Aiming at driver panic or other factors causing the lack of braking force and decreasing the driver's braking operating burden when driving on a long ramp, HBA and HDC control strategy is carried out by Stateflow state machine theory and Matlab/Simulink. The brake pedal displacement and speed are selected as the identification parameters to better identify the driver intention. Meanwhile, the ramp recognition is designed by Newton's second law. Considering the braking problem of high temperature failure, the temperature model is built. Based on the above, MIL and HIL are carried out, the results verify the correctness of the control strategy. In addition, road tests' results show the HBA function can meet the ECE standard and the HDC function can keep vehicle speed near the target speed, proving that the control strategy achieved good control effect.

To solve the problem of road roughness identification, a NARX neural network identification method and its applicability are studied based on vehicle responses. A four degree of freedom plane model of vehicle vibration system is established, thus, the vehicle responses and road roughness of wheel can be obtained by simulation. The application selection, input scheme optimization and evaluation index of NARX neural network are studied, and the solutions of vehicle response selection and its combination optimization are put forward. The NARX neural network is used to identify the road roughness at front wheel of a car under the common road grade B and 60 km/h driving speed, for which the correlation coefficient and root mean square error are 96.75% and 0.003 3, respectively. The influences of training sampling points, vehicle response random noise, vehicle speed, and road grade on the NARX neural network are considered, and the adaptability of NARX neural network method for road roughness identification based on vehicle responses is illustrated. The results show that the use of orthogonal test design to determine the optimal input scheme of the NARX neural network and the identification of road roughness based on vehicle responses can achieve satisfactory performance and good applicability.

In order to intelligently solve the problems existing in urban road networks and improve the accuracy of short-term traffic flow prediction, a short-term traffic prediction model is established by using the least square support vector machine (LSSVM). Specifically, the immune algorithm is adopted to optimize the penalty factor and kernel parameters of the LSSVM, thus obtaining the optimal prediction model. The prediction simulation experiment takes the average speed and occupancy rate of vehicles as the input of the model to predict the traffic flow. The experimental results show that the prediction error of the optimized LSSVM model used in the simulation experiment is reduced, and the output result is closer to the real value.

In order to provide reference for setting on-street parking space that occupies vehicle lane, traffic flow parameters survey was conducted under the interruption of on-street paring. The changing rules of cars’ saturated headway with the number of on-street parking cars were analyzed. The models between the saturated headway with the number of on-street parking cars on adjacent lane and interval lane were established respectively using SPSS software. Based on established models, suggested thresholds of traffic volume for adjacent lane and interval lane were given to set on-street parking lot, and case study was conducted. It shows that cars' saturated headway on adjacent lane and interval lane increases with the number of on-street parking cars and there are quadratic function relations between them. With the increase in the number of on-street paring cars the road design speed increases, and the adjustment factor decreases for possible capacity, so the setting of on-street parking lot is more improper. When the number of on-street parking car is the same, adjustment factor for possible capacity of interval lane is larger than that of adjacent lane, so the influence of on-street parking on traffic operation of interval lane is less than that of adjacent lane.

To solve the issue of the single ability for robot in the nuclear power plant, an autonomous exchange mechanism of the end-effector for robot is developed. The interface of multi-torque output with the concentric and parallel mechanism with 3-Hooke joints is used to provide power input for the end-effector with related operations. Based on analysis of the passive compliance and tolerance condition for the docking process of the double Hooke joints between the end-effector exchange and the tool rack, an automatic docking control strategy of the end-effectors exchange is proposed based on the contact force threshold. The automatic replacement of different end-effectors is realized by experiments, and the feasibility of the control strategy is verified. The mechanism prototype for end-effector exchange is designed. The exchange experiments of different end-effectors are carried out by the SCHUNK 6 DOF manipulator mobile experiment platform, which demonstrate the effectiveness of the control strategy, the tolerance performance of the mechanism. The experimental results show that the mechanism has completed docking process with larger tolerance compliant and realized the power transmission of the end-effector.

