According to the transmission system characteristics of pure electric loader, the ramp anti-slip control strategy was developed based on the operating parameters of loader and the torque and speed uploaded by the walking motor controller to the vehicle controller. By the vehicle controller, the conditions for the pure electric loader to enter the anti-slip mode was determined, and the proportional-integral（PI） algorithm was used to calculate the target torque delivered to the walking motor controller during the anti-slip mode for making the loader stable on the slope without pedal action. Based on Simulink, the ramp anti-slip control algorithm model of pure electric loader was established. By the Simulink automatic code generation technology, the vehicle controller programs were generated to conduct test verification and parameter optimization. The sliding distance of loader in slope parking and slope starting stage was used to measure the ramp anti-slip effect. The results show that the proposed ramp anti-slip strategy can effectively realize the standing slope on each slope. The maximum sliding distance is 8.0 cm when the loader stops on the slope at 30% slope, and the maximum sliding distance is 4.0 cm when the loader starts on the slope, which can meet the requirements for safe parking on slope.

To solve the problems of picking mushrooms manually in the factory mushroom growing environment with consuming time and labor， a mushroom picking robot was designed and developed. The mechanical structure of the picking robot system was designed by the modular design method, and the positive and negative kinematics solutions of the robot were deduced based on the D-H coordinate method to analyze the dynamic performance of the picking arm. The multi-objective optimization model of picking arm size structure was established for maximizing the picking efficiency, and the optimal solution was obtained with rapid iteration by genetic algorithm. The Adams virtual prototype model was established, and the picking dynamics simulation tests of the robot model before and after optimization were conducted. The simulation results show that under the same motor output torque, the maximum angular velocities of the big arm joint and the small arm joint are increased by 22.9% and 18.6%， respectively, while the single picking time is shortened from 1.60 s to 1.36 s with the picking speed increased by 15%. The developed physical prototype is suitable for the large area automatic picking operation in the sall multi-layer mushroom bed under the factory mushroom growing mode, and the single picking time is 2.0 s.

To predict the dynamic characteristics of the thermoelectric generator (TEG) system, a transient computational fluid dynamics (CFD) model for solving the temperature field distribution of TEG system and an analysis model for investigating the transient response characteristics of TEG modules were established based on COMSOL Multiphysics. A hybrid transient CFD-analysis model was proposed and validated through transient experiments. The results show that due to the thermal inertia effect, the conversion efficiency of TEG system exhibits momentary peak value. Compared to the transient fluctuations of exhaust gas temperature and mass flow rate, there is time lag in the hot and cold side temperatures of the thermoelectric semiconductor. Under the highway fuel economy test (HWFET) cycle conditions defined by the U.S. Environmental Protection Agency, by the transient model, the average output power and the average conversion efficiency of the entire TEG system are solved with 35.63 W and 3.40%, respectively. The average error of the transient model′s output voltage is 6.41%. By the proposed model, the transient response characteristics of the TEG system under transient thermal source excitation can be predicted with high accuracy and short computation time.

To improve the accuracy of path tracking and the vehicle handling stability in the process of automatic driving tracking, a trajectory tracking control method based on model predictive control principle and angle compensation was proposed. The overall control structure was divided into two layers, and the upper layer was the trajectory tracking control layer. According to the obtained road information and the driving state of the vehicle, the front wheel steering control input was determined by the model predictive control algorithm. In the lower layer, the sliding mode control theory was used to design the angle compensator, and the yaw rate deviation of the vehicle was taken as the control target to achieve accurate tracking. The results show that compared with the single-point preview strategy, the trajectory tracking control strategy based on model prediction and angle compensation can better control the vehicle to achieve trajectory tracking, and the peak values of yaw rate and sideslip angle are significantly reduced with better stability.

To realize the on-line detection of pH value of heterogeneous systems and provide stable reference potential, the polydopamine modified Ag/AgCl solid film reference electrode was developed by magnetron sputtering deposition of silver film and chlorination of NaClO solution to obtain AgCl layer and dopamine deposition modification film. The stability, reversibility and cyclic voltammetry characteristics of polydopamine modified electrodes with deposition times of 4, 8, 12 and 16 h were compared in phosphate buffered saline（PBS） solution. The results show that the standard deviation of response potential of reference electrode in PBS solution is about 1.00 mV. It can recover to relatively stable potential in different pH buffer solutions, and the deviation of the reference electrode is less than 5.00 mV with good reversibility. The response potential drift is small in 50 cyclic voltammetry tests. According to the sensitivity of the reference electrode ranging from 2.00 to 2.50 mV/pCl, the polydopamine modified electrode is not sensitive to chloride ion concentration, which confirms that the polydopamine modified reference electrode is feasible. The reference electrode with deposition time of 12 h has the best comprehensive performance in various tests. The application tests illuminate that the reference electrode is more suitable for the detection of pH of cultivation substrate.

