Research on the Parameters Optimization of Hydro-mechanical Compound Transmission with MOGA
Author(s) -
Zhen Zhu,
Yingfeng Cai,
Long Chen,
Changgao Xia
Publication year - 2018
Publication title -
destech transactions on engineering and technology research
Language(s) - English
Resource type - Journals
ISSN - 2475-885X
DOI - 10.12783/dtetr/ecar2018/26317
Subject(s) - hill climbing , genetic algorithm , mathematical optimization , interval (graph theory) , multi objective optimization , pareto principle , transmission (telecommunications) , fuel efficiency , optimization problem , computer science , optimal design , control theory (sociology) , mathematics , control (management) , engineering , automotive engineering , telecommunications , machine learning , artificial intelligence , combinatorics
Under the premise of the implementation of optimum control, the coupling optimization considering parameter and control can be used to solve the parameters matching problem of compound transmission system well. This paper takes a typical multi-mode hydro-mechanical compound transmission device as research object, and conducts kinematic analysis. Multi-Objective Genetic Algorithm(MOGA) based on Pareto optimal principle is used to solve the parameters optimization problem, including the choice of design variables, the determination of optimization goals, the imposition of constraints, and so on. The optimization model of transmission system is established, climbing angle and fuel consumption rate are considered as objective functions of dynamic performance and fuel economic performance, experimental design and optimization algorithm are combined to seek the optimum solution by global search. The results show that climbing angle ( o ) average value is 27.259, 99% confidence interval is [26.074, 28.445], and Pareto optimal solution is 27.931; fuel consumption rate (g/kW·h) average value is 208.876, 99% confidence interval is [208.622,209.130], and Pareto optimal solution is 206.760. The climbing angle increases with the decrease of the fuel consumption rate, so the optimal solution can be selected according to the actual needs. Introduction The research on the transmission system energy management is mainly centralized in power split hybrid vehicles. Mehdi Mahmoodi-k from Iran University of Science and Technology carried on the research on the energy management method with multi-input fuzzy control optimization, and made a comparison with the control method based on rules [1] . Emmanuel Vinot from Brown University carried on global optimization design, and optimized system parameters by genetic algorithm [2] . He Hongwen from Beijing Institute of Technology identified the engine optimal running track, and improved power management calibration precision [3] . In virtue of maturing hybrid power technology, this paper will blaze a new trail, and focus on the transmission system, especially the multi-mode hydro-mechanical compound transmission system, in order to realize energy management strategy optimization for large horsepower tractors [4-6] . Hydro-mechanical transmission can realize high efficiency transmission and stepless speed change, however, it is difficult to meet the requirements of flexible operation for starting condition, and efficient operation for transfer condition. Parameters optimization problem of compound transmission device based on energy management strategy under the condition of multi-objective constraints can be solved by dynamic programming algorithm, which is becoming a hot spot of recent research. Theoretical Basis System matching and optimization control are the key issues, which are closely related and interdependent. The heavy reliance of transmission system on control method bring conspicuous
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