The fingerprint indoor localization method based on the Received Signal Strength (RSS) is vulnerable to multipath effect and noise interference, resulting in low positioning accuracy. To solve this problem, an indoor positioning method based on location fingerprinting of imitating the mechanism of scorpion vibration source location is proposed. Firstly, the method imitates the n/1 neuron configuration of scorpion to construct the neuron structure, in order to encode the vibration signal and transform the vibration signal into pulses. Secondly, pulses are extracted as the location fingerprint feature, and then the location fingerprint feature database is established by the number of pulses. Finally, the Weighted K-Nearest Neighbours algorithm is used to estimate the position of vibration source. To verify the performance of the proposed algorithm, a vibration signal acquisition system is set up to imitate the vibration perception of scorpions. It is used to collect the user's step signals in the indoor environment. The experimental results indicate that the proposed method can improve the average positioning accuracy by 0.148 4 meters compared with the location fingerprinting based on RSS.

A novel multi-objective optimal design method is proposed for gearhead and ball screw two-stage driven electromechanical Brake actuator (EMB). With consideration of important factors, such as two stage driving, discrete transmission ratio, dynamic resistant torque, transmission inertia and feasibility constraints related to the component characteristics, this method can applied to determine the optimal combination of motor, gearhead and ball screw. First, the loads and motion laws were analyzed based on the dynamic models of EMB for emergency braking and anti-lock braking on dry asphalt road. Then, all feasible motors and ball screws, which can drive the load and satisfy the requirement for actuator size, feasible torque and speed of motor, characteristics of the planetary gears and ball-screw, were selected among the catalogues. Second, the planetary gears were designed according to the combinations of feasible motors and ball-screws to minimize the size of the planetary gear with the constraints of Hertzian pressure and bending fatigue strength, respectively, thus all feasible combinations of motor, gar ratio and ball-screw were achieved. Finally, the multi-objective optimal combination was obtained with respect to actuator weight, starting acceleration, air gap closing time during braking, and motor output torque.

A state-preference survey on drivers' route selection is conducted by designing the simulation scenario with real-time traffic condition in Vissim. A route selection forecasting model is constructed with binary logit model. The impact of habit and traffic condition on the drivers' route decision is estimated using this model. Results indicate that both the habit and traffic condition impact the drivers' route selection, however, the influence of habit is greater than the traffic condition. Besides, the effects of both factors vary with the changing traffic condition. A real-world forecasting experiment proves that the proposed model can be applied to predict the selection probability between habit route and alternative route according to traffic condition with satisfactory prediction accuracy. The results can be applied to real-time prediction and recommendation of travel route in vehicle navigation software.

A new hydraulic muffler is designed based on the mechanism of pressure ripple reduction by accumulator group with several accumulators installed in series. This design takes advantages of the characteristics of noise elimination and structure of Helmholtz muffler. The mathematical models of the accumulator group and the new hydraulic muffler are developed. The effects of a single accumulator, an accumulator group and the new hydraulic muffler on the pressure ripple reduction are investigated by numerical simulation using the Method of Characteristics (MOC) and FORTRAN language. The simulation results are compared with experimental data, which verifies the simulation model and calculation method. It is shown that the new hydraulic muffler can more effectively reduce the pressure ripple than the traditional accumulator, meanwhile its structure is smaller than the accumulator group, which is important in engineering application.

To overcome the current deficiency in studying the Rollover Stability (RS) of Semi-mounted Agricultural Machine Unit (SMAMU, including a tractor and semi-mounted machine), a new method to characterize the RS of SMAMU is proposed. The Lateral Load Transfer Ratio (LLTR) is chosen as the evaluation indicator of RS, the rollover mathematical model is established and quasi static simulation is carried out. Through ADAMS dynamic modeling, the simulation results are in good agreement with the mathematical model, which verifies the correctness of the theoretical model. The effects of the parameters of SMAMU on the RS are discussed and the sensitivity of the influencing factors is analyzed. The LLTR is correlated to the height of center of gravity, the wheel-base of the tractor, the weight of the SMAMU, the wheel-center-distance, the distance from the center of gravity to the tow point and the height of tow point. The results show that the height of the center of gravity and the wheel-base of both the tractor and the semi-mounted machine are the important factors affecting the RS. Besides reducing the height of center of gravity or increasing the wheel-base, reducing the height of the tow point or increasing the distance from the center of gravity to the tow point can also improve RS. This work may provide reference for the optimal design of SMAMU.

Taking the actual physical cache as the measurement of the buffered video, an adaptive algorithm based on physical caching of the video is proposed. The algorithm adjusts the bitrate of the video according to the buffer occupancy rate and the estimated throughput of the Internet. The performance tests are conducted under two virtual network conditions and two real network conditions. The results show that the proposed algorithm can reduce the sensitivity of the video bitrate to the change of the buffer and avoid the buffer frequent fluctuation. Compared with the traditional algorithm, the proposed algorithm is superior in terms of Quality of Experience (QoE).

