A basis for the computer-aided design of the topological structure of planetary gear trains. (March 2020)

• Record Type: Journal Article
• Authors: Du, Mao; Yang, Lin
• Is Part Of: Mechanism and machine theory. Volume 145(2020)
• Publication Date: 2020-03
• Subjects: Optimal topology design -- Planetary gear train -- Graph theory -- Automatically -- Computer-aided design -- Multi-power system; Machine theory -- Periodicals; Machinery -- Periodicals; Machines -- Périodiques; Génie mécanique -- Périodiques; Machine theory; Machinery; Periodicals; 621.81
• DOI: 10.1016/j.mechmachtheory.2019.103690
• Languages: English
• ISSNs: 0094-114X

Abstract

Highlights: The gearbox with PGTs is modularized for multi-source power systems with multiple power sources, and the coefficient library is established for the modules. A tree structure model reflecting the energy distribution inside the gearbox is first established by using a reverse search algorithm. A forward-backtrack algorithm is used to analyse the dynamics and kinematics of the gearbox. The transfer efficiency and cyclic power are obtained automatically. Abstract: The design of the optimal topology of transmission systems based on planetary gear trains (PGTs) has become one of the most important problems for the development of many multi-source power systems, such as hybrid electric vehicles (HEVs). However, due to the lack of a method for large-scale scheme design and comparison, the form of manual design often faces heavy workloads and a risk of missing the optimal topology. At present, computer identification and automatic calculation of dynamic parameters for multi-input and multi-DOF structures under different working states remains the key objective of large-scale computing and computer-based optimalization design. To solve these problems, this paper modularizes the topological structures of PGTs and proposes two algorithms based on the connectivity of connected graphs for the first time: the reverse search algorithm and the forward-backtrack algorithm. The results show that the proposed method can not only enable a computer to effectively identify the components of a structure under different working modes but can also automatically obtain the dynamic parameters, transmission efficiency, power flow and recirculating power, thus providing a basis for calculating the optimal topological structure in large-scale design schemes.