In order to solve the problem that the vibration of vehicle on uneven road will damage the vehicle components and affect the comfort of passengers, a damping method of active suspension with time delay feedback control in quarter car model is proposed. The suspension model has two degrees of freedom, which is composed of body mass and unsprung mass. In the range of parameters, taking the vehicle body vertical acceleration, suspension dynamic deflection and tire dynamic displacement as the optimization objectives, the particle swarm optimization algorithm is used to obtain the optimal control parameters. The simulation results show that, compared with the passive suspension, the control active suspension with time-delay feedback can reduce the vertical acceleration of vehicle body obviously under harmonic excitation, and has better damping effect. The active suspension with time delay feedback control has advantages in improving ride comfort and ride comfort.

This paper outlines a proposal for serving working professionals in industry by offering them two programs of study to enhance their education and improve their job prospects. The programs was specifically designed to meet the needs of the manufacturing industry in Texas. The courses are proposed to be offered online  because we expected working people to be interested in this program. By offering courses online we can attract a new group of working students that are constrained by their jobs from being able to take regular courses.

The performance of walking vehicle based on bionic foot robot is better than that of wheeled vehicle and tracked vehicle when it works in off-road and harsh environment. Through the imitation of various animal structural forms and movement modes, a variety of leg and foot structures came into being. Aiming at the complexity of quadruped vehicle model, straight and steering gait problems, a quadruped vehicle simulation platform is built. Using Solid Works to establish the model and obtain the kinematic equation. Adams is used to simulate and analyze the parameters at the center of mass of the vehicle, which proves the stability of the quadruped vehicle and lays the foundation for the dynamics and trajectory planning of the quadruped vehicle.

Pedestrian detection is a basic part of intelligent transportation, intelligent monitoring, multimedia retrieval and other fields. Pedestrian detection technology has a wide range of applications and has become a popular research object in the field of computer vision. However, factors such as pedestrian's posture, appearance, number, direction, movement, occlusion of the scene and changes in illumination will affect the detection performance, which is the difficulty of pedestrian detection technology. This paper uses gradient direction histogram (HOG) as the feature to detect pedestrian targets. Firstly, the basic outline of the moving object is extracted, then 8 features are extracted from the moving object with star vector representation, and the height, width and height are taken as the other 3 features. Finally, the SVM classifier is constructed to realize the image classification and recognition based on SVM. Experimental results show that this method can quickly and accurately detect and classify moving pedestrians in video surveillance, and the detection results are more accurate.

Our aim in this article is to introduce the stages of development of solutions of third-degree equations, dealing with some problems leading to that kind, and the attempts of Arab and Muslim mathematicians to solve them geometrically and algebraically.

In this study, a part of the car control by wire system, the communication system is designed. The communication system determines the real-time, efficiency and reliability of the whole control by wire system. Taking STM32 development board as the core, the hardware and software of CAN communication system are designed. In terms of software design, based on the characteristics of embedded system kernel of STM32 development board, the expected functions can be realized according to the needs of developers. In terms of hardware design, CAN communication system includes two communication nodes, which are called master node and sub-node. The master node is responsible for receiving the serial port 232 signal of the host computer system, converting the received serial port 232 signal into CAN signal, and finally sending it to the sub-node; The sub-node is responsible for receiving the signal sent by the master node, and the microprocessor analyzes the received signal, and then controls the motor according to the specific signal to complete the design of STM32 communication system for motor control.

In order to study the influence of time-delay feedback control on system stability, a two-degree-of-freedom model with time-delay feedback control is established. The range of the feedback gain coefficient and the critical time delay of the stability switching point are derived by using the stability switching method. The results show that the existence of time delay does not lead to system deterioration in the stable interval with full time delay. Near the stability switching point, the time delay can make the system stable or unstable, and the value of gain directly affects the time delay. Therefore, selecting appropriate feedback control parameters can not only stabilize the time-delay system, but also effectively suppress the vibration of the system.

In order to realize the development of the lateral stability control strategy of the trailer-mounted RV, it is necessary to use Carsim's existing vehicle model to establish a joint simulation of Simulink and Carsim to realize the purpose of simulation and verification of the control strategy. Here it is necessary to establish a multi-degree-of-freedom trailer model and a trailer-mounted carsim model, and compare and verify the accuracy of the multi-degree-of-freedom motorhome model. Through verification, it is found that the trajectory-following effect of the established trailer-mounted RV dynamic model is good, which shows that the built model has high accuracy and lays a research foundation for the subsequent RV lateral stability control.

In order to study the lateral shimmy phenomenon of a Trailer-mounted RV during driving, a dynamic model of a certain type of tractor-trailer was established, and the accuracy of the model was verified by the snake test of the real vehicle. The effects of nose mass of trailer, trailer yaw inertia, trailer mass and tire pressure on lateral stability of the Trailer-mounted RV were analyzed. The results show that when the nose mass of the trailer is about 10 %, it is conducive to the lateral stability of the Trailer-mounted RV. Reducing the trailer yaw inertia will improve the lateral stability of the Trailer-mounted RV. Tractor tire pressure slightly lower than RV tire pressure is also conducive to the lateral stability of RV. Changes in the mass of the trailer alone will not significantly affect the lateral stability of the Trailer-mounted RV.

