部出现频率为204和244Hz的强烈响应,在轨枕上方却未出现。在相邻轨枕中间铺设一个轨枕,使轨枕间距变为500mm,钢轨波磨停止发展。该结论是根据2年的观测结果得到的。     

Fatigue and buckling analysis of automotive components considering forming and welding effects

Some vehicle components are developed by setting target weights to the gram level at their design stages to accomplish a lightweight design. Recently, there have been many studies that have focused on lightweight design through the use of ultra-high-strength steels. However, a lightweight design can face many challenges if the reliability of the analysis is not also secured at the design stage. Such challenges include difficulties in coupled analyses when the file formats are different among PAM-STAMP, ABAQUS, and NASTRAN. In this study, we developed a mapping interface that enables mapping between the file formats of various software programs. Buckling analysis was coupled to the forming analysis, in which pre-strain test data were applied in considering the material’s strain hardening, to evaluate the rigidity of the front lower control arm that controls the wheels and transfers loads. The influence of forming effects on endurance was evaluated, and residual stresses around the weld zone were calculated. A comparison of experimental and analytical results indicated that the proposed analysis was highly reliable.     

Estimation of lateral offset and drift angle for application in secondary collision avoidance system

Recent reports show that the secondary collision on the road gives much higher fatality rate than the other traffic accidents. Many studies have been carried out to prevent the secondary accidents and as a result automotive companies began to introduce brake-based secondary collision avoidance systems. To prevent the secondary accidents it is important to monitor and control the lateral deviation of the vehicle after the primary collision. An estimator for the vehicle’s lateral offset and drift angle based on the in-vehicle sensors and the camera was developed in this paper. By employing sensor fusion scheme and applying extended Kalman filter, the estimator has been designed so that it works even when the camera loses the image of the lanes due to sudden change of the vehicle’s heading angle. For validation of the estimator, simulation has been carried out on various collision scenarios. The simulation results indicated that the estimator of this paper could calculate the vehicle’s lateral deviation with robustness that may be required for application in the secondary collision avoidance systems.     

Experimental and 3D,embedded modeling for diesel engine SCR deposit

Nowadays, the selective catalytic reduction (SCR) is a promising solution to fulfill stringent nitrogen oxide (NO_X) emission standards enforced by worldwide regulation bodies for lean burning engines. However, in the practical operation, urea deposits occur under unfavorable conditions, which bring about a failure of urea dosing strategy, affect the SCR system de-NOx performance and lowering the fuel economy by increasing the engine back pressure. This paper will present 3D deposit model, which can be used to predict the deposit position. Furthermore, a model-based controls strategy and calibration are designed. The comparison test results of both engine emission tests and vehicle field tests shows there is significant deposits improvement with the embedded model.     

Drowsy behavior detection based on driving information

Drowsy behavior is more likely to occur in sleep-deprived drivers. Individuals’ drowsy behavior detection technology should be developed to prevent drowsiness related crashes. Driving information such as acceleration, steering angle and velocity, and physiological signals of drivers such as electroencephalogram (EEG), and eye tracking are adopted in present drowsy behavior detection technologies. However, it is difficult to measure physiological signal, and eye tracking requires complex experiment equipment. As a result, driving information is adopted for drowsy driving detection. In order to achieve this purpose, driving experiment is performed for obtaining driving information through driving simulator. Moreover, this paper investigates effects of using different input parameter combinations, which is consisted of lateral acceleration, longitudinal acceleration, and steering angles with different time window sizes (i.e. 4 s, 10 s, 20 s, 30 s, 60 s), on drowsy driving detection using random forest algorithm. 20 s-size datasets using parameter combination of accelerations in lateral and longitudinal directions, compared to the other combination cases of driving information such as steering angles combined with lateral and longitudinal acceleration, steering angles only, longitudinal acceleration only, and lateral acceleration only, is considered the most effective information for drivers’ drowsy behavior detection. Moreover, comparing to ANN algorithm, RF algorithm performs better on processing complex input data for drowsy behavior detection. The results, which reveal high accuracy 84.8 % on drowsy driving behavior detection, can be applied on condition of operating real vehicles.     

