Ronghui Zhang

Study on Self-Tuning Tyre Friction Control for Developing Main-Servo Loop Integrated Chassis Control System

The inherent flexibility of hierarchical structure scheme with main-servo loop control structure is proposed to the problem of integrated chassis control system for the vehicle. It includes both main loop, which calculates and allocates the aim force using the optimal robust control algorithm and servo loop control systems, which track and achieve the target force using the onboard independent brake actuators. In fact, for the brake actuator, the aim friction is obtained by tracking the corresponding slip ratio of target force. For the coefficient of tire-road friction varying with different road surface, to get the nonlinear time-varying target slip ratio, the most famous quasi-static magic formula is proposed to estimate and predict real-time coefficient of different road surface and the constrained hybrid genetic algorithm (GA) is used to identify the key parameters of the magic formula on-line. Then, a self-tuning longitudinal slip ratio controller (LSC) based on the nonsingular and fast terminal sliding mode (NFTSM) control method is designed to improve the tracking accuracy and response speed of the actuators. At last, the proposed integrated chassis control strategies and the self-tuning control strategies are verified by computer simulations.

Study of Bicycle Movements in Conflicts at Mixed Traffic Unsignalized Intersections

Mixed traffic is a common phenomenon in developing countries such as China. Understanding bicycles’ moving behavior when it conflicts with motor vehicles/bicycles/pedestrians at unsignalized intersections is important for developing mixed traffic flow simulation models. Observations and analysis of bicycle movements when they conflict with those of vehicles/pedestrians at mixed traffic unsignalized intersections were made in our study. Field data from actual bicycle movements were captured from video data. We then proposed a plausible cyclist conflict avoidance movement model in mixed traffic flow situations based on fuzzy logic and the discrete choice method. Field data were used for model calibration and validation, and the results were promising.

A Dynamic Mode Decomposition Based Edge Detection Method for Art Images

Edge detection is a widely used feature extraction method in various fields, such as image processing, computer vision, machine vision, and so forth. However, it is still a challenging task to extract edges from art images, due to the false edge, shadow, and double lines of art images. In this paper, we propose a dynamic mode decomposition algorithm (DMD) based method for edge detection of art images. This is achieved by proposing a new color space based denoise method to deal with the shadow issue. Then, the false edge and double lines can be resolved by employing DMD method, which can be used to extract sparse features from the denoised images. Here, the sparse features have been enhanced by a new designed eight direction gradient operator. Finally, the effectiveness of our method will be demonstrated through detecting the edges of three classical types of art images (Comic, Oil Painting, and Printmaking).

Development and Characterization a Single-Active-Chamber Piezoelectric Membrane Pump with Multiple Passive Check Valves

In order to prevent the backward flow of piezoelectric pumps, this paper presents a single-active-chamber piezoelectric membrane pump with multiple passive check valves. Under the condition of a fixed total number of passive check valves, by means of changing the inlet valves and outlet valves’ configuration, the pumping characteristics in terms of flow rate and backpressure are experimentally investigated. Like the maximum flow rate and backpressure, the testing results show that the optimal frequencies are significantly affected by changes in the number inlet valves and outlet valves. The variation ratios of the maximum flow rate and the maximum backpressure are up to 66% and less than 20%, respectively. Furthermore, the piezoelectric pump generally demonstrates very similar flow rate and backpressure characteristics when the number of inlet valves in one kind of configuration is the same as that of outlet valves in another configuration. The comparison indicates that the backflow from the pumping chamber to inlet is basically the same as the backflow from the outlet to the pumping chamber. No matter whether the number of inlet valves or the number of outlet valves is increased, the backflow can be effectively reduced. In addition, the backpressure fluctuation can be significantly suppressed with an increase of either inlet valves or outlet valves. It also means that the pump can prevent the backflow more effectively at the cost of power consumption. The pump is very suitable for conditions where more accurate flow rates are needed and wear and fatigue of check valves often occur.

Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation

Aiming at the braking energy feedback control in the optimal energy recovery of the two-motor dual-axis drive electric vehicle (EV), the efficiency numerical simulation model based on the permanent magnet synchronous motor loss was established. At the same time, under different speed and braking conditions, based on maximum recovery efficiency and data calculation of motor system, the optimization motor braking torque distribution model was established. Thus, the distribution rule of the power optimization for the front and rear electric mechanism was obtained. This paper takes the Economic Commission of Europe (ECE) braking safety regulation as the constraint condition, and finally, a new regenerative braking torque distribution strategy numerical simulation was developed. The simulation model of Simulink and CarSim was established based on the simulation object. The numerical simulation results show that under the proposed strategy, the average utilization efficiency of the motor system is increased by 3.24% compared with the I based braking force distribution strategy. Moreover, it is 9.95% higher than the maximum braking energy recovery strategy of the front axle. Finally, through the driving behavior of the driver obtained from the big data platform, we analyze how the automobile braking force matches with the driver’s driving behavior. It also analyzes how the automobile braking force matches the energy recovery efficiency. The research results in this paper provide a reference for the future calculation of braking force feedback control system based on big data of new energy vehicles. It also provides a reference for the modeling of brake feedback control system.

Monitoring drivers' sleepy status at night based on machine vision

Driver fatigue is a chief cause of traffic accidents. For this reason, it is essential to develop a monitoring system for drivers’ level of fatigue. In recent years, driver fatigue monitoring technology based on machine vision has become a research hotspot, but most research focuses on driver fatigue detection during the day. This paper presents a night monitoring system for real-time fatigue driving detection, which makes up for the deficiencies of fatigue driving detection technology at night. First, we use infrared imaging to capture a driver’s image at night, and then we design an algorithm to detect the driver’s face. Second, we propose a new eye-detection algorithm that combines a Gabor filter with template matching to locate the position of the corners of the eye, and add an eye-validation process to increase the accuracy of the detection rate. Third, we use a spline function to fit the eyelid curve. After extracting eye fatigue features, we use eye blinking parameters to evaluate fatigue. Our system has been tested on the IMM Face Database, which contains more than 200 faces, as well as in a real-time test. The experimental results show that the system has good accuracy and robustness.

Attitude algorithm and initial alignment method for SINS applied in short-range aircraft

This paper presents an attitude solution algorithm based on the Micro-Electro-Mechanical System and quaternion method. We completed the numerical calculation and engineering practice by adopting fourth-order Runge–Kutta algorithm in the digital signal processor. The state space mathematical model of initial alignment in static base was established, and the initial alignment method based on Kalman filter was proposed. Based on the hardware in the loop simulation platform, the short-range flight simulation test and the actual flight test were carried out. The results show that the error of pitch, yaw and roll angle is fast convergent, and the fitting rate between flight simulation and flight test is more than 85%.

Bifurcation of Lane Change and Control on Highway for Tractor-Semitrailer under Rainy Weather

A new method is proposed for analyzing the nonlinear dynamics and stability in lane changes on highways for tractor-semitrailer under rainy weather. Unlike most of the literature associated with a simulated linear dynamic model for tractor-semitrailers steady steering on dry road, a verified 5DOF mechanical model with nonlinear tire based on vehicle test was used in the lane change simulation on low adhesion coefficient road. According to Jacobian matrix eigenvalues of the vehicle model, bifurcations of steady steering and sinusoidal steering on highways under rainy weather were investigated using a numerical method. Furthermore, based on feedback linearization theory, taking the tractor yaw rate and joint angle as control objects, a feedback linearization controller combined with AFS and DYC was established. The numerical simulation results reveal that Hopf bifurcations are identified in steady and sinusoidal steering conditions, which translate into an oscillatory behavior leading to instability. And simulations of urgent step and single-lane change in high velocity show that the designed controller has good effects on eliminating bifurcations and improving lateral stability of tractor-semitrailer, during lane changing on highway under rainy weather. It is a valuable reference for safety design of tractor-semitrailers to improve the traffic safety with driver-vehicle-road closed-loop system.

A Pedestrian Detection Method Based on Hierarchical Tree Cascade Classification at Nighttime

AbstractIllumination, for pedestrian detection at nighttime is weak, and detection is easily affected through variations in illumination. Thus, a bicharacteristic method of pedestrian detection at nighttime based on hierarchical tree cascade classification is presented according to “coarse-to-fine” principle. The proposed method consists of two stages of cascade classifiers. Coarse cascade classifiers are constructed in complete binary tree architecture. These classifiers use Haar-like features for the rapid identification of candidate pedestrian areas. By contrast, fine cascade classifiers have a parallel structure. Edgelet features are used for detection along three parts: the head-shoulder, trunk, and leg parts of candidate pedestrian areas. Bayesian decision-making is adopted to achieve pedestrian target detection and a comprehensive analysis of the detection results from these three parts. Experiments show that the proposed method has high accuracy, ideal real-time performance, and strong reliability...