In order to solve the trajectory planning of intelligent vehicle with multi-constraint conditions in unknown environment, a rolling optimization scheme is presented. A feasible trajectory planning method in the local environment is proposed via vehicle dynamic study. With the characteristics of smooth trajectories of six polynomials, the process of trajectory planning is transformed into solving a single polynomial coefficient. The obstacles in the planning window are classified according to the metric function, and the optimal trajectory and vehicle speed are decided according to the optima index. Simulink and CarSim are used to develop the environmental model and the trajectory model. The effectiveness of the planning scheme is verified by simulation study.

The traffic flows in the junction bottleneck area of urban expressway under normal weather condition, and under snow and ice conditions were investigated by video footage and manual counts. Then, the key values of the urban expressway running characteristics in the on-ramp bottleneck area were obtained, by which the improved Cell Transmission Model can be used to perform simulation of the running state of urban expressway. Furthermore, a variable speed-limit control method under snow and ice conditions was put forward, and simulation was carried out. Simulation results show that during the traffic congestion time, using the proposed method, the traffic efficiency is increased by 16.16 in the junction bottleneck area of urban expressway under snow and ice condition, effectively avoiding serious traffic congestion.

The key of realizing the cross dock is to design the joint of inbound trucks and out bound trucks. A proper sequence makes the cross docking more efficient and needs less makespan. Regarding the number of items in the temporary inventory was proportional to the makespan, this paper transfers the objective function of minimizing the makespan into minimizing the number of items in the temporary inventory. An Improved Harmony Search (IHS) algorithm is proposed to solve the optimization problem. Based on the solving limitation on the parameter value of harmony search algorithm, dynamic adjustment method is used to set parameters. The fixed parameters optimized by Taguchi experiments effectively improve the accuracy of solutions further. The simulation results show that the IHS solutions are more close to the overall optimal solutions than the Harmony Search and Tabu Search. HIS is better in terms of searching for optimal solutions to solve the problem of sequencing among inbound and outbound trucks.

In this paper, we propose an automatic music composition algorithm based on Long Short Term Memory-Recurrent Neural Network (LSTM-RNN). In this algorithm, we first divide music set into set which consists sequences of unit by length, and in the preprocessing we get the Mel frequency cepstrum coefficient as the feature of audio music. Second, the proposed training samples are trained and predicted by LSTM-RNN. Finally, the generated music sequences are joined to get a new music. In order to verify the effectiveness of the algorithm, we carry out an anonymous evaluation of the original music and the music generated by the algorithm. The results show that the algorithm can work well on automatic music composition.

A space vector model is proposed to overcome the lack of spatial location information in the bag-of-words model. The model turns visual words into vector model using the space location information of visual words to represent image, thereby achieves better classification performance. Experiments are carried out on two standard image datasets Caltech-101 and Caltech-256, respectively, with Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) classifiers. The results show that the space vector model can effectively improve the Average Classification Accuracy (ACA) and Average Category Precision (ACP), and has a good classification effect.

According to the commonly used braking energy recovery rate and driving range increase rate of the braking energy recovery evaluation index, the vehicle specific system scheme and the braking force distribution are analyzed. Then, a braking energy recovery evaluation method based on wheel cylinder pressure is put forward considering the opening degree of the vehicle Controller Area Network (CAN) protocol. The wheel cylinder pressure signal is acquired by pressure sensor. Vehicle test is carried out and the results show that, with relative error rate less than 6%, the proposed method is feasible, which enriches the braking energy recovery evaluation theory.

In this paper the vibration and noise of an electric bus were studied under the conditions of uniform speed and acceleration. The LMS instruments were applied to collect the vibration and noise signals of the electric bus. The source and the characteristics of the noise and vibration were studied by spectrum and order tracking analysis. The results show that the vibration inside the bus is mainly induced by the road excitation via the suspensions under uniform speed condition, while the motor noise is sharp under accelerating condition especially in the switch frequency. This study may provide useful information for reducing the noise and vibration of electric vehicles.

