Current Issue : January - March Volume : 2019 Issue Number : 1 Articles : 5 Articles
The concept of focus point preview is proposed, and fractional calculus is introduced to driver model to build focus point preview\ndriver model. A formula for calculating lateral error is given, where the weight coefficients of fractional calculus are designed to\nimitate the driverâ??s focus preview property. The relationship between the speed and the order of fractional calculus is studied. A\ndriver-vehicle-road simulation system is set up to illustrate the performances of the proposed previewmodel.TheS-type road is used\nto test the model in the case of continuous small curvature turns and the Shanghai F1 track model is used as the case that automobile\npassing large curvature curve.Theperformances are evaluated fromtwo aspects: path tracking effect and vehicle dynamic responses.\nIt is concluded that, as the speed of the vehicle increases, the optimal order of fractional integral increases, so that the order is seen\nas the degree of driverâ??s attention. What is more, in the case of large curvature, the path tracking performance is improved by\nincreasing the corresponding fractional order. Simulations results also show that, compared with the single-point preview model,\nthe performances of the focus point preview model are better. On the one hand, the proposed driver model can be used to control\nthe vehicle steering and path tracking. On the other hand, fractional calculus is used to reveal the driver preview property and the\norder is given a certain physical meaning, which is conducive to the development of fractional calculus applications....
Telematics box (T-Box) chip-level Global Navigation Satellite System (GNSS) receiver\nmodules usually suffer from GNSS information failure or noise in urban environments. In order to\nresolve this issue, this paper presents a real-time positioning method for Extended Kalman Filter\n(EKF) and Back Propagation Neural Network (BPNN) algorithms based on Antilock Brake System\n(ABS) sensor and GNSS information. Experiments were performed using an assembly in the vehicle\nwith a T-Box. The T-Box firstly use automotive kinematical Pre-EKF to fuse the four wheel speed,\nyaw rate and steering wheel angle data from the ABS sensor to obtain a more accurate vehicle\nspeed and heading angle velocity. In order to reduce the noise of the GNSS information, After-EKF\nfusion vehicle speed, heading angle velocity and GNSS data were used and low-noise positioning\ndata were obtained. The heading angle speed error is extracted as target and part of low-noise\npositioning data were used as input for training a BPNN model. When the positioning is invalid,\nthe well-trained BPNN corrected heading angle velocity output and vehicle speed add the synthesized\nrelative displacement to the previous absolute position to realize a new position. With the data of\nhigh-precision real-time kinematic differential positioning equipment as the reference, the use of the\ndual EKF can reduce the noise range of GNSS information and concentrate good-positioning signals\nof the road within 5 m (i.e. the positioning status is valid). When the GNSS information was shielded\n(making the positioning status invalid), and the previous data was regarded as a training sample, it is\nfound that the vehicle achieved 15 minutes position without GNSS information on the recycling line.\nThe results indicated this new position method can reduce the vehicle positioning noise when GNSS\ninformation is valid and determine the position during long periods of invalid GNSS information...
Modelling and implementing adequate controllers for urban road traffic control constitute a huge challenge nowadays because\nof the complexity of systems, as well as possible scenarios and configurations, in each road in a city. A series of issues related to\nmodelling these behaviours are common to arise when using formalisms, tools, and computation machines to perform complex\ncalculations and limitations. This paper presents a formal, flexible, and adaptable approach, with no limitations, from the scientific\npoint of view. For this purpose, modelling formalisms (cellular automata and timed automata) and analysis techniques (simulation\nand formal verification) are proposed to reach themain goals of modelling complex and adaptable behaviours in urban road traffic\nwith multiple over time changeable configurations. A case study is presented, in order to illustrate the approach and demonstrate\nin detail the unlimited application of the presented approach....
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The paper describes the effects of heat transfer enhancement and gas-flow\ncharacteristics by wing-type-vortex-generators inside a rectangular gas-flow\nduct of a plate-fin structure exhaust gas recirculation (EGR) cooler used in a\ncooled-EGR system. The analyses are conducted using computational fluid\ndynamics (CFD). The numerical modelling is designed as a gas-flow rectangular\nduct of an EGR cooler using two fluids with high temperature gas and\ncoolant water whose flow directions are opposite. The gas-flow duct used to\nseparate two fluids is assembled with a stainless steel material. The inlet temperature\nand velocity of gas flowed inside gas-flow duct are 400 deg C and 30\nm/s, respectively. Coolant water is flowed into two ducts on both a top and a\nbottom surface of the gas-flow duct, and the inlet temperature and velocity is\n80 deg C and 0.6 m/s, respectively. Wing-type-vortex-generators are designed to\nachieve good cooling performance and low pressure drop and positioned at\nthe center of the gas-flow duct with angle of inclination from 30 to 150 degrees\nat every 15 degrees. The temperature distributions and velocity vectors\ngained from numerical results were compared, and discussed. As a result, it is\nfound that the vortices guided in the proximity of heat transfer surfaces play\nan important role in the heat transfer enhancement and low pressure drop.\nThe collapse of the vortices is caused by complicated flow induced in the\ncorner constituted by two surfaces inside gas-flow duct....
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