To solve the problem that in traditional switching strategies for lateral tracking control algorithms in intelligent vehicles, the model matching strategy was always in active state with consuming computational resources and reducing motion smoothness, a control mode switching strategy based on least squares support vector machine (LSSVM) was designed. By the strategy, the control modes were dynamically switched based on error assessment under varying operational conditions. The control effectiveness was evaluated from three aspects of safety, comfort and tracking accuracy. The optimal control amount was executed in real time based on a multi-objective optimization mathematical model. The simulation results show that by the switching strategy, the superior lateral tracking performance in intelligent vehicles can be achieved under varying conditions with path tracking deviation range of ±0.1 m, yaw rate fluctuation range of ±2 （°）/s and jerk value range of ±10 m/s3. Compared to traditional single control algorithms, the proposed strategy exhibits improved tracking accuracy, stability and comfort.

To analyze the impact of the power system parameter matching design and energy management scheme on the vehicle performance, taking a fuel cell vehicle as research object, the parameters of main power system components were matched. The power-following energy management strategy and the fuzzy control-based energy management strategy were proposed to improve the economic performance of the vehicle, and the sliding average filtering algorithm was used to optimize the output of the fuzzy control strategy. To model the vehicle and energy management system, the joint simulation platform was established based on AVL-Cruise and Simulink to verify the power performance of the vehicle, and the economic performance of the vehicle under three control strategies was comparatively analyzed. The results show that the fuel cell output power curve of the optimized energy management strategy is smoother and is always within the high-efficiency output interval. Based on the principle of fuel cell priority protection, the optimized energy management strategy has the best performance.

To improve the seismic performance of prefabricated frame joints, based on bionics design, the replaceable artificial plastic hinge connection structure with the function of structural "fuse" was proposed, and nine replaceable artificial plastic hinge specimens with different parameters were designed. The low cyclic reciprocating load was applied to the replaceable artificial plastic hinge by Abaqus to investigate the seismic characteristics of the structure, such as failure mode, hysteretic performance and stiffness degradation. The results show that the failure position of the replaceable artificial plastic hinge structure is mainly concentrated at the flange buckling replaceable connecting plate, and the failure modes are flange buckling of replaceable connecting plate and shear deformation failure of shear dissipating rod. The hysteresis curve of beam end moment-angle is full with bolt slip phenomenon. The equivalent viscous damping coefficient is 0.30-0.45 with the ductility coefficient of 3.64-14.00, which illuminates that the proposed plastic hinge has good plastic deformation and energy-dissipation capacity.

Taking the building in hot summer and cold winter zone as research object, the transient system simulation program(TRNSYS）simulation platform was used to build the active phase change energy storage floor module. The simulation model of the active phase change cold storage floor air conditioning system and the conventional fan coil plus fresh air conditioning system was established, and the energy saving and economy were simulated and calculated. The effects of chilled water temperature on energy storage and release characteristics of active phase change energy storage floor, room temperature fluctuation and coefficient of performance (COP) of heat pump were investigated under the condition of night cold storage operation in the cooling season and typical day. The results show that under the condition of phase change cold storage at night，the optimal chilled water temperature is 9 ℃ when the cooling load per square meter is 74.78 W. When the cold storage heat pump adopts the intermittent operation scheme with low electricity price at night, the COP of heat pump operation can be effectively improved with reduced operation cost. Compared with the conventional fan coil plus fresh air air-conditioning system, the energy consumption of the active phase change energy storage floor air-conditioning system in the cooling season is reduced by 30.5% with operating cost reduced by 44.24%, and the comprehensive refrigeration energy efficiency ratio reaches 2.38 in summer.

To solve the shortcomings of single-network model with learning preference for data， the crop disease identification method was proposed based on multi-model fusion. The single model performance of four mainstream convolutional neural networks of ResNet50, DenseNet121, Xception and MobileNetV2 was evaluated by the proposed method, and the four single models were respectively conducted by multi-model feature-level and decision-level fusion to obtain the identification output. The feature-level fusion method was used to average, maximize and splice the final output feature layer of each sub-network to achieve efficient complementarity of heterogeneous features. The decision-level fusion method was used to maximize and average the output probability of each sub-network to achieve efficient union of probability distribution decisions. The experimental results on the PDR2018 crop disease datasets show that feature-level fusion outperforms decision-level fusion and single-model methods significantly. Among the fusion methods, splicing compression feature fusion achieves the highest recognition accuracy of 98.44%. The cross-database experiments on PlantDoc data subset and the actual images confirm that the feature fusion method exhibits superior accuracy and generalization performance compared to the single-model method.

