Liqun Lu

Fractional-order constitutive models provide an effective tool for describing the mechanical properties of viscoelastic materials. The Scott Blair model serves as the fundamental element in fractional viscoelastic theory. In this paper, we address the inherent connection between the Scott Blair model and integer-order differential models. To this end, the springpot element is schematically represented by the generalized Maxwell network and the Kelvin-Voigt network, respectively. By adopting the infinite state approach for the fractional integrator, the stiffness and viscosity coefficients are identified and shown to follow a distribution pattern. Furthermore, the above two networks are employed to determine the calculation formulas for energy storage and dissipation in the springpot element. Equivalencies between fractional energy formulas are verified under harmonic vibration conditions. Finally, the aforementioned methods are applied to the fractional Kelvin-Voigt model, and numerical simulations are carried out. The two distributed networks, as schematic representations of the springpot element, reveal the relationship between fractional and integer-order differential constitutive models, offer an effective approach for analyzing and computing the dynamic response of viscoelastic structures, endow the infinite state approach with physical significance and intuitive meaning, and readily lend themselves to application in various disciplines.

The electro-hydraulic hybrid system has emerged as a critical technology in new energy vehicles, owing to the remarkable power density and efficient energy regeneration capabilities of hydraulic technology, coupled with the high energy density of electric power. This system effectively enhances vehicle range and battery life. We developed an energy management strategy (EMS) for the electro-hydraulic hybrid system (EHHS) to ensure smooth energy conversion, while ensuring the full utilization of electrical and hydraulic energy within a reasonable and efficient range. To enhance the system’s overall performance, it is imperative to address pivotal technologies, including power coupling and energy management. In this research, the structure of an electro-hydraulic hybrid vehicle (EHHV) is classified, compared and discussed. The application of existing EHHVs is studied. Subsequently, an analysis and summary are conducted on the current status and development trends of EMSs and collaborative operation control strategies (COCSs), and a novel mechanical-electro-hydraulic power-coupled system (MEHPCS) is put forward that successfully converts mechanical, electrical, and hydraulic energy in performance. Simultaneously, other applications of the system are forecasted. Finally, some suggestions for the electro-hydraulic hybrid systems’ future development are made. This study can promote the development of sustainable transportation technologies. The system integrates mechanical engineering, control theory, and environmental science, enabling interdisciplinary methodological innovation. In addition, relevant studies provide data support for policy makers by quantifying energy consumption indicators.

In order to accurately obtain the seedling emergence rate of breeding sunflower and to assess the quality of sowing as well as the merit of sunflower varieties, a method of extracting the sunflower seedling emergence rate using multi-source remote sensing information from unmanned aerial vehicles is proposed. Visible and multispectral images of sunflower seedlings were acquired using a UAV. The thresholding method was used to segment the excess green image of the visible image into vegetation and non-vegetation, to obtain the center point of the vegetation to generate a buffer, and to mask the visible image to achieve weed removal. The components of color models such as the hue–saturation value (HSV), green-relative color space (YCbCr), cyan-magenta-yellow-black (CMYK), and CIELAB color space (L*A*B) models were compared and analyzed. The A component of the L*A*B model was preferred for the optimization of K-means clustering to segment sunflower seedlings and mulch using the genetic algorithm, and the segmentation accuracy was improved by 4.6% compared with the K-means clustering algorithm. All told, 10 geometric features of sunflower seedlings were extracted using segmented images, and 10 vegetation indices and 48 texture features of sunflower seedlings were calculated based on multispectral images. The Pearson’s correlation coefficient method was used to filter the three types of features, and the geometric feature set, the vegetation index set, the texture feature set, and the preferred feature set were constructed. The construction of a sunflower plant number estimation model using the crested porcupine optimizer–support vector machine is proposed and compared with the sunflower plant number estimation models constructed based on decision tree regression, BP neural network, and support vector machine regression. The results show that the accuracy of the model based on the preferred feature set is higher than that of the other three feature sets, indicating that feature screening can improve the accuracy and stability of models; assessed using the CPO-SVR model, the accuracy of the preferred feature set was the highest, with an R² of 0.94, an RMSE of 5.16, and an MAE of 3.03. Compared to the SVR model, the value of the R² is improved by 3.3%, the RMSE decreased by 18.3%, and the MAE decreased by 18.1%. The results of the study can be cost-effective, accurate, and reliable in terms of obtaining the seedling emergence rate of sunflower field breeding.

In order to improve the accuracy of multispectral image inversion of soil and plant analytical development (SPAD) of the cotton canopy, image segmentation methods were utilized to remove the background interference, such as soil and shadow in UAV multispectral images. UAV multispectral images of cotton bud stage canopies at three different heights (30 m, 50 m, and 80 m) were acquired. Four methods, namely vegetation index thresholding (VIT), supervised classification by support vector machine (SVM), spectral mixture analysis (SMA), and multiple endmember spectral mixture analysis (MESMA), were used to segment cotton, soil, and shadows in the multispectral images of cotton. The segmented UAV multispectral images were used to extract the spectral information of the cotton canopy, and eight vegetation indices were calculated to construct the dataset. Partial least squares regression (PLSR), Random forest (FR), and support vector regression (SVR) algorithms were used to construct the inversion model of cotton SPAD. This study analyzed the effects of different image segmentation methods on the extraction accuracy of spectral information and the accuracy of SPAD modeling in the cotton canopy. The results showed that (1) The accuracy of spectral information extraction can be improved by removing background interference such as soil and shadows using four image segmentation methods. The correlation between the vegetation indices calculated from MESMA segmented images and the SPAD of the cotton canopy was improved the most; (2) At three different flight altitudes, the vegetation indices calculated by the MESMA segmentation method were used as the input variable, and the SVR model had the best accuracy in the inversion of cotton SPAD, with R² of 0.810, 0.778, and 0.697, respectively; (3) At a flight altitude of 80 m, the R² of the SVR models constructed using vegetation indices calculated from images segmented by VIT, SVM, SMA, and MESMA methods were improved by 2.2%, 5.8%, 13.7%, and 17.9%, respectively, compared to the original images. Therefore, the MESMA mixed pixel decomposition method can effectively remove soil and shadows in multispectral images, especially to provide a reference for improving the inversion accuracy of crop physiological parameters in low-resolution images with more mixed pixels.

