Optimization of the transmission characteristics of an HMCVT for a high-powered tractor based on an improved NSGA-II algorithm

2022 ◽  
pp. 095440702110679
Author(s):  
Jiang Li ◽  
Zhiqiang Zhai ◽  
Zhansheng Song ◽  
Shenghui Fu ◽  
Zhongxiang Zhu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Optimization Design ◽  
Structural Parameters ◽  
Population Diversity ◽  
Operating Conditions ◽  
Power Performance ◽  
Transmission Characteristics ◽  
Nsga Ii ◽  
Pareto Solution ◽  
Multi Objective

The hydro-mechanical continuously variable transmission (HMCVT) is a critical component of the power transmission system in a tractor. However, the complexity of the operating conditions imposes high requirements on the transmission characteristics. To improve the powerful performance and economy of HMCVTs and satisfy the operational demands of high-powered tractors, a new optimization design method for the characteristic parameters of an HMCVT is proposed. First, the characteristics of an HMCVT are modeled, and the influence of the structural parameters on the transmission characteristics is analyzed. Then, HMCVT performance evaluation indexes are formulated. In accordance with the speed regulation of system, power performance, and economy characteristics, a multi-objective optimization mathematical model is established, and an improved fast non-dominated sorting genetic algorithm (INSGA-II) is designed. The introduction of a normal distribution crossover operator (NDX) and an improved adaptive adjustment mutation operator not only ensures the population diversity but also improves the Pareto solution convergence properties during the process of genetic evolution. The superiority of INSGA-II is verified by comparison with a traditional multi-objective genetic algorithm. Finally, the optimization results show that the torque ratio is increased by approximately 2.81%, 14.32%, 2.31%, and 15.07% in HM1, HM2, HM3, and HM4 respectively. The transmission efficiency is increased by approximately 3.48% and 1.97% in HM1 (HM3) and HM2 (HM4). Also, INSGA-II finds the optimal solution with a faster speed and shorter optimization time than MULGA. This research can serve as a reference for the design and optimization of HMCVTs for high-powered tractors.

Study of the Non-Dominated Sorting Genetic Algorithm for the Optimal Structural Parameter of the Tooth-Arrangement Multi-Fingered Dextrous Hand

2013 ◽  
Vol 756-759 ◽  
pp. 4082-4089
Author(s):  
Zhan Li Li ◽  
Xiang Ting He
Keyword(s):  
Genetic Algorithm ◽  
Parameter Optimization ◽  
Experimental Results ◽  
Structural Parameter ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Pareto Solution ◽  
Multi Objective ◽  
Dextrous Hand

Firstly, the structural parameter optimization of the tooth-arrangement multi-fingered dextrous hand is studied. Secondly, as to the shortcomings that the Pareto solution of multi-objective optimization was distributed unevenly in NSGA-II, a non-dominated sorting genetic algorithm based on immune principle is proposed. Lastly, the structural parameter of the medical tooth-arrangement multi-fingered dextrous hand is optimized using the proposed algorithm. The experimental results show that this algorithm can optimize structural parameter of tooth-arrangement multi-fingered dextrous hand very well.

Applications of Multi-Objective Genetic Algorithm in Optimizing Steering Performances for Submersible

2013 ◽  
Vol 756-759 ◽  
pp. 3136-3140
Author(s):  
Zhuo Yi Yang ◽  
Yong Jie Pang ◽  
Shao Lian Ma
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Approximation Model ◽  
Horizontal Movement ◽  
Nsga Ii ◽  
Hydrodynamic Coefficient ◽  
Pareto Solution ◽  
Multi Objective ◽  
Minimum Drag ◽  
Multi Objective Genetic Algorithm

Multi-objective arithmetic NSGA-II based on Pareto solution is investigated to deal with integrated optimal design of speedability and manoeuvre performances for submersible. Approximation model of resistance for serial revolving shape is constructed by hydrodynamic numerical calculations. The appraisement criterions of stability and mobility are calculated from linear equation of horizontal movement by estimating hydrodynamic coefficient of submersible. After optimization, the scattered Pareto solution of drag and turning diameter are gained, and from the solutions designer can select the reasonable one based on the actual requirement. The Pareto solution can ensure the minimum drag in this manoeuvre performance or the best manoeuvre performance in this drag value.

scholarly journals Multi-Objective Optimization Design of a Novel Integral Squeeze Film Bearing Damper

Machines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 206
Author(s):  
Yipeng Zhang ◽  
Lidong He ◽  
Jianjiang Yang ◽  
Gang Zhu ◽  
Xingyun Jia ◽  
...  
Keyword(s):  
Optimization Design ◽  
Structural Parameters ◽  
Rotor System ◽  
Squeeze Film ◽  
Optimization Strategy ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Practical Applications ◽  
Multi Objective ◽  
Transmitted Force

