Powertrain parameter matching and optimal design of dual-motor driven electric tractor

The rationality of powertrain parameter design has a significant influence on the traction performance and economic performance of electric tractor.At present,researches on powertrain parameter design mainly focus on electric vehicles,and electric agricultural machinery draw much less attention.Therefore,a method of powertrain parameter matching and optimization design for electric tractor was proposed in this paper,which was based on dual-motor coupling drive mode.The particle swarm optimization(PSO)algorithm based on mixed penalty function was used for parameter optimization.Parameter optimization design was programmed using MATLAB.A simulation dynamic model with optimization design variables of electric tractor powertrain was established based on MATLAB/Simulink.Compared with the simulation results before optimization,the objective functions were optimized and the traction performance of electric tractor was improved,which indicated the effectiveness of the proposed method.

Constructing Three-Phase Capillary Pressure Functions by Parameter Matching Using a Modified Ensemble Kalman Filter

Usually extended two-phase capillary pressures are used in three-phase simulations,because three-phase capillary pressures are not possible or hard to measure.In this work three-phase capillary pressure surfaces are created by at pore network model.The input parameters to this network model are found by matching two-phase capillary pressure curves.This matching is done with a slightly modified EnKF routine.Tables with three-phase capillary pressures are created and used as input to flow simulations.

Matching and Simulation of Power Parameters of Electric Transporter based on Cruise Software

In view of the characteristics of warehouse or freight yard carrying out transfer and loading conditions,the performance parameter matching of the power system of an electric transfer vehicle was studied,and the driving motor and power battery of the key components of the vehicle were reasonably selected.Cruise software was used to simulate the loading process of the vehicle.The results show that the performance design of the power system of the electric transport vehicle and its key components is reasonable,meeting the requirements of maximum speed,climbing performance and starting driving performance,and providing a reference and credible basis for the design of the power system of the vehicle.

The Optimal Matching Parameter of Half Discrete Hilbert Type Multiple Integral Inequalities with Non-Homogeneous Kernels and Applications

By using the weight function method,the matching parameters of the half discrete Hilbert type multiple integral inequality with a non-homogeneous kernel K(n,||x||ρ,m)=G(nλ1||x||ρmλ,2)are discussed,some equivalent conditions of the optimal matching parameter are established,and the expression of the optimal constant factor is obtained.Finally,their applications in operator theory are considered.

Optimum Driving System Design for Dual-Motor Pure Electric Vehicles

A pure electric vehicle driven by dual motors is taken as the research object and the driving scheme of the driving motor is improved to increase the transmission efficiency of existing electric vehicles.Based on the architecture of the transmission system,we propose vehicle performance parameters and performance indexes of a pure electric vehicle,a time-sharing driving strategy of dual motors.First,the parameters of the battery,motor,and transmission system are matched.Then,the electric vehicle transmission model is built in Amesim and the control strategy is designed in Simulink.With the optimization goal of improving the vehicle’s dynamic performance and driving range,the optimal parameters are determined through analysis.Finally,the characteristics of the motor are tested on the bench.The results show that the energy-saving potential of the timesharing driven double motor is higher,and the driving mileage of the double motor drive is increased by 4%.

Optimization on conventional and electric air-cycle refrigeration systems of aircraft: A short-cut method and analysis

The air-cycle refrigeration system is widely used in commercial and military aircraft,and its efficiency greatly affects aircraft performance.Nowadays,this system requires a more efficient design and optimization method.In this paper,a short-cut optimization method with high efficiency and effectiveness is introduced for both conventional and electric air-cycle refrigeration systems.Based on the system characteristics,a four-layer parameter matching algorithm is designed which avoids computational difficulty caused by simultaneous equations.Fuel penalty is chosen as the objective function of optimization;design variables are reduced based on sensitivity analysis to improve optimization efficiency.The results show that the 3-variable optimization of the conventional air-cycle refrigeration system can obtain almost the same results as the traditional 6-variable optimization in that these two optimizations can both significantly reduce the fuel penalty.However,the computer running time of the 3-variable optimization is much shorter than that of the 6-variable optimization.The optimal fuel penalty of the electric air-cycle refrigeration system is lower than that of the conventional one.This study can provide reference for optimizing the aircycle refrigeration system of aircraft.

A New Definition of the Hough Transform

This paper's main contributions are three-fold. Firstly, it is shown that the two existing template matching-like definitions of the Hough transform in the literature areinadequate. Secondly, an inherent probabilistic aspect of the Hough transform embedded in the transformation process from image space to parameter space is clarified.Thirdly, a new definition of the Hough transform is proposed which takes into account both the intersection scheme between the mapping curve (or mapping surface) and accumulator cells and the inherent probabilistic characteristics.