Hepatic trauma induced in traffic accidents is one of the most common injury patterns, causing high fatality rate. Human liver biomechanical responses associated with frontal impacts, oblique impacts were studied using simplified Chinese human body Finite Element Model (FEM), assembling with more geometrical-accurate liver model and an average Chinese adult male model from high resolution CT data. The model was than applied for studying liver dynamic response and injuries in frontal and oblique pendulum impact simulations at low, middle and high velocities. Analysis of dynamic response and pressure distribution with high injury risk on liver was performed. Pressure and peak strain that may induce hepatic injuries were computed from the model simulations and were analyzed about the correlation with global parameters, such as thoracic deflection, viscous criterion value, contact force. It indicates that using single variable representing liver response is questionable under different loading boundaries.

In this paper a quantum k-means algorithm is proposed by integrating the quantum paradigm to improve the efficiency of traditional k-means algorithm. First, each vector and k cluster centers are prepared to be in quantum superposition, which are then utilized to compute the similarities in parallel. Second, the quantum amplitude estimation algorithm is applied to convert the similarities into quantum bit. Finally, from the quantum bit the most similar center of the vector is obtained using the quantum algorithm for determining the minimum. Theoretical analysis shows that, compared with the traditional quantum algorithm, the time complexity of the quantum k-means algorithm decreases under given condition and the space complexity diminishes exponentially.

Inspired sand scorpions in locating their preys, a novel bionic localization method is proposed to solve the problem of vibration event localization. Different from commonly used methods, a spike firing model is introduced to solve the problem of arrival picking. Based on the 3/1 configuration, each spike firing model fires different number of spikes. The vibration signal is coded into spike signal for orientation of the target using population vector code. According to the actual situation and the selectivity of the biological evolution, the distribution of the receivers is modified and compared with that of before modification. Also the bionic method is compared with the TDOA method in simulation environment. The orientation errors of the bionic method are smaller than that of the TDOA method. In addition, location experiment is carried out in an open area. The average error of landing orientation is 4.9310° for 76 sets of data, satisfying the orientation requirement.

Based on fluid-solid interaction method, simulation analysis of the flow around the external rearview mirror was carried out to investigate the mechanism of fluid-induced vibration, and the main vibration forms were described. First, the rigid external rearview mirror model was investigated to get the drag coefficient C_d, and lift coefficient C_l, which provide a comparison basis for the study of fluid-induced vibration and verify the feasibility of the simulation program. Then, the flow around the external rearview mirror was simulated by numerical method to investigate the vibration characteristics of the mirror under different velocities. The changes of the drag and lift coefficients, vibration amplitude, frequency of vortex shedding and other parameters with the velocity were obtained. Results show that strong vibration of the mirror occurs when the vertex shedding frequency is approach to the structural natural frequency of the external rearview mirror, and the vibration strength is far greater than the impact strength of the wind.

Using a high fidelity driving simulator with eight degrees of freedom, the effect of low visibility in haze weather condition on the driving behavior of three Car-Following (CF) stages (acceleration, deceleration and steady following stages) are analyzed from both engineering CF models and psychological-physiological CF model. The results show that the low visibility environment in haze weather condition has significantly different impacts on driving behavior of different CF stages. In acceleration CF stage, the drivers' sensitivity in changes of relative speed and spacing, as well as maximum desired acceleration under haze weather condition are significantly lower, 29.3%, 33.1% and 17.4% respectively, than that under clear weather condition. Meanwhile the heterogeneities in driving behavior are substantially larger in haze weather condition. In the deceleration stage, drivers' sensitivity in changes of relative speed, maximum desired deceleration and expected maximum deceleration of the leading vehicle under haze weather condition are significantly larger, 31.7%, 17.8% and 16.3% respectively, than that in clear weather condition. Whereas, the drivers' sensitivity in change of the spacing decreases by 32.1% in haze weather condition. In steady CF stage, the drivers have larger sensitivities in changes of relative speed, 41.6% higher in average in haze weather than that in clear weather, and have slightly smaller maximum desired acceleration and deceleration. However, there are no significant differences in desired speed and drivers' reaction to the change in spacing under different weather conditions. Moreover, the action points of acceleration and deceleration indicate that the drivers under low visibility in haze weather adopt quicker acceleration to follow the leading vehicle more closely, and are more cautious to take quicker braking action to avoid collision. The main findings of this paper provide references for setting-up of microscopic simulation for emergency traffic evacuation in case of low visibility in haze weather condition.