The suspension system’s performance has a direct impact on the ride comfort, handling stability, and driving safety of heavy vehicles. The active air suspension of heavy vehicles can adjust the stiffness, damping parameters, and body height in real-time based on different road conditions. This adjustment ensures that the entire vehicle experiences a smooth ride while also making vehicle loading and unloading more labor efficient. Additionally, the active air suspension system enables the vehicle to achieve automation and intelligence. This study focused on a particular 6 × 4 heavy vehicle and designed an active air suspension system that aligns with the vehicle parameters of the heavy truck. Through the use of a fuzzy PID active control strategy, this study investigated and analyzed the height adjustment of the air spring. The results indicate that at a vehicle speed of 60 km/h on a class A road surface, the vehicle body’s vertical acceleration was reduced by 22.1%, and the dynamic travel of the suspension was reduced by 20.1%. This indicates that the fuzzy PID active air suspension system effectively reduces the vehicle’s vibrations and improves ride comfort.

Compared with the traditional automotive suspension, hydro-pneumatic suspension has the characteristics of large energy storage ratio, nonlinear stiffness and can change the ground clearance of the vehicle body, which makes the vehicle have good ride comfort and handling stability during driving. In order to improve the performance of hydro-pneumatic suspension, it is necessary to design hydro-pneumatic suspension test bench for performance test. Aiming at the problem that the output signal of the mechanical test bench used in China is single and has large error, which is difficult to meet the performance test requirements of hydro-pneumatic suspension, a hydro-pneumatic suspension test bench based on electro-hydraulic proportional control is designed. Through AMESim/MATLAB joint system modeling and simulation, in the tracking comparison of sinusoidal signal, compared with the traditional PID control method, the fuzzy PID control method reduces the error by 56.8% and the lag time by 70%; Through the experimental analysis of hydro-pneumatic suspension elastic force characteristic diagram, indicator diagram and damping force velocity characteristic diagram, the error rate of the test bench in sinusoidal signal tracking experiment is less than 15%, which meets the test requirements of hydro-pneumatic suspension.

By effectively integrating traditional engines with reciprocating plunger pumps, the constrained piston hydraulic engine can simultaneously output hydraulic energy and rotational mechanical energy, which effectively solves the problems of the complex structure, long power transmission chain, and low energy conversion efficiency of traditional power sources. Based on a certain single-cylinder diesel engine, a single-cylinder axial constrained piston hydraulic engine was designed, and its thermal–mechanical–liquid coordination mechanism was studied and analyzed in-depth. A mathematical model of the thermal–mechanical–liquid coupling working process of the single-cylinder axial hydraulic engine was established, and the conversion mechanism and output of the three types of energy, thermal, mechanical, and liquid, were simulated and analyzed. The results show that under the premise of improving the overall efficiency, the constrained piston hydraulic engine can effectively output mechanical–hydraulic dual-element power, and its combustion characteristics and output power performance indicators meet the expected design requirements. The maximum amplitude difference of the output hydraulic oil flow rate reaches 248 L/min, and the flow rate fluctuates greatly, so it is necessary to adopt methods to suppress the flow rate pulsation to ensure the reliability of the output flow rate.

To solve the brake caliper disc brake piston sealing ring in the high temperature, pressure, and changeful, complex working environments, such as vibration failure cause brake short service life, low reliability, in the original brake piston O seal ring and cross section, the research, based on the standard of sealing ring, such as special-shaped seal structure is put forward in order to improve the reliability of the caliper disc brake piston sealing performance. Based on the basic concept of time-varying reliability and the theoretical basis of stress-strength interference model, the time-varying reliability model of the plum blossom seal ring of the brake piston under shear stress failure and leakage failure modes was established. The reliability of the plum blossom seal ring under single failure mode and multiple failure modes is obtained. The results show that under the same conditions, the reliability of the plum blossom seal ring is greater than that of the O seal ring, and its sealing performance is better than that of the O seal ring.

Due to the harsh working environment of the tractor, the transmission can often be faulty. In order to ensure the reliability of its operation, it must be monitored and the fault discovered. In this paper, the support vector machine (SVM) method is used. The eigenvector conversion of the original data uses the following eigenvectors: Three fault modes (leakage fault of shift clutch hydraulic cylinder, blockage fault of oil passage, and blockage fault of proportional valve spool) are identified in matrix and laboratory (MATLAB) with the help of the library for support vector machines (LibSVM) toolkit, and the classification accuracy of test samples is 90%. The normal mode of the PST electro-hydraulic system and the three kinds of fault modes mentioned above are discriminated against, and the correct rate of fault diagnosis reaches 95%, which meets the needs of practical engineering. Analysis of the fault recording data of the power shifting transmission shift solenoid valve shows that the difference between fault pressure data and normal data is small, and the value of traffic data is greater. This method can realize the fault mode online recognition based on controller area network (CAN) communication, and the research results provide a theoretical basis for the fault diagnosis of the PST electro-hydraulic control system.