In order to better control the vibration of the rotor system so as to improve the stability and safety of the rotor, a novel vibration control solution is needed. In this paper, the multi-objective optimization problem is used for designing a novel integral squeeze film bearing damper (ISFBD). The method attempts to reduce the stiffness and stress convergence of ISFBD, which can greatly decrease the transmitted force of the rotor system and better use the damping effect to dissipate the vibration energy. The finite element model of ISFBD is established to analyze the stiffness and stress, and the correctness of the calculation is verified by setting up a stiffness test platform. The sensitivity of different structural parameters of stiffness and stress is analyzed by ANOVA. Meanwhile, the non-dominated sorting genetic algorithm (NSGA-II) and grey correlation analysis (GRA) algorithms are coupled for multi-objective optimization of stiffness and stress. The results indicate that optimized ISFBD can distribute 26.6% of the rotor system’s energy and reduce 59.3% of the transmitted force at the bearing location. It is also proved that the optimization strategy is effective, which can provide a useful method for ISFBD design in practical applications.

scholarly journals Optimal Design of a Novel Magnetic Twisting Device Based on NSGA-II Algorithm

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Xu Qiao ◽  
He Yuchen ◽  
Mei Shunqi ◽  
Chen Zhen ◽  
Wang Shaojun ◽  
...  
Keyword(s):  
Optimization Design ◽  
Structural Parameters ◽  
Multi Objective Optimization ◽  
Algorithm Optimization ◽  
Transmission Characteristics ◽  
Nsga Ii ◽  
New Device ◽  
Contact Transmission ◽  
Magnetic Drive ◽  
Maximum Transmission

Abstract This paper presents a novel magnetic twisting device with a coaxial double rotor based on non-contact transmission characteristics of magnetic drive technology. When the twisting device rotates one cycle, the yarn can get triple twists. This means the new device can twist three times more than what the traditional single twist does. The structure of the magnetic twisting device is designed according to the twisting principle. The influence of main structural parameters on the magnetic torque is analyzed. To optimize the maximum transmission torque and the minimum magnet volume, the multi-objective optimization design model for the twisting device is established. Main parameters such as the relative angle of active disc assembly and passive disc assembly, the thickness of magnet, and the average radius of the magnet distribution are optimized by NSGA-II algorithm. Optimization results show that the proposed structural optimization design of a twisting device based on the magnetic drive has excellent performance and is effective for industrial application.

scholarly journals RV reducer Design Using Resnet-based model and integration of Discretized OPtimization

2021 ◽  
Author(s):  
Jiacheng Miao ◽  
Chaoyang Li ◽  
Bingkui Chen
Keyword(s):  
Optimization Design ◽  
Evaluation Method ◽  
Structural Parameters ◽  
Structure Design ◽  
Design Model ◽  
System Structure ◽  
Enhancement Effect ◽  
Nsga Ii ◽  
Multi Objective ◽  
Rv Reducer

Abstract A new type of mechanical system structure design model is proposed, which uses a small number of system feature samples to generate a new structure model. In this model, (1) the theory of limited sample recommendation algorithm is used to study the external dimensions recommendation of the reducer, an SG-Resnet network suitable for the generation of reducer structure parameters is established, the main factors affecting the promotion ability and learning rate of the SG-Resnet network structure are analyzed through hyperparameters, and in-depth study of the mechanism of each influencing factor. (2) Establish an optimization design method for the internal dimensions of the reducer, and initially calculate the structural parameters according to the basic performance parameters of the reducer, combine the objective function and constraint conditions to establish the corresponding multi-objective optimization model, and establish the Kriging proxy model. The mixed population NSGA-II algorithm is proposed, the MP-NSGA-II algorithm is used to obtain multiple sets of Pareto optimal solutions, and the multi-objective evaluation method is used to select the optimal solution from the non-dominated solution set. Experiments were carried out to verify the positive enhancement effect of the structural design model on the stiffness of the reducer. The experiment showed the reliability and generalizability of the model. This research provides a new solution for reducer design and lays a solid foundation for the development of integrated RV reducer forward design software.