In the process of the digital hydraulic pumps/motors displacement shifting, the torque impacts problem which influences the ride performance has always been found. Some researches had been made for torque impact mechanism and its inhibition. According to the experiment results, in the process of digital control there exists a different degree of hysteresis between pressure establish-ment/disestablishment and signal outgoing in different diameters of reversing valves, which causes pressure superposition of multi-stage pump and further leads to the additive effect of impact. In order to solve the above-mentioned problem, on the basis of the re-sponse time for reversing valves and system pressure impact, a step sequence control strategy had been formulated. Then the control strategy had been simulated by using AMESim software, and verified the strategy by way of experiments. Experiment results show that the step sequence control strategy reduces impact degree during the process of displacement shifting by 23%, relieves the sys-tem's torque impact effectively, and satisfies the dynamic continuity principle of the system.

For parts with complex surfaces, a 3D scanning measurement method for full profile was proposed. To obtain the shape deviation of the part, the scanning model was built by reverse modeling and used to compare with the design model. The proposed method was used to measure the blade out arc hollow parts of a large nuclear power steam turbine, and then compared with the designed model. The measuring results show that the largest positive and negative deviations are 2.59 mm and -3.03 mm, respectively. Compared with the traditional special fixture, the 3D full profile measurement method can be used to measure various complex parts rapidly, and it has the characteristics of full data and high precision. To solve the springback problem of the part, springback compensation for the part with complex surface based on reverse engineering was introduced. After springback compensation for the blade out arc hollow part, The molds were processed and tested. The results show that the final largest positive and negative deviations are 1.36 mm and -1.43 mm, which meet the requirement of the shape deviation of that part.

Regarding that the videos collected by intelligent monitoring system in coal mine underground are blur, a novel algorithm for unclear video object detection based on improved particle filter is proposed. In the framework of standard particle filter, a nonlinear, non-Gaussian and multi system state space fusion model is constructed based on frame difference. First, particle sampling and probability density propagation are realized in the region of the key points obtained in the frame difference image. Then, the weighted posterior sample particles are used to represent the posterior probability density of the multi system state space fusion model. The mean of the samples is used to estimate and fuse the posteriori state of the system. Finally, the system state space model is output to fulfill the object detection. Experiments are carried out using the video data of the Sanjiaohe coal mine underground monitoring system. The performance of the proposed model is evaluated by comparison with extended Kalman filter, unscented Kalman filter and particle filter. The improved accuracy and effectiveness of the proposed method are demonstrated.

A coordinated control system is developed for the regenerative and hydraulic braking systems in electric-wheel vehicle. The control system is based on real calculation of wheel slip ratio model to improve the stability of the electric-wheel vehicle in emergency braking process. Antilock braking control is realized by reducing the motor torque with setting a series of threshold values of slip ratio, which are compared with instantaneous longitudinal slip ratio calculated according to wheel speed, based on a redesign of hydraulic braking system. A 15 DOF vehicle model is established in AMESim and Anti-lock Braking System (ABS) control model is established in Simulink. Simulation is carried out at low, middle and high grade of adhesion coefficient of the road. Results show that the proposed control strategy can prevent the wheel from locking as efficient recovery of braking energy, and ensure the braking stability of the vehicle.

The relationship between the modifications of spot-welding mass matrices or rigidity matrices and Body in White (BIW) structural dynamic characteristics is investigated. First, the spot-welding parameters of shell structures in BIW are identified in order to describe the actual structural frequencies and vibration mode. Then, the method of Elastic-Plastic Beam with Parameter Identification (EPBPI) is employed to simulate spot-welding. Finally, the EPBPI method is compared with the universal method of elastic-plastic beam spot-welding in dynamic characteristic analysis, and it is applied to simulate of the dynamic characteristics of a real BIW to further validate the simulation accuracy. Results show that the EPBPI spot-welding simulation method can improve the accuracy of dynamic characteristic simulation of shell structure and provide a research method for spot-welding numerical simulation.

In order to study the visual characteristics of the driver under stress condition, the eye movement data of drivers under different stress scenarios are analyzed. The dynamic clustering method is used to divide the gaze area, and the related visual characteristic indexes are selected to analyze. The principal component analysis and statistical analysis methods are used to analyze the eye movement data of the drivers. Test results show that when driver is under the stress scene the visual distribution is more concentrated, and the driver is more accustomed to obtain traffic information from the main area of the front region. When a moving object is in the scene, the driver will judge the moving range of the object and select 1 to 2 related auxiliary areas for information retrieval. The driver is used to gaze the main area and scan the auxiliary areas.