The annealing was used to remove the adsorbed gases and impurities on graphene film, and the state of graphene surface was changed. The surface of graphene film before and after annealing was characterized in situ by atomic force microscope and Kelvin probe force microscope. The surface morphology and surface potential map of graphene film before and after annealing were obtained respectively. The work function was calculated according to the surface potential map, and the change mechanism of work function induced by annealing was analyzed. The results show that the annealing treatment causes the escape of water molecular between the graphene film and substrate, which reduces the gap between graphene film and SiO2 substrate and the P-type doping level of graphene film， resulting in the increasing of the Fermi level and the decreasing of work function.

To solve the problem that conventional linear Kalman filtering was increasingly unable to meet the demand of multi-motorized target tracking accuracy, a cooperative tracking method based on adaptive multi-model particle filtering was proposed. The host vehicle and the cooperative vehicle respectively executed the adaptive interactive multi model particle filter (AIMM-PF) algorithm to obtain the motion states of the target vehicles in the environment. By the cooperative vehicle, the tracked target state was sent to the host vehicle through vehicle-to-vehicle communication. The data association and data fusion techniques based on the Hungarian algorithm and the fast covariance crossover algorithm were utilized to achieve cooperative tracking of multiple maneuvering targets. The V2V communication, radar and localization simulation system were built to sense and track seven target vehicles within 200 meters range with two intelligent vehicles as the host vehicle and the cooperative vehicle, and the simulation experiments were completed. The results show that compared with the traditional single-vehicle tracking, by the cooperative tracking, the sensing range is expanded, and the tracking error is reduced by 31.1% without affecting the tracking efficiency.

 To improve the data detection accuracy of low-cost sensors in the original navigation system and the control effect of ship trajectory tracking, the data fusion algorithm was introduced to propose a new trajectory tracking algorithm. The multiple coordinate transformations of ship hull were conducted, and two Kalman filters were used to fuse more accurate ship heading angle, coordinates and velocity. The control algorithm based on eliminating trajectory velocity deviation and heading angle deviation was proposed. The traditional PID controller was designed as cascade control system with PI controller and  differential controller. The differential variables in the inner loop were precisely detected and transmitted by the existing accelerometers and gyroscopes to eliminate the adjusting differential parameters for achieving good control results of systems with low detection accuracy. The each required output of the two vessels on the ship was calculated to improve the effect of trajectory tracking. The multiple cruise tests of unmanned working ship were conducted on the experimental platform with real-time monitoring the ship status data and operating trajectory through upper computer，and the overall optimized trajectory tracking effect was analyzed. The results show that the heading angle, positioning and velocity fused by the Kalman filter have smaller data variance and are closer to ideal values. For the control algorithm， the overshoot of the system does not exceed 3%, and the response speed is fast enough with the steady-state error of about zero. After optimization，the success rate of the straight section for trajectory tracking is increased from 80% to 95%, and the success rate of the turning section is increased from 60% to 90%. The maximum average yaw distance of the straight section after optimization is decreased from 0.83 m to 0.12 m, and the maximum average yaw distance of the turning section is decreased from 1.25 m to 0.22 m. After turning, the average adjustment distance of 0.95 meters is required to enter the straight state, and the tracking effects of straight and turning sections are significantly improved.

Based on the characteristics of slotless brushless DC motor with small size, high power density and cogging torque, the slotless brushless micro DC motor for catheter pump was designed using flexible printed circuit board (FPCB) technology, and the loss analysis and optimal design of slotless brushless micro DC motor for catheter pump were conducted based on 3D multi-physical field coupling model analysis method. The results show that the copper loss of the slotless brushless micro DC motor for catheter pump accounts for about 88% of the whole motor loss, which is the main source of motor heating. In the temperature field simulation, the temperature change can change the motor loss and affect the motor output torque. In the flow field simulation model, the motor temperature can increase the human blood temperature and affect the blood compatibility. The flowing blood takes away part of the heat and reduces the motor temperature. The output torque of the pump motor with optimized winding is improved, and the loss is reduced.