In this paper we introduce and study the new class of closed sets in topological spaces namely generalized #rg-closed (briefly, g#rg-closed) sets. This class lies in between the class of strongly generalized closed (briefly, g*-closed) sets and the class of regular generalized closed (briefly, rg-closed) sets. Also, we will study their properties in compare with existed classes.

In order to analyze the driving stability of a trailer-mounted RV, a certain model of trailer-mounted RV train dynamics model was established. Through a combination of theoretical analysis and simulation experiments, the driving stability of the trailer-mounted touring car train under steady-state steering, turning braking, emergency steering, and high-speed line shifting is studied.

The driving behavior of the vehicle is composed of horizontal driving behavior and vertical driving behavior vectors. There are the basic modules of autonomous driving. From the viewpoint of the lateral position of the vehicle in the lane, the lateral driving state of the vehicle can be divided into left deviation, left offset, straight, right offset and right deviation, and the five lateral driving states can constitute different lateral driving behaviors. In order to realize the recognition of these five lateral driving states, a recognition model based on generalized neural network was proposed. Collect virtual driving data, firstly pre-process and factor analysis the data, secondly use k-fold cross validation loop to find the optimal SPREAD, and finally sample data for generalized neural network training and testing. The results show that the model recognition rate can reach 93.63%, which is better than the BP neural network recognition result. It is ideal and can support the research of driving behavior.

In this paper an experimental investigation was carried out to study the strength properties of concrete partially replacing the cement content by slag powder. four series of concrete mixes were cast. The first series included normal concrete 0% replacement mix, the second series included 10% replacement mix, the third series included 15% replacement mix and the fourth series included 20% replacement mix. Each series included one mix with 350 kg/m³ cement content of CEMI 42.5 type plus 1% super plasticizer as a mineral additive in all mixes. The study of compressive, split tensile and flexural strengths were done on 60 specimens, 24 plain cube specimens of size 150 x 150 x 150mm, 24 cylinders specimens of size 150mm dia. and 300mm height and 12 beams specimens of size 150x150x750 mm. The recorded results show that the increase in dosage of the slag powder as a replacement of cement content gives upmost reading in all previous strength tests.

In order to better improve the ability and fuel economy of plug-in hybrid electric vehicle (PHEV) to cope with slippery and complex roads, a two-axle drive configuration of PHEV was proposed to avoid the problems such as single axle drive mode, low efficiency and inability to meet the high torque demand. On the basis of this configuration, the working mode is divided and formulated, and the vehicle model and control strategy are built based on Matlab \Simulink. The accuracy of the built model and the effectiveness of the strategy are verified. The simulation results show that this configuration can accurately switch modes, effectively improve the endurance range, and achieve significant energy saving effect.

Cylindrical spiral spring is an important part of railway vehicle suspension system. Based on the theory of optimal design and according to the design requirements of spiral spring, the mathematical model of optimal design was established, and the optimization design system of cylindrical spiral spring was developed by using Matlab App Designer. The results show that the system is simple in operation and reasonable in optimization. It can be applied to the optimization design of cylindrical spiral spring and improve the working efficiency.

According to the characteristics of the double wishbone independent suspension, according to the geometric relationship of the guide mechanism of the suspension in the transverse plane, longitudinal plane and horizontal plane, the hard point coordinates of the suspension are designed reasonably, so that the suspension can maintain good kinematic characteristics and improve the vehicle performance. The simulation model of double wishbone independent suspension was established in the ADAMS/CAR module, and the variation law of wheel positioning parameters with wheel jumping up and down was analyzed. The wheel positioning parameters were taken as the optimization objective, and the hard point coordinate parameters of the guide mechanism were taken as the design variables for simulation optimization.    The optimization results show that the kinematics performance of the suspension is improved by optimizing the hard point coordinates of the steering mechanism.

Aiming at the problem of traffic flow prediction in intelligent transportation system (ITS), an improved long-term and short-term memory network (LSTM) model is proposed. This model uses attention mechanism to give different weights to the characteristics of different time points in historical time series, and then it can mine more effective information and improve the accuracy of the model when predicting future traffic flow. By comparing with support vector regression (SVR), BP neural network and LSTM, it can be found that this model has more effective prediction accuracy and model stability.

In view of the problems of difficult power system arrangement and unreasonable axle load distribution of traditional range-extended electric vehicles, the power system configuration of range extender front in-wheel motor rear drive is constructed, and the power system parameters are matched, the vehicle control strategy is built based on MATLAB\Simulink, and the power and economy of the vehicle are analyzed under NEDC conditions using AVL Cruise simulation software. The simulation results show that the proposed powertrain scheme meets the requirements of power and economy of the vehicle, and each operating mode can be turned on or off under specific operating conditions, and the built control strategy is consistent with the operating mode of the extended program electric vehicle.

A combined algorithm based on Genetic Algorithm Optimized BP neural network (GA-BP) is proposed to predict battery charging energy, this method is based on data exploration, feature engineering and model screening of charging data. The error is selected as the evaluation index of the prediction results. By processing the platform data, the input characteristic variables with large correlation with charging energy are obtained. In order to facilitate the training of subsequent models, the input characteristic variables are normalized. The neural network model optimized by genetic algorithm is established, and the segment charging energy is predicted by using the processed real vehicle data.