In order to improve the loss of traffic efficiency caused by the application of variable speed limit control, the integration of adaptive cruise control and variable speed limit control is analyzed to control the highway traffic. The cruise control model is developed from the intelligent driver model, and then it is integrated with the variable speed limit control method. The microscopic traffic data of the NGSIM in the USA are used to calibrate the models. Simulations of the highway traffic are carried out. Results show that the integrated control method reduces the average increasing rate of vehicles' travel time by successfully declining the speed of the vehicles in the upstream of the bottleneck, thus improving the traffic efficiency of the highway. The results of this study may provide valuable information for highway traffic management.

Heat resistant bulk Al was prepared by mechanical milling, cold isostatic pressing and press-forming technique. The bulk Al possesses stable microstructure, with grain size between 0.6 and 4 μm, and the ultimate tensile strength, 536 MPa, surpasses that of most commercial Al alloys, especially at high temperature. The heat exposure experiment was carried out at 200 ℃, 300 ℃ and 350 ℃ for 4320 h. The high temperature endurance strength is 381 MPa, 242 MPa and 178 MPa corresponding to 200 ℃, 300 ℃ and 350 ℃ respectively. The pinning action of the second-phase dispersoids in bulk Al highly restrains grain growth during the process of hating.

Taking the PCR tyre 205/55R16 as the research object, finite element analysis model with complex patterns was established. The volume change behavior of pattern grooves in the contact zone was realized by simulating the tyre rolling process with Abaqus software, which was used as the boundary conditions of tyre pumping noise analysis. On this basis, the flow field characteristics in the pattern grooves were analyzed using Computational Fluid Dynamics (CFD) method, and the FW-H equation was applied to calculate the pumping noise of the tyre pattern. By analyzing the pattern deformation characteristics in the contact zone, the evaluation methods of pattern pumping noise and pattern volume deformation rate were determined. The results show that the pattern volume deformation rate can accurately predict pumping noise. On this basis, low noise structure of pattern groove reinforcement ribs was put forward. The pattern stiffness was strengthened and the pattern deformation was decreased by using the reinforcement ribs, and the noise was reduced by 3.68 dB.

Reinforced retaining wall has been widely used in highway construction, however, the vertical settlement, cross cracks of the pavement and outward-dipping deformation and other defects have occurred. These defects can even lead to partial collapse that impacts the traffic. Based on the defect survey of the reinforced retaining wall in Harbin City, the main forms of the defects are summarized. A section of road with typical defects is selected as an example to investigate the influences of fill properties, fill voids, ribbon fracture, seepage, traffic load and other factors on the horizontal deflection and the axial force using finite element software MIDAS-GTS NX. The causes of the defects of the reinforces retaining wall are systematically analyzed. Results show that the defects of the retaining wall are caused by the integrated actions of soil pressure, traffic load, pavement seepage and many other factors. The values of C and φ of the fill are the sensitive factors of the horizontal displacement of retaining wall. The pavement crack and seepage lead to the moisture increase, resulting in the decreases in C and φ, which is the factor of the outward-dipping deformation. Ribbon fracture, fill void and traffic load are important factors that lead to horizontal deformation of the retaining wall. This study may provide reference for the maintenance and strengthening of reinforced retaining walls.

To study and measure the drag-reduction performance of bionic functional surfaces with internal flow, a testing system based on differential pressure measurement was designed. Considering the characteristics of the internal flow, the test section is replacable to adapt to the flow field wall with different thickness. The data acquisition, processing and control system was designed based on programmable logic controller. The system precision was analyzed and the mean square errors of different flow velocities were calculated. The elastic silicone rubber and elastic thermal conductive bionic surface was tested using this system. The system can provide a high accuracy analysis and test platform for the study of drag-reduction performance of various bionic functional surfaces with internal flow.

First,the start-stop operation mechanism of hybrid vehicle is analyzed, and an AMESim simulation model is established, which can reflect the transient dynamics of the start-stop process. Second, according to the working principle of the engine start-stop system, the start-stop control problem is described as a speed tracking problem, and a simplified control-oriented model of the engine and motor coupling is proposed. Third, based on the nonlinear characteristics of the system, a nonlinear triple-step controller is designed, and the robust stability of the closed-loop system is analyzed using the input to state stability theory. Finally, the effectiveness and robustness of the triple-step controller is tested by co-simulation with AMESim and MATLAB/Simulink. Results show that the proposed control system can achieve fast and smooth start-stop of the engine.