Experimental investigations on continuous regenerative anti-lock braking system of full electric vehicle

Functions of anti-lock braking for full electric vehicles (EV) with individually controlled wheel drive can be realized through conventional brake system actuating friction brakes and regenerative brake system actuating electric motors. To analyze advantages and limitations of both variants of anti-lock braking systems (ABS), the presented study introduces results of experimental investigations obtained from proving ground tests of all-wheel drive EV. The brake performance is assessed for three different configurations: hydraulic ABS; regenerative ABS only on the front axle; blended hydraulic and regenerative ABS on the front axle and hydraulic ABS on the rear axle. The hydraulic ABS is based on a rule-based controller, and the continuous regenerative ABS uses the gain-scheduled proportional-integral direct slip control with feedforward and feedback control parts. The results of tests on low-friction road surface demonstrated that all the ABS configurations guarantee considerable reduction of the brake distance compared to the vehicle without ABS. In addition, braking manoeuvres with the regenerative ABS are characterized by accurate tracking of the reference wheel slip that results in less oscillatory time profile of the vehicle deceleration and, as consequence, in better driving comfort. The results of the presented experimental investigations can be used in the process of selection of ABS architecture for upcoming generations of full electric vehicles with individual wheel drive.     

Electrochemical battery model and its parameter estimator for use in a battery management system of plug-in hybrid electric vehicles

This paper reports the development of a battery model and its parameter estimator that are readily applicable to automotive battery management systems (BMSs). Due to the parameter estimator, the battery model can maintain reliability over the wider and longer use of the battery. To this end, the electrochemical model is used, which can reflect the aging-induced physicochemical changes in the battery to the aging-relevant parameters within the model. To update the effective kinetic and transport parameters using a computationally light BMS, the parameter estimator is built based on a covariance matrix adaptation evolution strategy (CMA-ES) that can function without the need for complex Jacobian matrix calculations. The existing CMA-ES implementation is modified primarily by region-based memory management such that it satisfies the memory constraints of the BMS. Among the several aging-relevant parameters, only the liquid-phase diffusivity of Li-ion is chosen to be estimated. This also facilitates integrating the parameter estimator into the BMS because a smaller number of parameter estimates yields the fewer number of iterations, thus, the greater computational efficiency of the parameter estimator. Consequently, the BMS-integrated parameter estimator enables the voltage to be predicted and the capacity retention to be estimated within 1 % error throughout the battery life-time.     

Required traffic micro‐simulation runs for reliable multivariate performance estimates

Previous methods to calculate the minimum number of traffic micro‐simulation runs do not consider multiple measures of performance simultaneously at an overall confidence level, which can lead to unreliable simulation outputs. This paper describes new methodologies for calculating the minimum number of traffic micro‐simulation runs for multivariate estimates at an overall confidence level. Simultaneous confidence intervals obtained from multiple comparisons in statistical theory such as the Bonferroni inequality and simultaneous confidence interval method are used to estimate multiple measures of performance with allowable errors at an overall confidence level. Measures of performance can be means and standard deviations. Results of numerical analysis based on an example corridor suggest that the proposed methods provide improved means of assessing statistical accuracy of multiple measures of performance. Results also indicate that the minimum number of runs is influenced by not only the sample size issue but also the complexity of the traffic system. Copyright © 2015 John Wiley & Sons, Ltd.     

Performance analysis according to the combination of energy storage system for fuel cell hybrid vehicle

The need for the unmanned ground combat vehicle (UGCV), which is used for the surveillance, reconnaissance and targeting during extremely dangerous condition on the battlefield, has steadily increased, and the transition from manned ground combat vehicles to unmanned ground combat vehicles is expected to reduce the loss of lives during battle. The UGCV needs many types of capabilities to achieve satisfactory performance. This paper focuses on the modeling and control of the power system of the UGCV, and proposes the fuel cell hybrid system (FCHS) for the power system of the UGCV. The fuel cell hybrid system has many advantages in stealth drive and the system efficiency. In addition, the FCHS is much quieter than the engine generator and generates much less heat. The benefits of the FCHS are advantageous for use in Army operations, which require ‘silent watch’ capability and the ability to operate without showing up on an enemy’s radar screen. The FCHS has a fuel cell and uses an energy storage system (ESS) as a power source. The ESS (e.g., batteries or ultracapacitors) helps the fuel cell supply power to the electric drive system and also recovers energy during deceleration. The ESS makes it possible to improve the efficiency and dynamic characteristic of the power system. In this paper, the FCHS is composed of different combinations of component models. The component sizes are chosen to satisfy performance requirements. In order to determine the power distribution between the fuel cell and the ESS, a power management strategy based on the required power and the SOC (state of charge) of the ESS is proposed. Batteries and ultracapacitor, components of the ESS, have different characteristics. Accordingly, varying the combination of ESS components can change the performance of the power system. The performance of the FCHS with respect to different combinations of ESS is analyzed using simulated results.