Multi-Objection Optimization Design of Automobile Transmission System

2012 ◽  
Vol 590 ◽  
pp. 231-235
Author(s):  
Yong Hai Wu ◽  
Feng Wang
Keyword(s):  
Optimization Design ◽  
System Optimization ◽  
Transmission System ◽  
Population Diversity ◽  
Energy Utilization ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Standing Start ◽  
Poor Population

In this paper the Six-speed transmission with belt overdrive gear of one automobile transmission system will be taken as research object, automobile energy utilization ratio and standing start continuous shift acceleration time will be regarded as objective function, the multi-objective optimization model of automobile transmission system will be established. The improved congestion degree calculation and choose operation method will be put forward according to the problem that poor population diversity when NSGA-II algorithm was used in the transmission optimization, the improved NSGA-II algorithm will be used to implement multi-objective optimization design on the automobile transmission system. Optimization results show that Pareto optimal solutions obtained from the improved algorithm are more evenly distributed and algorithms are more efficient. The improved NSGA-II algorithm used in this paper is also suitable for other areas of computing multi-objective optimization problem.

scholarly journals Multi-objective topology optimization of magnetic couplers for wireless power transfer

2020 ◽  
Vol 64 (1-4) ◽  
pp. 325-333
Author(s):  
Yunyi Gong ◽  
Yoshitsugu Otomo ◽  
Hajime Igarashi
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Wireless Power Transfer ◽  
Power Transfer ◽  
Wireless Power ◽  
Nsga Ii ◽  
Pareto Solution ◽  
Good Balance ◽  
Multi Objective ◽  
Gaussian Network

In this paper, the multi-objective topology optimizations of wireless power transfer (WPT) devices with two different coil geometries are proposed for obtaining the designs with good balance between transfer efficiency and safety. For this purpose, the proposed method adopts the normalized Gaussian network (NGnet) and Non-dominated Sorting Genetic Algorithm II (NSGA-II). In addition, the optimization under the different constraint on ferrite volume is carried out to verify its influence on optimization results. It has been shown that the proposed method successfully provides the Pareto solution to the design problem of the WPT device.

Multi-Objective Design Optimization for Product Platform and Product Family Design Using Genetic Algorithms

2005 ◽  
Author(s):  
Satish V. K. Akundi ◽  
Timothy W. Simpson ◽  
Patrick M. Reed
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Genetic Algorithms ◽  
Product Family ◽  
Optimization Techniques ◽  
Product Platform ◽  
Product Family Design ◽  
Nsga Ii ◽  
Pareto Solution ◽  
Multi Objective

Many companies are using product families and platform-based product development to reduce costs and time-to-market while increasing product variety and customization. Multi-objective optimization is increasingly becoming a powerful tool to support product platform and product family design. In this paper, a genetic algorithm-based optimization method for product family design is suggested, and its application is demonstrated using a family of universal electric motors. Using an appropriate representation for the design variables and by adopting a suitable formulation for the genetic algorithm, a one-stage approach for product family design can be realized that requires no a priori platform decision-making, eliminating the need for higher-level problem-specific domain knowledge. Optimizing product platforms using multi-objective algorithms gives the designer a Pareto solution set, which can be used to make better decisions based on the trade-offs present across different objectives. Two Non-Dominated Sorting Genetic Algorithms, namely, NSGA-II and ε-NSGA-II, are described, and their performance is compared. Implementation challenges associated with the use of these algorithms are also discussed. Comparison of the results with existing benchmark designs suggests that the proposed multi-objective genetic algorithms perform better than conventional single-objective optimization techniques, while providing designers with more information to support decision making during product family design.

Multi-objective optimization of squirrel cage fan for range hood based on Kriging model

2021 ◽  
pp. 095440622199586
Author(s):  
Qianhao Xiao ◽  
Jun Wang ◽  
Boyan Jiang ◽  
Weigang Yang ◽  
Xiaopei Yang
Keyword(s):  
Flow Rate ◽  
Optimization Design ◽  
Volume Flow Rate ◽  
Kriging Model ◽  
Volume Flow ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Squirrel Cage

In view of the multi-objective optimization design of the squirrel cage fan for the range hood, a blade parameterization method based on the quadratic non-uniform B-spline (NUBS) determined by four control points was proposed to control the outlet angle, chord length and maximum camber of the blade. Morris-Mitchell criteria were used to obtain the optimal Latin hypercube sample based on the evolutionary operation, and different subsets of sample numbers were created to study the influence of sample numbers on the multi-objective optimization results. The Kriging model, which can accurately reflect the response relationship between design variables and optimization objectives, was established. The second-generation Non-dominated Sorting Genetic algorithm (NSGA-II) was used to optimize the volume flow rate at the best efficiency point (BEP) and the maximum volume flow rate point (MVP). The results show that the design parameters corresponding to the optimization results under different sample numbers are not the same, and the fluctuation range of the optimal design parameters is related to the influence of the design parameters on the optimization objectives. Compared with the prototype, the optimized impeller increases the radial velocity of the impeller outlet, reduces the flow loss in the volute, and increases the diffusion capacity, which improves the volume flow rate, and efficiency of the range hood system under multiple working conditions.

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