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Some physical parameters of a hub motor-driven four-wheel electric vehicle will change when the vehicle turns or maneuvers and the parameter change is caused by the change of the driving conditions. An adaptive sliding mode control is proposed in this paper to maintain the vehicle’s stability by compensating for the change of these parameters. The control parameter being adapted is the converging rate of the system state towards the sliding mode. As the Lyapunov method is used, so both the vehicle stability and adaptive rate convergence are guaranteed. Moreover, the hierarchical control structure is adopted for this vehicle stability control system. The above adaptive sliding model control forms the upper-layer; while the lower-layer control is to distribute the upper torque to the four wheels in an optimal way, subject to several constraints. In addition, the best feasible reference of the yaw rate and the vehicle side slip angle are obtained and used in the control system. The developed method is simulated under the CarSim/MATLAB co-simulation environment to evaluate the system performance. The simulation results are compared with the non-adaptive existing sliding mode control, and show that the proposed method is superior under different conditions. © 2020, KSAE.

Objective To explore the clinical efficacy of tuina combined with moxibustion for treatment of lung-wei insecurity-type sweating syndrome in children. Methods Infantile tuina combined with moxibustion was conducted for 28 cases of lung-wei insecurity-type sweating syndrome in children. Tuina was carried out for once every other day, and moxibustion was conducted for once every other three days. Clinical efficacy was observed after treatment for 4 weeks. Results The total effective rate of tuina combined with moxibustion for treatment of lung-wei insecurity-type sweating syndrome in children was 92.85%. Conclusion The efficacy of tuina combined with moxibustion for treatment of lung-wei insecurity-type sweating syndrome in children is definite, which is worthy of being popularized clinically.

In this paper, we deal with the problem of improving backup and recovery performance by compressing redundancies in large disk-based backup system. We analyze some general compression algorithms; evaluate their scalability and applicability. We investigate the distribution features of the redundant data in whole system range, and propose a multi-resolution distributed compression algorithm which can discern duplicated data at granularity of file level, block level or byte level to reduce the redundancy in backup environment. In order to accelerate recovery, we propose a synthetic backup solution which stores data in a recovery-oriented way and can compose the final data in back-end backup server. Experiments show that this algorithm can greatly reduce bandwidth consumption, save storage cost, and shorten the backup and recovery time. We implement these technologies in our product, called H-info backup system, which is capable of achieving over 10x compression ratio in both network utilization and data storage during backup.

The ZnO quantum dots (about 3 nm in average size) and the ZnO nanorods (about 80 nm in length and 14 nm in width) were synthesized by the sol−gel method. They were characterized by X-ray powder diffraction (XRD), transmission electron microscopy (TEM), UV−vis spectroscopy, and photoluminescence (PL) spectroscopy. The surface photovoltage (SPV) of ZnO nanoparticles was investigated by means of surface photovoltage spectroscopy (SPS) and field-induced surface photovoltage spectroscopy (FISPS), and the bands were identified. The results show that the SPV of ZnO nanoparticles are greatly different for their different sizes as a result of the quantum confinement effect. The ZnO quantum dots exhibit marked quantum confinement properties; that is, FISPS takes a high symmetry in the changes of the response intensity with the strengthening of the two opposed electric fields, and the FISPS response band always appears at about 369 nm, no matter what external electric field is applied. Whereas for the ZnO nanorods a...

Surface photovoltage spectrum (SPS) and field-induced surface photovoltage spectrum (FISPS) are valuable techniques for the determination of pn conduction type of organic semiconductors. Here, cond...

Support vector machine (SVM) based on classification is applied for fault diagnosis of the automotive engine. The basic idea is to identify the information by using the trained SVM model to classify new fault samples. The data from the engine simulation model by AMESim software are fault features extracted, and these fault characteristic parameters have statistical property and specific physical meaning. Principal component analysis (PCA) is used to reduce the dimensions and redundancy of the data, and then these data are normalized as the input of SVM. The proposed method achieves accurate fault classification because SVM has good performance of classification and generalization ability, which is verified by the result of combining MATLAB/SIMULIK and AMESim. And the simulation results indicates that the proposed SVM based fault diagnosis method has achieved the better performance than the Artificial Neural Network, meeting the requirements of real-time diagnosis of the automotive engine.

This paper studies the loading sequence effect on fatigue damage accumulation and puts forward the kneepoint coordinate formulae and two-stage fatigue damage cumulative rules (KDR) under L-H loading and H-L loading by analysing extensive fatigue damage test data and theoretical research. KDR can be used more widely for various complex loadings than Manson's double linear damage rule. The damage line in the paper is closer to experimental data than Miner's straight line. Experimental verification of two- and three-level stresses with different loading sequences has shown that the average error of residual life estimated by KDR is 12.2% and is much less than that of 50.1% estimated by Miner's rule.

A controller is designed based on BP neural network in this paper, which is applied to compensate the nonlinearity of electromagnetic valve of ABS, such as time-delay, etc. Thus, an intelligent controller is used to improve the quality of pressure adjustment in ABS. Data for training BP neural network is obtained from actual ABS. The cases for pressure-increase and pressure-decrease are studied, respectively. And the parameters of BP neural network are optimized. Finally, experiments including hardware in the loop are executed to verify the effectiveness of the provided design with the low adhesion road condition. And the quality of ABS is improved.

The 16 kb/s LD-CELP speech coding algorithm is submitted by AT&T to CCITT for the 16 kb/s speech coding standard which can be used in many applications. After having investigated the algorithm carefully and simulated it in FORTRAN and DSP TMS320C30 assembly language respectively the authors find that the difficulty implementing the 16 kb/s LD-CELP algorithm on a TMS320C30 is the large computational load and rather uneven distribution among 8 vectors in the same adaptation cycle. Some techniques are used in the program to reduce the computational load and a recursive window is used to compute autocorrelation functions. At last, the authors employ about 90% processor time of a TMS320C30 to implement the 16 kb/s LD-CELP coding algorithm in real-time. >

A simplified compact model for a miniaturized cross-shaped CMOS integrated Hall device is presented. The model has a simple circuit structure, only consisting of a passive network with eight non-linear resistors and four current-controlled voltage sources. It completely considers the following effects: non-linear conductivity, geometry dependence of sensitivity, temperature drift, lateral diffusion, and junction field effect. The model has been implemented in Verilog-A hardware description language and was successfully performed in a Cadence Spectre simulator. The simulation results are in good accordance with the classic experimental results reported in the literature.

Consider the irrecoverable energy dissipation in fatigue damage process and take the cycle-dependence into account, a fatigue damage model has been proposed. Comparisons have been done between the estimated results by this model and several usual ones with test results.

The cyclic hysteresis energy of four kinds of steel was analysed using fully reversed constant-strain-controlled fatigue tests. Mathematical formulae for the cyclic hysteresis energy of the materials, which have different cyclic properties, are proposed. Because of the experimental and theoretical relations of cyclic hysteresis energy and the total absorbed energy to failure versus fatigue failure life, it is considered that part of the hysteresis energy is absorbed through heating, vibration and non-propagating defects during the process of fatigue life. The total absorbed energy to failure is associated with the variation of cyclic hysteresis energy.