To investigate the dynamic performance of long-span truss fiber reinforced polymer(FRP) bridge after repairing completion, the 92-meter-span FRP truss bridge model was established based on guide girder pushing. The vehicle-bridge coupling algorithm of long-span composite truss bridge was compiled to analyze the effects of speed, vehicle weight and road surface roughness on the mid-span vertical displacement, vertical acceleration and key member stress of the FRP truss bridge. The results show that the more uneven the road surface is, the greater the impact of the vehicle on the bridge structure is. The vertical displacement is more affected by the road surface level than that by the member stress. In the speed range from 20 km/h to 50 km/h, the impact coefficient is less affected by the speed change. When the vehicle speed exceeds 50 km/h, the influence of speed change on the impact coefficient is gradually increased. The peak curve of vehicle mass to bridge dynamic response shows linear increasing trend. When the vehicle mass is 2.80×104 kg with vehicle speed of 30 km/h, the maximum mid-span vertical displacement is 167 mm, which does not exceed the military emergency bridge displacement limit (L/120), indicating that the bridge design can meet the emergency traffic requirements.

To solve the problems of severe centralization and vulnerability to data tampering in traditional seafood traceability systems, the blockchain technology was employed to design the seafood traceability system based on hazard analysis and critical control points (HACCP). The multiple linear regression was used to process the sample data indicators and confirm the critical control points in the farming process. Based on the determination of key information, the smart contracts were designed to verify the uploaded data at each stage of seafood traceability. From the perspective of system feasibility, the detailed designs were conducted for system functionality, consensus topology and traceability coding. The seafood traceability system was developed and subjected to function and performance testing. The results show that the system transaction throughput is consistently around 320 transactions per second. The average transaction latency is approximate 0.5 s, and the transaction success rate is about 99.8%. The performance is fully capable of meeting the needs of production practices.

To solve the frost failure problem on super-hydrophobic surfaces in low temperature and high humidity environment, the slippery surface was fabricated by coating with lubricant oil on the rough super-hydrophobic surface. The wettability and microstructures of slippery surfaces were determined. The experimental platforms of frost prevention system and vertical defrosting test system were designed and constructed to investigate the dynamic behavior of frosting and defrosting on slippery surface, super-hydrophobic surface and pure copper surface. The results show that on the slippery surface, the dynamic lubricant film can be generated in the porous and rough structures of the substrate, which can effectively reduce the frost crystal nucleation and prevent the formation of "ice bridge". The frost mass and propagation speed wave on slippery surface are significantly lower than those on super-hydrophobic surface and pure copper surface, which shows better frost inhibition performance. During the process of vertical defrosting and drainage, the defrosting efficiency on each surface is proportional to the frosting mass. The mass and surface coverage of residual water upon defrosting on slippery surfaces are slightly higher than that on super-hydrophobic surface and lower than that on pure copper surface, which exhibits good defrosting and drainage performance.

The performance of Beidou satellite-based augmentation system (BDSBAS) single frequency augmentation service was evaluated and analyzed according to the shortcomings of the research on the corresponding operational performance support of the BDSBAS with the actual data. The calculation process of BDSBAS accuracy enhancement and integrity enhancement was comprehensively sorted out based on the relevant international standards. The process of accuracy enhancement and integrity enhancement was achieved through the publicly broadcast BDSBAS-B1C messages, and the enhancement results were used to evaluate the service performance of BDSBAS in China in the second quarter of 2022 in terms of precision, integrity and availability. The results show that during the test period, the BDSBAS single frequency augmentation service can support the accuracy and availability required for approach procedure with vertical guidance (APV)-I operation, and the horizontal and vertical accuracies respectively range from 1.5 to 5.5 m and from 2.5 to 10.3 m with the availability of APV-I operation of 99.871% (better than 99.000%). Although the transient integrity does not support APV-I, the positioning error is completely enveloped by the protection level without misleading information and dangerous misleading information events.

 Kitchen waste is composed of complex and diverse ingredients with a variety of organic matter and inorganic salts, which is perishable and foul-smelling under high temperature conditions in summer. To reduce the deterioration rate of kitchen waste in the collection and storage process and cool down the kitchen waste in community residences for short time before treatment，the intelligent temperature-controlled dustbin was designed based on the fan-pad cooling device. Several temperature sensors were distributed inside the dustbin and controlled by Siemens PLC.The execution conditions of the fan-pad cooling device were programmed, and the PID algorithm was used for software optimization, while the data was visualized by touch screen. The intelligent control of the fan-pad cooling system was realized to maintain the internal temperature of the dustbin in the set range，and the system debugging and test verification were conducted. The results show that the detection error of the intelligent temperature control system is less than 0.5 ℃, which meets the accuracy requirements. When the outdoor temperature is as high as 35 ℃, the average temperature in the dustbin can be maintained at about 25 ℃, which meets the constant temperature storage requirements of kitchen waste.