To make full use of the scare spectrum resources shared by marine mammals and underwater acoustic sensor networks,a new marine mammal-friendly spectrum allocation algorithm in cognitive acoustic networks is proposed. First,the marine mammals are considered as the primary user and the sensor node is used as the secondary user.Then,the communication mechanism of the mammal-friendly cognitive acoustic networks is proposed.The utility function is established with the goal of maximizing the system capacity of the secondary user.Third, the secondary user's transmission power and channel allocation are solved by the Lagrange multiplier method combined with power control and channel allocation technique. Finally,the marine mammal-friendly cognitive acoustic network spectrum allocation mechanism and algorithm are designed,which can achieve the channel sharing of the primary user and the secondary user,as well as maximizing the spectrum efficiency.Simulation results show that the marine mammal-friendly cognitive acoustic spectrum allocation algorithm not only can avoid interference between the sensor nodes and the marine mammals, but also the bandwidth efficiency and system capacity are improved by 37.4% and 34.3% respectively.

In order to improve the performance of lane departure warning system, an unintentional lane departure analysis method is proposed. This method combines the driver's operation characteristics, vehicle's motion characteristics and the relationship between the vehicle and the lane. First, the unintentional lane departure is classified into two parts: lane departure by fatigue and lane departure by secondary task. Then, experiments of unintentional lane departure are carried out through the co-simulation platform based on CarSim and LabWIEW. Twelve drivers of different genders, proficiencies and driving behaviors are selected to participate the experiments. The unintentional lane departure parameters are collected and analyzed, including the driver's operation behavior, the motion characteristics of the vehicles and the relative motion position between the vehicle and the lane. Finally, an unintentional lane departure recognition model is constructed based on Gaussian Mixture-Hidden Markov Model (GM-HMM). The recognition results show good performance of the proposed model in online and offline tests.

“Pseudo subjective” method based on driving parameters of vehicles are commonly used to evaluate shift quality. This method indirectly reflects driver's subjective feelings by analyzing the vehicle running parameters, but ignores the human body's reaction in the shift process. In order to reflect the driver's subjective feelings, the driver model in the vehicle under shift condition is established and the human response spectrum is introduced to solve the problem for the first time. Gray relational theory is used to build the evaluation system. The system is verified by experiments to reflect the driver's feelings well.

Video-processing technology was used to acquire detailed spatio-temporal data of pedestrians, and the underlying law of the conflict between violating pedestrians and turning vehicles was analyzed, then a model of pedestrians' crossing position distribution was proposed. First, on the basis of the survey data, the relationship between conflict and pedestrian crossing distribution was qualitatively analyzed. Then, based on the analysis of pedestrians' crossing positions at seven surveyed crosswalks, the impacts of crosswalk length and elapsed time on pedestrians' crossing position distribution were investigated. Further, a Gauss function was applied to model the pedestrians' crossing position distribution at different times. Finally, the formulas about elapsed time, crosswalk length and three model parameters were established. The adjusted R² of the fitting models were 0.9, 0.93 and 0.97 respectively, which indicates that the proposed models can well represent the law of pedestrians' crossing position distribution. The proposed model was verified and the role of the model on determining the conflict zone was illustrated. An optimization method to reduce the conflict zone was put forward.

The forming process of the front-end three-dimensional skin of China Electric Multiple Units (CEMU) was simulated and analyzed using the general finite element software Autoform. The influences of the process parameters such as blankholder force, drawbead, die radius, draw depth, friction coefficient and die gap on the forming of the V-section skin with large thickness, shallow drawing depth and twisted structure were investigated. The reasons for the forming defects such as insufficient stretching and poor contour accuracy were analyzed and the controlling methods were proposed. The results show that insufficient stretching is mainly originated from the lack of flow resistance, which can be controlled by setting proper drawbead and increasing the blankholder force; for the investigated long strip skin in this work, variable intensity drawbead is recommended. Poor contour accuracy is mainly caused by large springback. Process parameter optimization can improve the contour accuracy to some extent, and degrees of the influence parameters are in the order: die radius > friction coefficient > die gap > draw depth. Compensation to the surface based on springback can significantly control the contour accuracy. For the 4 mm 5083-H111 aluminum alloy, the optimal compensation is 1.2 times of the springback amount. Forming tests were conducted according to the simulation results, and high quality compensations were achieved, which prove the validity of the proposed defect controlling methods.