Research on the efficiency characteristic of the hydromechanical continuous variable transmission (HMCVT) in tractors is key to obtaining optimal transmission, developing control strategies, and assessing efficiency. To ease and improve the accuracy of obtaining the efficiency completely based on test measurements or theoretical calculation, this study proposes a method for building the HMCVT efficiency model. The method is based on an improved simulated annealing (SA) algorithm according to a small amount of test data. The study uses 8 groups of transmission efficiency values under different operating conditions obtained from bench tests. By theoretical analysis of the HMCVT, this study divides the total transmission efficiency into (i) the transmission efficiency from the output power of the power source to the confluence mechanism, (ii) the transmission efficiency of the confluence mechanism, and (iii) the transmission efficiency of the output part after confluence. The formulas for the three parts of transmission efficiencies are then derived. This study improves the SA algorithm and uses it to identify the three key parameters of hydraulic systems of the transmission efficiency calculation model. Research results indicate that the efficiency model built using the proposed method exhibits high accuracy with an error of about 1.90%. The improved SA algorithm can rapidly complete key parameter identification with an error of about 2.16%; when the displacement ratio is 0, the efficiency values at the same stage are approximately equal under different operating conditions. The HMCVT efficiency model can be built rapidly and effectively with only five groups of efficiency measurement tests.
To build a more accurate motor efficiency model with a strong generalization ability in order to evaluate and improve the efficiency characteristics of electric vehicles, this paper researches motor efficiency modeling based on the bench tests of two motor efficiencies with differently rated powers. This paper compares and analyzes three motor efficiency modeling methods and finds that, when the measured values in motor efficiency tests are insufficient, the bilinear interpolation method and radial basis kernel function neural networks have poor generalization abilities in full working conditions, and the precision of polynomial regression is limited. On this basis, this paper proposes a new modeling method combining correlation analysis, polynomial regression, and an improved simulated annealing (I-SA) algorithm. Using the mean and the standard deviation of the mean absolute percentage error of the 5-fold Cross Validation (CV) of 100 random tests as the evaluation indices of the precision of the motor efficiency model, and based on the motor efficiency models with verified precision, this paper makes a comparative analysis on the full vehicle efficiency of electric tractors of three types of drive in five working conditions. Research results show that the proposed novel method has a high modeling precision of motor efficiency; tractors with a dual motor coupling drive system have optimal economic performance.
A wet clutch is the key component to realize power uninterrupted in agricultural machinery operation. To reduce impact of the system and improve engagement quality, this paper studies and establishes the dynamic load characteristics model of a wet clutch and analyzes three kinds of tractor working conditions. This paper proposes and adopts the method of combining ‘PLS analysis-Improved SA—Comparison of various models-Actual test data’. The results show that with the limit of 100 Nm, the relationship between dynamic load characteristics and oil pressure is opposite. Load is highly inversely correlated with dynamic load, and it has enough precision to build a power curve model only by load (MAPE is 4.5929%). Take a certain type of tractor for example, oil pressure should be maintained at a low level, plowing resistance should be greater than 1600 N and the mass of transportation should avoid 600~1800 kg. This study provides a direct basis for the control, design and performance improvement of agricultural machinery.
There are some problems in the shifting process of hydraulic CVT, such as irregularity, low stability and high failure rate. In this paper, the BP neural network and convolutional neural network are used for fault diagnosis of the HMCVT hydraulic system. Firstly, through experiments, 120 groups of pressure and flow data under normal and four typical fault modes were obtained and preprocessed; they were divided into 80 groups of training samples and 40 groups of test samples via random extraction, using the BP neural network model and convolutional neural network model for fault classification. The results show that compared with BP, PSO-BP and other models, the fault diagnosis rate of the BAS-BP neural network model can reach 92.5%, and the average diagnosis accuracy rate of the convolutional neural network can reach 97.5%, which can be effectively applied to the fault diagnosis of the HMCVT hydraulic system and provide some reference for the shifting reliability of hydraulic CVT.
The hydro-mechanical continuously variable transmission (HMCVT) has complicated transmission characteristics. To analyze the influences of various factors on HMCVT’s efficiency characteristics and build a more precise HMCVT efficiency characteristic model, the paper conducted a full factorial simulation test for and a modeling study on a novel five-stage HMCVT’s efficiency characteristics. The full factorial test considered four factors with a total of 160 groups of test samples and used a range analysis method. Moreover, we proposed a piecewise modeling method for HMCVT efficiency characteristics based on the improved genetic algorithm (I-GA) and compared the precision of seven models. Research results showed that the working stage with the power output from the planet carrier had relatively higher efficiency. The variable pump’s displacement ratio had the greatest influence, and the HMCVT’s efficiency characteristics presented two variation laws with the boundary that the displacement ratio is 0. The load power and the engine speed showed a positive correlation and a negative correlation with the efficiency characteristics, respectively, and the influences decreased as the factor values increased. The modeling method proposed had high modeling precision and the mean absolute percentage error (MAPE) of seven models was in the range of 1.6884~3.1375%. The estimation precision greatly could be improved (the MAPE reduced by 7.7024% and the R2 increased by 9.2943%) by introducing the first-order term of engine speed on the basis of a two-factor model (in which the factors were the displacement ratio and the load power). The paper aimed to offer direct reference information on parameters of the mechanical design and control strategy development of HMCVT from an energy-saving perspective in the design stage.
To improve the speed regulating characteristics of continuously variable transmission for agricultural machinery, in order to meet the engineering and technical requirements of precision agriculture and intelligent agriculture, the paper researches and proposes a method combining the analysis of speed regulating characteristics, regression-based correction, and the improved particle swarm optimization (I-PSO) algorithm. First, the paper analyzes the degree of deviation between the linearization degree and the theoretical value of the speed regulating characteristics of the variable-pump constant-motor system of agricultural machinery according to the measurement results of the bench test. Next, the paper corrects the speed regulating characteristics and compares the regression results based on four models. Finally, the paper proposes a design method for the expected speed regulating characteristics of agricultural machinery and it completes the optimization of speed regulating characteristics and the matching of transmission parameters with the I-PSO algorithm. Results indicate that the speed regulating characteristics of the variable-pump constant-motor system show high linearization (with a coefficient of determination of 0.9775). The theoretical and measured values of the speed regulating characteristics have a certain deviation (with a coefficient of determination of 0.8934). Therefore, correcting the speed regulating characteristics of the variable-pimp constant-motor system is highly necessary. In addition, the second reciprocal function model proposed has the highest correction precision (with a coefficient of determination of 0.9978). The I-PSO algorithm is applicable to the design and application of hydro-mechanical continuously variable transmission (HMCVT) for agricultural machinery. The new method proposed can improve the HMCVT’s speed regulating characteristics efficiently and quickly. It also ensures that the speed regulating characteristics are highly consistent with the expected design characteristics (with a mean error of 1.73%). Thus, the research offers a theoretical direction and design basis for the research and development of continuously variable transmission units in agricultural machinery.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.