To investigate the chaotic characteristics of mixed traffic flow and discern the factors influencing the degree of chaos in mixed traffic platoons, the Cao method and the improved Cao method were employed based on the traditional traffic flow theory to determine the delay time and embedding dimension of the mixed traffic flow. The phase space of mixed traffic flow sequences was reconstructed to determine the chaotic characteristics by calculating the maximum Lyapunov exponent. The influential parameters of the proportion of intelligent connected vehicle (ICV) using cooperative adaptive cruise control (CACC) and the delay time in mixed traffic flow were analyzed. The results show that when the maximum Lyapunov exponent of the headway sequence during the car-following process is less than zero, chaos exists in the mixed traffic flow. Increasing the proportion of CACC vehicles can mitigate chaos in certain time intervals. The car-following system tends to be stable when the proportion of CACC vehicles reaches 0.6. The delay time of CACC vehicles significantly affects chaos, and maintaining low communication delays is essential for CACC vehicles to effectively suppress chaos.

A new finite-time adaptive tracking control scheme based on prescribed performance was developed to solve the control problem of non-strict feedback systems with input delays and dynamic uncertainties. The time-delay systems were transformed into delay-free systems by Pade approximation and auxiliary intermediate variable, and the unmodeled dynamics was handled by the dynamic signal generated by the first-order auxiliary system. The prescribed performance adaptive tracking control was implemented by the hyperbolic tangent function, and the stability analysis was presented based on dynamic surface control method. Taking the second-order nonlinear system with unmodeled dynamics and input delay as example, the numerical simulation of the proposed control strategy was conducted in MATLAB environment . The results show that the proposed control scheme can avoid the singularity in the derivation of virtual control, and all signals in the closed-loop system are bounded in finite time. The tracking error can converge to prescribed time-varying region, and the control algorithm is effective.

For the security concerns of communication data and key in automotive ethernet, an automotive ethernet security communication method based on dynamic keys was innovatively designed. The attack tree model for automotive ethernet security threats was established to analyze the faced security threats. The comprehensive architecture for automotive ethernet security communication methods was constructed to address the threats, and the dynamic key algorithm model was designed to generate implicit dynamic keys. The secure communication method based on dynamic keys was designed to encrypt original data through dynamic keys, and the digests were generated and compared at the receiving end. Communication and network attack processes between domains were simulated using Linux-based systems, I.MX6ULL microcontrollers and Windows devices, and the difference degrees of keys, ciphertexts and plaintexts were compared. The communication process was attacked to analyze the data interactions by Wireshark software. The results show that the proposed method can effectively ensure the key security and the confidentiality, freshness, authenticity and integrity of automotive ethernet data, and it can effectively counter tampering attacks and replaying attacks.

To realize fast and accurate measurement of grain moisture with low cost, the miniaturized channel state information (CSI) acquisition equipment was used for grain moisture detection. Two feature selection algorithms of random forest and principal component analysis were adopted to extract the feature subcarriers of the CSI amplitude index, and the ten kinds of grain moisture were classified based on the selected feature subcarriers. Considering that the application in the mobility scene was limited by power consumption and arithmetic power, the breadth learning system with simple structure, fast operation speed and low arithmetic power requirement was selected for processing CSI data and was compared with the traditional convolutional neural network(CNN) in terms of accuracy and training time. The enhancement nodes of the broad learning system (BLS) were dynamically increased. The experimental results show that the principal component analysis(PCA) algorithm maximally eliminates the redundant information in the CSI data. Compared with the CNN, the BLS can achieve faster speed  and better accuracy. Therefore, the PCA-BLS combination achieves the best classification results. Increasing the number of enhancement nodes can increase the training time, but the recognition accuracy is improved to some extent.

 To solve the problem that the pedestrian dead reckoning (PDR) indoor signals were susceptible to interference from environment and multipath effects, the optimal indoor PDR modelling method based on multi-model fusion was proposed. The system model of the multi-model fusion indoor PDR modelling approach was given with four key stages of step detection, step length projection, direction projection and position projection. In the step detection stage, the peak detection algorithm, local maximum algorithm and advance over zero detection algorithm were integrated, and in the step projection stage, the Weinberg method and Kim method were integrated. The Kalman filter algorithm was used to correct the errors of step detection and step projection. The comparison with traditional algorithms in terms of step number, step length, direction and position errors in different scenarios was completed. The results show that the fused model combines the feature recognition results of traditional step detection and step length estimation algorithms, which can realize the optimization of signal characteristics in the process of step detection and step length estimation. In the handheld scene, the step detection is accurate, and the step length estimation median error range is 0.060 m or less with the minimum direction estimation average absolute error of 3.06° and the position estimation average error of 0.235 3 m, which achieves good indoor walking status recognition and position estimation performance.